Johann Hofmann - 
              Your speaker and expert for industry 4.0

              After completing his mechanical engineering studies in 1989, Johann Hofmann began to systematize the flow of data and information in a paperless manner as head of NC programming at Maschinenfabrik Reinhausen. Step by step, the unique ValueFacturing® assistance system with integrated data hub and data pump was created.

              After decades of persistence, a digital solution for high-performance production was created, with which Johann Hofmann brought the INDUSTRIE 4.0 AWARD for Maschinenfabrik Reinhausen to Regensburg in 2013.

              As a mechanical engineer with over 30 years of experience in digitization, Johann Hofmann has developed his talent for communicating complex issues in an informative and entertaining way.


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                                                                                      Adaptive systems have a special adaptability to the respective environment.

                                                                                      If this term is projected into the production halls, it is synonymous here with a new form of flexibility in production processes. The starting point for this is described by the term Data Governance (e.g. networking and data security). Based on this i40-Components can be networked with MOM-Systems . This is how adaptive production is gradually created in the  Smart Factory.

                                                                                      Additive manufacturing, also known as 3D printing, is a manufacturing process that uses 3D CAD data to create a component layer by layer by depositing material. In principle, the existing manufacturing processes such as:

                                                                                      • Casting

                                                                                      • Forging

                                                                                      • Milling

                                                                                      • Drilling

                                                                                      • Welding or

                                                                                      • Soldering will be added with another manufacturing process, the 3D printing.

                                                                                      This is why I do not place this term under the heading INDUSTRY 4.0, but see it as an independent technology.

                                                                                      Active learning is a subfield of Machine Learning

                                                                                      AMQP stands for Advanced Message Queuing Protocol.

                                                                                      It is an asynchronous and binary protocol for message transmission, which is independent of the programming language. AMQP has been jointly developed by large companies, including Microsoft, Cisco, VMware, Bank of America, and many others.
                                                                                      Just like MQTT, AMQP is a protocol in the environment of IoT.

                                                                                      Further information about AMQP can be found here.

                                                                                      The abbreviation XaaS stands for the term "Anything as a Service". The term Everything as a Service (EaaS) is often used in parallel. XaaS refers to an approach of providing and consuming "everything" as a service. It is therefore the logical last step after the following subsets already exist as a service:

                                                                                      1. Software as a Service (SaaS)

                                                                                      2. Platform as a Service (PaaS)

                                                                                      3. Infrastructure as a Service (IaaS)

                                                                                      As a rule, all other, additional services are attributable to one of these three core services SaaS, PaaS or Iaas. SaaS, PaaS. oder IaaS zurückzuführen.

                                                                                      The term App is derived from the word Application (application software). Currently, a mobile app is a slim application software that is available on the Internet for downloading to smartphones. In contrast to system programs, mobile apps always have a direct benefit, but their range of functions is limited. In the future, apps will probably leave this limitation behind and increasingly replace system programs.
                                                                                      See also the entry: DIGITAL VALUE

                                                                                      Artificial Intelligence as a Service (AIaaS) refers totificial Intelligence as a Service (AIaaS) bezeichnet man Artificial Intelligence (AI) from the Cloud
                                                                                      This is one of the most innovative services.
                                                                                      The possibility to obtain AI as a service enables, among others, start-up companies to realize their ideas without large initial investments and risks.
                                                                                      AI from the cloud comprises a wide range of services from which the appropriate services can be selected according to individual needs. One disadvantage, however, is that almost all commercial AIaaS providers do not publish the algorithms. It is therefore a kind of "black box", i.e. extensive and systematic tests to verify the results can take a long time.

                                                                                      Some of the known types of AIaaS include Bots and Machine Learning.

                                                                                      Alternatively, AIaaS is also called: Cognitive Services

                                                                                      Assistance systems assist people and enable them to make better decisions. This is because assistance systems reduce the "working" complexity that "arrives" at humans to a manageable level. In addition, assistance systems support the development of the user's competence through supporting measures. Cognitive assistance systems are able to produce the following positive effects:

                                                                                      1. Assistance systems improve the results. 
                                                                                        The car's brake assistant, which improves stopping distance and lane keeping when braking, can serve as a metaphor.

                                                                                      2. Assistance systems promote the competence development of the user. 
                                                                                        The navigation system in the car can serve as a metaphor, giving non-local drivers the ability to navigate in foreign cities.

                                                                                      3. Assistance systems make the otherwise impossible possible. 
                                                                                        As a metaphor we can use a modern fighter plane, which cannot be flown by the pilot alone without assistance systems. 

                                                                                      The ValueFacturing® assistance system enables the production planner to orchestrate complete machine groups.

                                                                                      Assistance precedes autonomy and enables people to make better decisions. Even in future fully autonomous systems (e.g., self-propelled cars), an assistance system will enable people to have numerous possibilities of influence.

                                                                                      Especially fascinating about Industry 4.0 is the following:

                                                                                      • Assistance systems that assist humans and

                                                                                      • autonomous systems that replace humans (e.g. as car drivers) and

                                                                                      • the freedom for people to choose and decide at will about the meaningfulness

                                                                                      An Augmented Operator is an employee who, among other things, uses IT-based assistance systems to expand his view of the factory.
                                                                                      People thus consciously retain a central role in all relevant processes of Smart Factory.
                                                                                      Its tasks can be named as follows:

                                                                                                     observe - understand - evaluate - decide - take responsibility

                                                                                      In this control loop, he can influence targets according to situation and context.
                                                                                      He performs these tasks via mobile devices, such as tablet PCs or smartphones. In the future, the employee 4.0 with the data glasses and the telephone headset on his head will always carry all technical requirements with him to be able to react in seconds. In addition, they will be able to intervene in production from anywhere in the world via these mobile devices, for example, and monitor and control operating and product statuses via real-time images. This requires stronger interdisciplinary action and thinking as well as a distinctive foresight, so that the questions of the future are not answered with yesterday's answers.

                                                                                      Augmented Reality (or "augmented reality") expands the human perception of the real world by fading in additional virtual information. The merging of these two worlds is called Augmented Reality (AR).  The user needs Augmented Reality glasses, such as the Microsoft Hololens. 

                                                                                      Augmented Reality can also be experienced in an attenuated form with smartphone, tablet, or head-up display.
                                                                                      The Virtual Reality (VR) User sees 100% virtual images
                                                                                      The Augmented Reality (AR) User sees a mixture of real and virtual images, which are not spatially related to each other
                                                                                      The Mixed Reality (MR) User sees a mixture of real and virtual images that have a spatial relationship to each other.


                                                                                      A one-dimensional barcode is an electronically readable font consisting of various wide, parallel bars and gaps. The barcode is read in by machine with optical reading devices, such as scanners, and processed electronically. The best known barcode scanners are probably the supermarket cash registers. This one-dimensional bar code is also called bar code, bar code or bar code. A one-dimensional barcode can contain a maximum of 40 digits or 20 characters. Depending on the required information density, there are different one-dimensional barcode types.

                                                                                      Here you find a: List of all Barcodetypes

                                                                                      Batch learning is a subfield of Machine Learning.

                                                                                      Big Data is first of all just a collection of stupid raw data and refers to amounts of data that can no longer be processed using conventional methods of data processing. This amount of data is growing due to the technical development and that of the Internet, as it is becoming increasingly easier to collect, store and analyze large amounts of data.
                                                                                      Big Data is virtually a collective term for digital mass data, which opens up completely new possibilities in technical terms.
                                                                                      However, the added value of Big Data is only created when this raw data (Data Lake) is refined by heuristics or pattern recognition (Data Mining). Thus one comes to new knowledge gain (Smart Data ).
                                                                                      The definition of Big Data includes the following 5 dimensions: 

                                                                                            1. volume  (Volume of data)
                                                                                            2. velocity  (Speed at which the data volumes are moving)
                                                                                            3. variety (Variance or diversity of the data)
                                                                                            4. value (added business value through the data)
                                                                                            5. validity  (Correctness of the data)

                                                                                      Big-Data gets through Data-Mining to Smart-Data

                                                                                      The term "Bin Picking" stands - for the so-called "grip into the box" by a robot. In many automation solutions, workpieces are fed to a machine by a robot. These workpieces are usually stored unsorted (but mostly sorted by type) in a box pallet or other container. It is a special challenge for the robot to always grip the chaotically stacked workpieces correctly. For this purpose, the image recognition software must clearly recognize the position and direction of the workpieces with the help of AI.

                                                                                      Bitcoin (BTC) is the world's leading digital payment method based on a Blockchain and the pioneer among the crypto currencies. The Bitcoin currency is inflation-proof, since the inventor Satoshi Nakamoto limited the absolute amount to 21 million Bitcoins. In July 2019, there were about 17.85 million Bitcoins in circulation, so that most of them have already been mined. It is assumed that all 21 million Bitcoins will have been mined by 2130.

                                                                                      By the way: 
                                                                                      There are other digital currencies like Ether, XRP or Bitcoin Cashh

                                                                                      A block chain is a database that contains a constantly growing list of transaction records. The database is expanded chronologically, comparable to a chain ("block chain" = "Blockchain"), to which new elements are constantly added at the lower end. If one block is complete, the next one is created. Each block contains a checksum of the previous block. This results in a chain of blocks from the Genesis block to the current block. In a block chain, these blocks are not only distributed on a few computers, but on many computers worldwide. The resulting worldwide transparency is supposed to prevent manipulation possibilities and is one of the biggest advantages of a block chain. A disadvantage is the relatively low data throughput.

                                                                                      The best known block chain application is the digital crypto currency Bitcoin.

                                                                                      Bluetooth is an industrial standard developed in 1999 for data transmission between devices over short distances via radio technology (WPAN). The main purpose of Bluetooth is to replace cable connections between devices. There are different types and versions of Bluetooth devices, reaching different ranges from 1 to 100 meters. In practice, a distance of 1 to 10 meters is usually recommended for the connection to be established. With Bluetooth Version 5, which has been available since the end of 2016, the range and transmission speed have been significantly increased. With no obstacles between transmitter and receiver, connections of up to 200 meters and a maximum data rate of 2 Mbps in open space are possible.  Equipped with these features, Bluetooth 5 devices in Internet of Things  (IoT) will make many things possible.

                                                                                      The name "Bluetooth" is derived from the Danish King Harald Bluetooth (English Harald Bluetooth). The logo shows a monogram of his initials H and B in Germanic runes.

                                                                                      Bots are programs that simulate human behavior patterns to simulate a human presence on the Internet.
                                                                                      The goal is to interact with real people.
                                                                                      Depending on the program, the bots appear in different levels of complexity. In the simplest case, these bots react to certain keywords or so-called hashtags, to which they in turn react with ready-made information. By using artificial Intelligence and comprehensive data analysis, however, the bots are increasingly better able to simulate the real existence of a human being. In addition, daily events can also be integrated to further substantiate authenticity.

                                                                                      Usually the bots are intended for a specific purpose.
                                                                                            • Social Bots are active in social networks to share, link or comment on postings.
                                                                                            • Chat Bots are used where questions must be answered automatically.

                                                                                      A negative example of social bots would be political propaganda.
                                                                                      One example of chat bots are reservation portals. But also news portals, like the Tagesschau, have their own chat bot called Novi-Bot, with which you can chat about current topics.

                                                                                      With increasing artificial Intelligence it becomes more and more difficult to expose bots.
                                                                                      The following Turing test is the benchmark for the bot:
                                                                                      If a human questioner after intensive discussion (without visual contact) with a human and an artificial Intelligence (bot) can not say clearly, which of both is the machine, then the machine passed the Turing test.

                                                                                      Social Bots writes
                                                                                      Chat Bots speaks


                                                                                      Cloud computing (German: Rechnerwolke or data cloud) is an operator model in which IT resources, such as servers, are not operated on the company's own premises, but are made available dynamically, e.g. via the Internet. This type of provisioning enables the IT resources (hardware, software, infrastructure) to be called up flexibly and according to demand.
                                                                                      A distinction is made between the following characteristics in cloud computing:

                                                                                      Public Cloud
                                                                                      The Public Cloud is a public cloud whose services are openly accessible to everyone via the Internet.

                                                                                      Private Cloud
                                                                                      The private cloud is also known as the enterprise cloud.
                                                                                      Although it uses the advantages of cloud technology, it remains within a company through internal hosting and thus achieves a high level of security and data protection, but with increased personnel and maintenance costs. 

                                                                                      Hybrid Cloud
                                                                                      When private clouds are combined with public clouds, one speaks of a hybrid cloud. This enables separation and distribution of data protection-critical and non-critical business processes, but with even higher personnel and maintenance costs.

                                                                                      The opposite of the cloud is called On-Premise

                                                                                      Condition Monitoring stands for the continuous condition monitoring of assets such as machines and plants, etc.Based on sensor data collected and analyzed in real time, a reliable picture of the (wear) condition of components can be obtained and automatically reacted to if necessary.

                                                                                      Condition monitoring can also take place without visualization, i.e.  the software runs undetected in the background and only becomes noticeable by automatic countermeasures in case of detected faults. This monitoring of the machine condition is the mandatory prerequisite for a foresighted and demand-oriented maintenance and repair using Predictive Maintenance.


                                                                                      • Visualization shows states only pictorially, without reacting automatically to critical states.
                                                                                      • Condition monitoring reacts to critical conditions or to values outside a defined range.
                                                                                      • Predictive Maintenance can calculate in advance, based on the conditions, when maintenance should be performed.

                                                                                      The term Cyber-Physical Production System (CPPS) stands for the use of a Cyber-Physical Systems (CPS) in the manufacturing industry.

                                                                                      You can find further information at: Cyber-Physical Systems (CPS)

                                                                                      Cyber-Physical Systems (CPS), also called cyber-physical systems, are objects that move along production lines and control themselves. For this purpose, they are digitized and given their own data storage devices to carry information with them. In addition to data storage, it can be useful to carry "embedded software" with you to make your own decisions. CPS also refers to industrial applications that generate benefits by intelligently compressing data generated in various subsystems at a higher level into information that can in turn trigger actions. For this purpose, they require a sensor and an actuator.

                                                                                      Fraunhofer IIS defines CPS in a narrow sense as follows: "Cyber-Physical Systems are distributed, networked and real-time communicating embedded systems, which monitor the processes of the real physical world via sensors and control or regulate them via actuators. They are also often characterized by high adaptability and the ability to handle complex data structures. 

                                                                                      CPS needs:
                                                                                              1. Sensors to collect data.
                                                                                              2. embedded software to evaluate the data and make decisions.
                                                                                              3. actuators to implement the calculated decisions (e.g. electric motors).
                                                                                      An automatic awning control system includes:
                                                                                               • a sensor that measures the wind force.
                                                                                               • a software that decides when the awning must be retracted automatically.
                                                                                               • an actuator that retracts the awning using an electric motor.


                                                                                      There is currently (2019) no clear definition for data governance.
                                                                                      In a simplified form, it is a form of data management that sets rules for handling data through data policies. This set of rules can contain generally valid as well as company-specific specifications. The range of tasks includes, among other things, guidelines for:

                                                                                      • Provision of data 
                                                                                      • Design of access rights
                                                                                      • Networking strategies
                                                                                      • Data security
                                                                                      • Data quality
                                                                                      • Logging of data processing
                                                                                      • Monitoring of the defined specifications
                                                                                      • Monitoring of legal requirements and compliance demands
                                                                                      • Dealing with Legacy Systems
                                                                                      • …

                                                                                      Data Governance pursues the following goals, among others:
                                                                                      • Ensure system availability
                                                                                      • Identifying and avoiding risks
                                                                                      • Recognize and use potentials
                                                                                      • Reduce IT costs

                                                                                      In principle Data Governance describes the starting conditions for INDUSTRIE 4.0

                                                                                      The term data lake stands for a very large and unstructured data storage.It contains data in its original raw format. This has the advantage that the data does not have to be checked or formatted before storage. The Data Lake must be able to hold any data format. 
                                                                                      This avoids distributed data silos.

                                                                                      Only when the data is needed is the affected data prepared. For this, however, powerful and intelligent mechanisms are needed to process these huge amounts of information with reasonable response times.
                                                                                      This is a typical Big Data Application.
                                                                                      The benefit arises only when Data Mining is used to turn this raw data into Smart Data  .

                                                                                      Data Science is formed from the English words data "data" and science "science" and stands for the extraction of knowledge from data.
                                                                                      People who work in data science are called data scientists.

                                                                                      The filtering of specific information from a large amount of data is called "data mining" or pattern recognition. This involves searching mass data with data analysis and detection algorithms with the aim of identifying new patterns, cross-references and trends. If such patterns are found, then the data to Smart Data will provide the new insights. In order to avoid misinterpretations as far as possible, the detection algorithms must recognize outliers and manipulated data and remove them from the evaluation.


                                                                                      Data-Mining transferres Big Data to Smart Data

                                                                                      The data matrix code is the best known two-dimensional barcode. It was developed by the American company Acuity Corp. in the late 1980s. The aim of the development was to be able to store more data in as small a space as possible than with the barcode. The DataMatrix code is a simple chessboard-like pixel surface with white or black pixels and can contain any information. The actual capacity of a DataMatrix Code is determined by the size of the symbol and can contain up to 3116 digits or 2335 characters.

                                                                                      In order to read the coded information, an image processing system is required, e.g. a 2D scanner. All types of barcodes allow control, monitoring, tracking, automation, simplification and optimization in business processes.

                                                                                      Example: Marking of packages

                                                                                      Here you find a: List of all Barcodetypes

                                                                                      Data Enrichment or Data Enhancement is the enhancement of data sets with additional information. Usually, digital master data streams are enriched by the on-board intelligence of a cognitive assistance system, thereby generating fully automated process data. A prerequisite for this is complete and error-free master data!

                                                                                      In a high expansion stage (e.g.: at ValueFacturing) process data is not only enriched but completely regenerated.

                                                                                      Data security includes all technical measures that serve to protect data. The following sub-goals are pursued:

                                                                                      • Confidentiality 
                                                                                        Goal: Access only by authorized users 
                                                                                        Approach: Rights system

                                                                                      • Integrity
                                                                                        Goal: Protection against manipulation 
                                                                                        Approach: virus scanner, firewall, encryption or cryptographic procedures, Blockchain

                                                                                      • Availability 
                                                                                        Goal: Reliability 
                                                                                        Solution approach: Server architecture, Cloud

                                                                                      • Controllability
                                                                                        Goal: Testing by logging 
                                                                                        Solution: Storage systems

                                                                                      In contrast to data protection, data security is not limited to personal data.

                                                                                      Deep Learning is a subarea of Machine Learning.
                                                                                       Delimitation :

                                                                                      • Beim Machine Learning  In machine learning, humans intervene in the analysis of the data and can thus influence the actual learning process.

                                                                                      • In deep learning, the human being only ensures that the data is available for learning. This means that the human leaves the calculations completely to the machine and has no influence on the results of the learning process.

                                                                                      Face, object or speech recognition, if required also with the distinction of natural persons and Bots.

                                                                                      Machine Learning enables human interaction. Deep Learning is autonomous.

                                                                                      Digital Value

                                                                                      In the final analysis, the digital value will arrive for the user as follows: 

                                                                                      • In the backend Artificial Intelligence (AI) will have a variety of effects and integrate the enablers according to the situation.

                                                                                      • Apps on a wide variety of mobile devices will serve as a front-end to human beings or replace them.

                                                                                      This results in new products and new business models. See also the encyclopedia entries on E-Health and Smart-Home.

                                                                                      Digital shadow is the process data that machines generate during their operation. This is raw data, also known as digital footprint. On the one hand, this data is the input for Condition Monitoring , and on the other hand it forms the basis for more comprehensive knowledge that can be gained through Data Mining (pattern finding in the raw data).

                                                                                      The Digital Shadow should not be confused with the Digital Twin because it is a digital (virtual) image of the real object.

                                                                                      Digital Twin: digital image of the real machine Digital shadow: raw data generated by the machine

                                                                                      The digital twin is the virtual image of a product that accompanies its real counterpart for a lifetime, because many things can be predicted precisely on the basis of the digital doppelgänger. The potential behind it is great: Instead of expensive prototypes and lengthy chains of experiments, these images can be used to run through all kinds of scenarios in the complete product development process within a very short time, develop and reject solution strategies, sound out and implement possible improvements.

                                                                                      The digital twin must not be confused with the Digital shadow. verwechselt werden.

                                                                                      Digital twin: digital image of the real machine 
                                                                                      Digital shadow: Raw data generated by the machine

                                                                                      The paper documents are digitized and therefore no longer printed out but digitally displayed.

                                                                                      Flight ticket The process of "boarding the plane" has therefore not changed. Some passengers with analog paper tickets and some with digital cell phone tickets board the plane at the same time.

                                                                                      Digital transformation:
                                                                                      Here too, the paper documents are digitized for the first time. However, due to digital availability, the associated process is now also changing. These process changes can be harmless or can be so radical that the transformation becomes a disruption.

                                                                                      Example: Book 
                                                                                      This has completely changed the "Buy a book" process: When the e-book has been read to the end, you don't even have to get up from your deck chair, but can buy the next book directly via download. This is called disruptive!

                                                                                      Disruptive technologies completely replace established technologies and displace them from the market within a short time. In most cases, they are inferior in quality at the beginning, but gradually catch up with their predecessors and surpass them after some time.

                                                                                      In the beginning digital cameras could not convince qualitatively. Due to too low resolution, the image quality was initially poor and was a major disadvantage compared to classical photography. However, the image result could be immediately checked and processed or copied. The image quality quickly improved to such an extent that digital cameras have replaced analog cameras.

                                                                                        In contrast to disruptive technologies there are transformer technologies.


                                                                                      "E-Health" (also electronic health) stands for electronic and digital technologies in the healthcare sector for medical care and monitoring of people. Fitness bracelets or fitness trackers, so-called Wearables, measure not only the number of steps, but also the pulse and blood pressure and usually forward the recorded information to a smartphone app. In the simplest case, interesting diagrams and graphics are generated from it. In acute cases, the rescue service can even be activated automatically. The monitoring of implanted pacemakers can thus save lives.

                                                                                      More and more doctors use e-health to support their patients: 

                                                                                      • in prevention

                                                                                      • in diagnostics

                                                                                      • for treatment

                                                                                      • for aftercare

                                                                                      E-health thus refers to the use of digital aids to support doctors and patients.

                                                                                      Now, during the corona pandemic, an e-health app on the wrist for early detection of the virus would be an ingenious solution. 

                                                                                      Unfortunately this app is not yet available!

                                                                                      "E-Health" is a nice example of the  DIGITAL VALUE including its definition..

                                                                                      E-learning (electronic learning) refers to all forms of learning in which electronic or digital media are used.  These are often web- and computer-based forms of learning.

                                                                                      If e-learning is carried out on one's own initiative, e.g. in distance learning, it is called virtual teaching.

                                                                                      When face-to-face courses and virtual teaching are combined, this is called blended learning. Blended Learning is a mixture of classical teaching and distance learning. It is a form of learning that combines the advantages of classroom teaching and virtual teaching. One part of the learning content is taught face-to-face by the teacher in the classroom and the other part is learned at home on the PC using learning programs. One advantage of virtual teaching is that learning is not bound to time and place.

                                                                                      In analogy to the term "Blended Learning", "Blended Concepts" describes the conceptual coordination of the individual modules with each other.

                                                                                      The art is to develop an instructive and interesting concept for the respective topic so that the students have fun and achieve learning success through gamification.

                                                                                      The term gamification (from English game for "game") stands for learning through play and is a special form of e-learning.

                                                                                      Good gamification examples are the Quizzer® and the Web Based Training, which offer gamification for different topics.


                                                                                      The term Edge Computing is still relatively young and stands for decentralized data processing on the spot. Figuratively speaking, edge computing takes place at the edge between the data source (e.g.: sensors) and the data center or  Cloud . Edge computing enables efficient data processing where large amounts of data can be processed close to the source, requiring less Internet bandwidth.

                                                                                      Its goal is to minimize waiting times (latency) and prevent network overload.

                                                                                      The term embedded system stands for integrated software on a reduced hardware which is not called a computer. The embedded software is usually stored in a flash memory and cannot be changed by the user or only with special means. We also encounter an embedded system in the form of so-called firmware. Smart objects are equipped with an embedded system to be able to get in contact with their environment. Embedded systems are used e.g. in household appliances or in pacemakers.

                                                                                      An entity describes the identity of a real or virtual "thing". For this purpose, each "thing" receives a Unique Identification Number (UIN). This UIN is a unique identification number with which all things (entities) become uniquely identifiable and thus unique.  When assigning the UIN numbers, the repeated assignment of the same number must be reliably excluded. In the sense of the Internet of things (IoT) the entity has to be provided for all things that want to be connected!

                                                                                      An Asset becomes unique only through a Unique Identification Number in its management shell and thus becomes an entity.


                                                                                      A greenfield is a completely newly built company "on a greenfield site", equipped with the most modern machines and software systems. It is virtually a company without any inherited burdens, which make digitalization considerably more difficult. However, the reality is almost always the opposite, namely a company with a historically grown machine park, with different software systems and versions.

                                                                                      Example:  In a discrete manufacturing the following machine controls can be found: 
                                                                                      Siemens, Fanuc, Haas, Heller, Heidenhain, Bosch, Dialog, Maho, Mazak, Mitsubishi, Okuma, Phillips, Traub

                                                                                      with different communication protocols such as: 
                                                                                      SinCom, MCIS_RPC, MCIS_TDI, Create MyInterface, TNC Remo, Focas2, Ethernet Library, MTConnect

                                                                                      The hoped-for solution of the future: OPC UA is often only partially available. One calls this condition Brownfield, and/or also gladly a zoo. As contaminated sites, every brownfield contains incomplete and incorrect master data and numerous paper documents. The networking of a brownfield machine park is like a battle of houses.


                                                                                      The abbreviation HMI stands for Human Machine Interface and describes a user interface through which a human being can interact with a machine. In the simplest case this is an ON/OFF switch.

                                                                                      • The first HMIs were valves on steam engines

                                                                                      • With the advent of electronics, switches, buttons, signal lamps and pointer-based display panels were used

                                                                                      • The classic for a HMI for decades is the keyboard and the screen

                                                                                      • With the advent of smartphones and tablets, however, wiping technology on the touch screen has increasingly established itself as HMI

                                                                                      It is to be expected that in the future, Wearables such as  Augmented Reality glasses will increasingly be used as HMI, as will communication with the machine via gestures, facial expressions or speech


                                                                                      A modern HMI in the sense of INDUSTRY 4.0 no longer has analog elements, but is completely virtualized. Therefore, the term HMI is classified under the umbrella term virtualization. 

                                                                                      Here to Video

                                                                                      A holodeck is a staging environment in which the participants can completely immerse themselves in a world of illusion by means of various Virtual-Reality plications including integrated real elements, e.g. to train certain applications. Vacant halls are suitable as a staging environment. (e.g. gymnasiums or disbanded supermarkets or DIY stores). As real elements (here: red door) the elements necessary for the case of application are built up. As a Virtual-Reality scene, an environment is virtually represented according to the application. The real elements (here: red door or e.g. stairs) are integrated into the Virtual-Reality scene.

                                                                                      The Virtual-Reality scene can be supplemented by technical tools with the following real effects:

                                                                                      • Wind

                                                                                      • Warmth

                                                                                      • Heat

                                                                                      • Smells

                                                                                      • Noise

                                                                                      In this way, absolutely realistic operational environments are created, which could not be practiced in this clarity without the holodeck.

                                                                                      Origin of the term: 
                                                                                      The term holodeck was taken from the film series "Star Trek". On the "Starship Enterprise" the crew members often retreated to a holodeck in their spare time to travel to virtual worlds.


                                                                                      An Industry 4.0 component consists of an asset with the associated management shell. The basic idea of the I4.0 component is to provide each industry 4.0 capable asset with a management shell that is suitable for adequately describing the asset in terms of possible use cases.

                                                                                      Detached from Industry 4.0, the term asset stands for fixed assets. In the sense of Industry 4.0 assets are all things that have a networking capability. Asset is therefore all things (IoT) that can be connected to the Internet or Intranet*. E.g.: all kinds of machines, plants, storage systems or their individual components.   

                                                                                      The management shell is the digital representation of a physical asset. It contains the relevant information about the asset, including its functions to be used and how to access them via I4.0 communication. It is divided into a header and a body. The body can contain several submodels. The content of all submodels of an I4.0 component is called a manifest . The submodels consist of a strictly uniform format range and a variable, asset-specific format range.

                                                                                      An asset becomes unique only through a Unique Identification Number in its management shell and thus becomes an entity.

                                                                                      iBeacon is a proprietary standard for indoor navigation based on Bluetooth, introduced by Apple lnc. In addition in the area small transmitters (iBeacons) are placed as signal transmitters, which send signals in fixed time intervals. If a receiver (e.g. a smartphone app) comes into the range of a transmitter, the transmitter can be located and actions can be triggered.

                                                                                      In a museum, an iBeacon is attached to each sight. If the visitor comes near the iBeacon with his smartphone, the app starts explaining the sight. In this case, the visitor's own smartphone with its own headphones replaces the well-known audio guides that otherwise always have to be borrowed at the museum ticket office.

                                                                                      Used in department stores, iBeacons can offer customers a new shopping experience. This way they can be made aware of current offers and precisely guided to their styles and sizes. This can be the floor or specific departments in the shopping center.

                                                                                      Industry 4.0, also referred to as the "4th industrial revolution" in reference to the three previous industrial revolutions, has become a synonym for the digital factory of the future.

                                                                                      Originally, the term Industry 4.0 originates from a future-oriented project of the German government's High-Tech Strategy from 2011, which aims to ensure the international competitiveness of German industry in the long term. This initiative aims to ensure that Germany continues to play a leading economic role internationally. Although the German government's ambitious Industry 4.0 project for the future has given its name to the development process of German production and initiated a public discussion, the beginnings of Industry 4.0 go back further in time.

                                                                                      In order to grasp the core of this industrial (r)evolution and its characteristic fundamental difference from the past, WEB-BASED-TRAINING provides an informative look into its history. Today's initial situation, in which modern companies find themselves, has become much more complex. This requires a change in production, a continuous and comprehensive networking, which could be achieved by using the Internet in the course of Industry 4.0. One of the goals of Industry 4.0 is to increase the flexibility of production in such a way that, if necessary, batch size one can be produced economically and the customer receives an individually configured product.

                                                                                      Originally, the term Industry 4.0 stems from a future project of the German government's high-tech strategy, which was announced in 2011. Its aim is to ensure the international competitiveness of German industry in the long term. This forward-looking initiative aims to ensure that Germany continues to play a leading economic role internationally. But we can only achieve this as "Team Germany"!

                                                                                      A key role plays here: Find and be found

                                                                                      One of the aims of an innovation platform is therefore to bring together innovative companies, thereby measurably increasing the innovation performance of its members and promoting a sustainable innovation culture.

                                                                                      Platform for Innovation in Germany

                                                                                      Another goal of an innovation platform is to lay the groundwork, i.e. to set the broad direction, while curbing uncontrolled growth and keeping an eye on standardization instead.

                                                                                      The term "interdisciplinarity" refers to the connection and combination of independent (scientific) disciplines and their methods, approaches or lines of thought. Different solution strategies are combined here for the best possible result, which can lead to new ways of thinking and solutions for problems. Especially in times of a beginning Fourth Industrial Revolution, many synergies between individual disciplines can be used.

                                                                                      Beyond the scientific perspective, a concrete example can be found in the job description of the mechatronics engineer. A few years ago, this has developed from the respective apprenticeship occupations of locksmith and electrician, supplemented by control engineering and regulation technology and information technology.

                                                                                      A new job description is currently being created by merging the mechatronic engineer with the computer scientist.

                                                                                      The Internet of Services is a part of the Internet that offers services and functionalities as a web-based service. Providers make them available on the Internet and offer their use on request. The individual software modules or services can be integrated with each other via Internet service technologies. This enables companies to orchestrate the individual software components into complex yet flexible solutions. A simple example is the pizza service, which is ordered via cell phone app.

                                                                                      The following picture of the future describes the interaction of the Internet of Things and services:

                                                                                      • Internet of things
                                                                                        In future, all vehicles will be automatically connected to the Internet and report all operating data to a Clouddatabase. The operating data includes, for example, the operating status of the windshield wiper motor (off, on, interval, fast).

                                                                                      • Internet of Services 
                                                                                        Software service providers who have no idea about meteorology make the best regional weather report available. The result will almost certainly be more accurate, cheaper and better than previous local weather forecasts. Of course, there will also be jokers who will organize a flash mob so that several hundred car drivers will simultaneously switch on their windshield wipers in bright sunshine. Pattern recognition software
                                                                                        (Data-Mining) must therefore also be able to verify the accuracy of the raw data.

                                                                                      • New business models
                                                                                        This results in new business models, which in turn act as a catalyst for the Internet of things and services.

                                                                                      IoT stands for Internet of Things. When we humans sit in front of the PC and surf the Internet, this can be called the counterpart (the Internet of Things). However, when things (such as a machine or a cooking spoon) go on the Internet, you don't need a keyboard or a screen to do so. An own IP address, Internet access and a program are enough.

                                                                                      This extension of the existing Internet to the Internet of Things is the technical idea of integrating objects of all kinds into a universal digital network. A possible future scenario in the Internet of Things is that every installed wear part has its own IP and is connected to the Internet. Once in use, each part thus remains connected to the maintenance units via the Internet for the rest of its life and automatically reports any problems. Modern cars, for example, automatically call the rescue control center in case of an accident and transmit the current position.

                                                                                      Interoperability stands for the ability of different systems to work together as seamlessly as possible.

                                                                                      In the simple case, these are standardized systems that are compatible with each other; in the more difficult case, they are heterogeneous systems that do not have a common communication protocol.

                                                                                      Among others OPC UA is hoping for a big step towards interoperability with INDUSTRY 4.0. Also by the management shell, almost als digital twin of the Assets, it also promises a big step towards interoperability.

                                                                                      By the way: interoperability is also a great advantage when people work together, especially in mixed teams.

                                                                                      O-Link is a worldwide standardized IO technology to communicate with sensors and actuators. IO stands for Input/Output = "Input/Output". 
                                                                                      It is a powerful point-to-point communication. This technology was developed by the IO-Link consortium.

                                                                                      IPv6 stands for the Internet Protocol Version 6. IPv6 is expected to replace the currently still used version 4 of the Internet Protocol IPv4 in the next few years, because the Internet is currently running out of addresses. With only 4.3 billion possible IP addresses, the currently used Internet protocol IPv4 is no longer sufficient for the growing number of Internet users worldwide. The new Internet protocol IPv6, which allows up to 340 sextillion IP addresses, is the solution. This is an incredibly large number with 39 digits:

                                                                                      340 000 000 000 000 000 000 000 000 000 000 000 000

                                                                                      This makes it possible to assign a unique IP address to every square millimeter on the earth's surface. The Internet protocol IPv6 is one of the prerequisites for the worldwide and cross-system networking of people, plants and products with independent and decentralized organization and control of production units.

                                                                                      Infrastructure as a Service (IaaS) is a service that, in contrast to the classic purchase of computer infrastructure, offers the rental of hardware as a service. IaaS providers provide their hardware equipment, such as server and storage systems, and also take on additional tasks such as system maintenance, data backup and emergency management. IaaS customers can independently access infrastructure services and pay for them according to the period of use.


                                                                                      The adjective cognitive is derived from the Latin cognoscere (to know, to recognize) and means problem-solving ability through differentiated perception of the environment in connection with existing knowledge. In this sense, cognitive assistance systems are able to perceive the environment through sensor technology and, in combination with their on-board intelligence, enable data enrichment.

                                                                                      The term artificial intelligence (AI) is not clearly defined because even the definition of "human intelligence" is fuzzy.

                                                                                      One possible definition is:
                                                                                      When the solution of a task requires intelligence from a human being, can also be solved by a computer, then we speak of artificial intelligence.
                                                                                      In the early days of AI this may have been a sufficient definition,With today's possibilities, however, AI is able to far outperform humans in certain areas.

                                                                                      The Google image search via photo upload uses AI for image recognition and thus Google is able to find the requested image in billions of images within seconds.

                                                                                      In principle, Artificial Intelligence is a branch of computer science that deals with the intelligent behaviour of computers and machine learning. The term Artificial Intelligence has been around since 1956 and was first used in a workshop entitled "Dartmouth Summer Research Project". Artificial intelligence has always been a collective term for visionary ideas that do not yet work. Because when a certain part of AI starts to work, it immediately gets its own name (sometimes even before) e.g: 

                                                                                      KI can concern the following 2 different solution spaces:

                                                                                          1. closed solution space with limited solution possibilities. Example: Chess computer
                                                                                          2. open solution space with infinite solution possibilities. Example: weather forecast.


                                                                                      Lean Management stands for the entirety of principles, methods and procedures for the efficient design of the complete value chain of industrial goods. By introducing Lean methods, processes are harmonised to create a holistic production system without waste. The origin of Lean Management lies in the Japanese automotive industry.

                                                                                      The aim is to increase productivity while avoiding waste. There are more than 80 different lean methods to achieve this. One of them is: Order and cleanliness at the workplace.

                                                                                      LEAN management is the basic prerequisite for the SMART FACTORY, because LEAN + INDUSTRY 4.0 = SMART FACTORY

                                                                                      Legacy is the English word for bequest, legacy, inheritance.

                                                                                      Legacy systems in the IT environment are established, historically grown software solutions.

                                                                                      Although the developers are usually already retired, the operating systems used have not been supported for a long time, and there is no or insufficient documentation, many of these systems still convince with a range of functions that can only be mapped with difficulty or at great expense in modern environments. This is because the mentality during and after the CIM wave in the 90 years has led to the fact that almost every user request has been solved by special programming. At the turn of the millennium, for example, it was considered ingenious to map business processes in Excel with the most sophisticated macros. These originally highly valued solutions now make their replacement more difficult and, from the point of view of availability, even more urgent. In order to remain executable, legacy systems are therefore often encapsulated to the outside and the old operating system and runtime environment is emulated in a virtual environment.


                                                                                      CHARON-VAX is a Vax emulator for Windows and emulates the operating system VMS from Digital Equipment Corporation. In order for the digital transformation of business processes to succeed, legacy systems must be replaced promptly, e.g. by MOM Systeme ersetzt werden. Every company has to create its Data Governance strategy.


                                                                                      Machine Learning is a branch of artificial intelligence and uses neural networks and large amounts of data. The way it works is inspired in many areas by learning in the human brain.

                                                                                      The recognition of patternsn (=Data-Mining) in existing data sets  (=Big Data) enables new knowledge to be gained  (=Smart Data ) which would not be possible with conventional methods. The knowledge gained from the data can be generalised and used for new problem solutions or for the analysis of previously unknown data. In order for the software to learn and find solutions independently, the systems must first be supplied with the data and algorithms relevant for learning. Furthermore, rules for the analysis of the data stock and pattern recognition have to be established.  For machine learning, distributed computer structures and in particular artificial neural networks, which function on the model of the human brain, are used.

                                                                                      Different types of machine learning are being developed:

                                                                                      • Supervised Learning, currently: supervised learning: (existing expert knowledge is used to teach the system)

                                                                                      • Active learning: (enables the machine to request the desired results for certain input data)

                                                                                      • Batch learning: (happens in offline mode, i.e. during batch learning the Data-Lake is not changed anymore)

                                                                                      • Sequential learning: (here the data sets from the Data-Lake are processed sequentially)

                                                                                      An example of the application of machine learning is stock market analyses, which sometimes calculate interesting investment strategies. These automated stock market analyses are now carried out by a so-called Robo-Advisor, and the results are becoming increasingly professional.  The term Robo-Advisor is composed of the English words Robot and Advisor and stands for the automated form of investment.


                                                                                      • The increase in machine learning is Deep Learning.

                                                                                      • The encyclopaedia entry for Smart Data  takes up the topic of "machine learning" from a different direction.

                                                                                      Machine-to-Machine (M2M) stands for the automated exchange of information between terminal devices. Various technologies are used for M2M communication, such as mobile radio, WLAN, Bluetooth or NFC. Classic M2M communication is a point-to-point application without the Internet. In the sense of INDUSTRY 4.0 and especially in the sense of Internet of things (IoT) end devices are all things that can be networked with the Internet. Therefore M2M and IoT are often mentioned in the same breath. Together they pursue the goal of automated data exchange between terminal devices. However, while IoT requires networking via the Internet and an IP address, classic M2M also works without the Internet.

                                                                                      Example for M2M classic without Internet: 
                                                                                      The intelligent car key with proximity sensor and RFID-Transponder unlocks the car keyless.

                                                                                      Example of M2M with IoT:
                                                                                      iWatch makes cashless payments at the supermarket checkout using Apple Pay.

                                                                                      M2M solutions will increasingly integrate the following enablers from INDUSTRIE 4.0

                                                                                      This creates additional new business models.

                                                                                      A manifesto is part of the administrative shell of a I4.0 Component. It contains the information of all partial models.

                                                                                      You can find further information at: Management shell

                                                                                      Fertigung Analytik umfasst

                                                                                      of digital production data.

                                                                                      Manufacturing Analytics is thus quasi the umbrella term for Condition Monitoring incl. Predictive Maintenance.

                                                                                      Manufacturing as a Service (MaaS) refers to the shared use of networked production facilities. MaaS requires real-time access in order to query the status of the machines, so they must be connected to a high-performance and stable Internet. One vision of MaaS, for example, is that many machining service providers in Germany or Europe will interconnect to form a huge machine park. Only what is currently needed is produced on demand. This type of production is also known as Manufacturing on Demand (MoD) or on-demand production. The customer uploads his CAD data to a manufacturing platform and receives a daily updated ranking of all suitable manufacturers. After placing the order, IoT enables the customer to track the status of his order in real time. MaaS turns the world into a village, i.e. even the most remote manufacturing locations participate in the world market.

                                                                                      The increasing possibilities of the Additiven Fertigung (3D printing) are the tailwind for the MaaS concept.

                                                                                      It is the interface between a planning system (ERP) and the shop floor (= machine hall). The E stands for Execution and defines that an MES has to take care of the execution of the planned order in the machine hall. The MES implements both horizontal and vertical networking.

                                                                                      The VDI technical committee MES has defined the core tasks of an MES in the guideline VDI 5600. However, MES systems must adapt to the new challenges posed by Industry 4.0 and will therefore continue to develop into Manufacturing-Operations Management (MOM) Systems. MOM will be more than MES. 

                                                                                      see: Manufacturing-as-a-Service (MaaS)

                                                                                      Manufacturing Operations Management is the extension of a MES in the direction of IoT.

                                                                                      One of the aims here is to move from "execution" (= execution and control) to "production optimisation through regulation". MOM focuses on the digitalisation of processes and information to increase efficiency and transparency.

                                                                                      The author of the encyclopaedia participates in the MES/MOM working group of the ZVEI.  
                                                                                      This implementation recommendation was published in 2017. 
                                                                                      The next implementation recommendation will be published at the Hannover Fair in 2020. 
                                                                                      An overview is given in this lecture of the author.  

                                                                                      MES -Systems were created at the time of INDUSTRY 3.0 and now have a lot of legacy issues. A general problem to be found in manufacturing with NC machines was, or still is, that the different aggregates involved in a manufacturing process (NC machines, presetting devices, storage systems etc.) use proprietary data formats and a cross-aggregate provision of process data is regularly not possible. The networking of a historically grown machine park is like a house-to-house battle that must be won for each machine.

                                                                                      The following basics must be met for MOM to break these limits:

                                                                                      All manufacturers of networkable products (assets) agree:

                                                                                      • a common language such as OPC UA. Under this premise, uniform OPC UA parameter sets are promptly created that cover the respective subject-specific conditions.

                                                                                      • the need for a standardised  management shell per Asset uand deliver them with it.

                                                                                      This results in I4.0-Components and based on this MOM can make „Plug and Produce“ work. A simple example is the printer installation. On Windows XP, or earlier, a printer installation was always an exciting task. In the days of Windows 10, a newly plugged in printer is completely self-configuring. ( = "Plug and Play").

                                                                                      MQTT is occasionally called the "little" brother of OPC UA , because MQTT was originally developed for small sensors with low computing power. OPC UA and MQTT cannot be directly compared, however, because they solve different tasks. The classic application for MQTT are small sensors that provide only a few and mostly fixed data, but with real-time requirements. OPC UA, on the other hand, is used when there are many and extensive data and freely configurable data rooms. Compared to OPC UA at MQTT, there is no security deficit, because it also allows the unique identification of the participants and also encrypts the transmitted data.

                                                                                      META stands for taking a bird's eye view


                                                                                      1. The META level is taken by an arbitrator to understand the different views of conflicting parties.

                                                                                      2.  META data are superordinate and structured information to raw data.

                                                                                      3. META systems in the sense of Industry 4.0 are superordinate assistance systems that are able to communicate with different digital ecosystems.  See e.g.: ValueFacturing

                                                                                      The Mixed Reality (MR) user sees a mixture of real and virtual images that have a spatial relationship to each other. In the Mixed Reality environment a digital element behaves naturally. If, for example, a virtual cup is placed on a real table and the table is moved, the cup follows the table movement.

                                                                                      Demarcation and further information can be found at the term: Augmented Reality

                                                                                      Mobile computing, or mobile computing, is one of the prerequisites for Industry 4.0, as is the new Internet protocol IPv6, which covers human computing on a portable device and includes mobile communication, hardware and software. Mobile computers can be laptops, tablet PCs, smartphones, or data glasses. The location and time-independent access to operational data and applications, which should be as simple and intuitive as possible, has become the standard for all companies. This development is still limited by the comparatively low transmission rates of mobile internet, common security standards, or the energy consumption of the devices, which goes along with their battery life.

                                                                                      Next generation mobile computing will make data glasses and Wearables real.

                                                                                      MTConnect is an open standard for factory communication and can be seen as a simple alternative to  OPC UA . MTConnect is pushed by American companies and is promoted by the MTConnect Institute.

                                                                                      MTConnect standardises device data. The protocol works exclusively unidirectional (Read Only) and is designed for easy integration. This means that with MTConnect, a MES or MOMsystem can only read data from one machine, but cannot supply the machine with data and therefore cannot control it. This makes MTConnect unsuitable for Industry 4.0. MTConnect also lacks the increasingly important security mechanisms to secure and encrypt the data flow. However, there are already bridges or gateways to transform MTConnect to  OPC UA .


                                                                                      Near Field Communication (NFC) is an international transmission standard based on RFID technology for the contactless exchange of data via radio technology over short distances:

                                                                                      • The recommended distance between transmitter and receiver is 10 cm.

                                                                                      • The maximum distance between transmitter and receiver is 20 cm.

                                                                                      For example, smartphones and their NFC functionality can be used by various car manufacturers to unlock the car doors and make personal settings on the seat. In more and more shops, for example, it is possible to pay directly at the cash desk using a smartphone. NFC is the technology that is currently gaining acceptance for this. At NFC cash registers, you only need to hold your card up to the reader to pay.

                                                                                      Neural networks are known from brain research. The nervous system of humans and animals consists of nerve cells, also called neurons. These neurons are linked together by synapses and form a neural network. This blueprint of our brain enables human thinking and computing power.

                                                                                      In order to realise Artificial Intelligence (AI) , work is being done to simulate this biological neural network by means of an artificial neural network in the computer. For this purpose, the neurons (also called nodes) of an artificial neural network are arranged and linked in layers. Different variants can be used for this. In computer hardware, neural networks are simulated by multiprocessor systems with a very large number of very simple processors. Each processor models a neuron. Not a special program is written for each application, but the neural network has to learn the correct way of working itself (in analogy to humans). The results of this approach are not exactly predictable, so that solutions can arise which are characterised as "inexplicable" or "intelligent".

                                                                                      Neural networks are used, for example, for "Machine Learning" und „Deep Learning".

                                                                                      Neuronale Netze versuchen das menschliche Gehirn nachzubauen.


                                                                                      see: Manufacturing-as-a-Service (MaaS)

                                                                                      On-Premise is the opposite of Cloud and describes an operator model in which the servers are operated on the company's own premises, on site or locally.

                                                                                      It is only since local use has increasingly been offered in the  Cloud  that the term has emerged as an antipole.

                                                                                      The abbreviation OPC UA stands for „ Open Platform Communications Unified Architecture“.

                                                                                      The manufacturer-independent exchange of data is a decisive basis for the successful introduction of Industry 4.0. OPC UA contains a collection of specifications that standardises communication in the industrial automation environment. For this purpose it is structured as a platform-independent, service-oriented architecture (SOA). OPC UA enables machine data, such as control variables, measured values, parameters, etc. to be described in a machine-readable form and thus be transported in the sense of IoT  . OPC UA is an important milestone on the way to standardisation of factory processes.

                                                                                      OPC UA is promoted by the OPC Foundation and is primarily used in Europe. A novel and promising German approach to machine networking is umati. In other parts of the world,   MTConnect  among others, plays an important role in press communication.

                                                                                      The term orchestration in the sense of INDUSTRY 4.0 was taken over from the field of orchestral music and means combining, assembling and conducting different assets and web services to form a value stream. This is implemented by means of service-oriented architectureSOA) .

                                                                                      Each individual orchestra musician with his or her special instrument is comparable to an asset in a production hall. From the perspective of the conductor, who has to keep an eye on all the individual instruments at the same time and bring them into action at the right moment, an orchestration is created. A conductor in the sense of Industry 4.0 is e.g. a production controller who orchestrates the assets in a production hall with a cognitive assistance system. Similarly, the multi-machine operation of complex turning-milling centres including the control of all required production resources (tools, devices, etc.) by a single employee could be called orchestration. This is only made possible by a cognitive assistance system.


                                                                                      It is assumed that every technology always reaches its performance limits in terms of its potential for further development and that a technological leap will therefore be necessary after some time. However, a technological leap (e.g. a switch from analogue to digital working methods) always leads to a deterioration at the beginning. This is because the new working method must first be installed, trained and educated. This costs time and resources that are lacking elsewhere.

                                                                                      Ideally, the introduction phase on the new S-curve should be passed through quickly, so that the positive effects occur promptly and the system reaches the mature phase. 

                                                                                      Ideally, this blue curve coincides with the other two curves, which represent the course of organisational and cultural development. However, practice in INDUSTRY 4.0 projects almost always shows the parallel shift shown here. The occurrence of the effect is thus delayed by the time period (delta t). The better the digital competence of the employees, the department, the management and the company as a whole, the smaller is this parallel shift. In difficult cases this can last well over 2 years. Here, consulting an external expert for change management can help to accelerate the process.

                                                                                      The following presentation by the author explains these facts: Competence 4.0 – From Homo sapiens to Homo digitalis

                                                                                      Platform as a Service (PaaS) is a service that provides a programming platform for web application developers in the  Cloud .

                                                                                      Not to be confused with: Software as a Service (SaaS). SaaS refers to a service that provides an immediately usable software solution for end users as web applications in the  Cloud .

                                                                                      This means that the user does not buy and install the required programming language, but only uses the software via the Internet when needed. The service recipient pays a usage fee for use and operation. Compared to a traditional licence model, the PaaS or SaaS model saves the service recipient the purchase and operating costs, IT administration, maintenance work and updates.

                                                                                      Differentiating PaaS from SaaS offerings: 
                                                                                      PaaS-Applications are development environments, they contain programming languages and other helpful programming tools and are intended for software developers to develop e.g. SaaS applications. Example: Google App Engine

                                                                                      SaaS-Applications are functional software solutions for specific tasks and have a graphical user interface. They are usually made explicitly for end users. Example: Microsoft Office 365

                                                                                      „Plug & Produce“ steht für: einstecken („Plug“) und produzieren („Produce“)

                                                                                      The principle of "Plug & Play" is now well known. The printer installation can serve as a simple example. Under Windows XP, or earlier, a printer installation was always an exciting task. In the days of Windows 10, a newly plugged in printer now configures itself completely automatically. Just plug it in ("Plug") and start ("Play").

                                                                                      With "Plug & Produce", this principle is to be transferred to the factory halls, because this would make it just as easy to commission CNC machines and production plants, because they would configure themselves just as easily, so to speak. The prerequisites required for this are described under the term Smart Factory.

                                                                                      However, the reality of connecting new production facilities is reminiscent of the early days of PC work. The commissioning of a new CNC machine is like a house-to-house battle.

                                                                                      Predictive analytics is when you scratch yourself before it itches.

                                                                                      Attention Buzzword Bingo:

                                                                                      "By collecting huge amounts of data; in other words Big Data, Data Lake is created. The Data Scientist uses  AI in the form of Data Mining, Process Mining, Machine Learning and Deep Learning and creates Smart Data ."

                                                                                      Or said "EASILY different":

                                                                                      By collecting a lot of facts and thinking about them, new insights are created. Predictive analytics collects raw data and calculates future events.

                                                                                      A more detailed explanation of predictive analytics can be found in the lexicon under the term: Smart Data


                                                                                      A special form of predictive analytics is Predictive Maintenance and stands for predictive maintenance of machines. Another form of predictive analytics is the 18 o'clock forecast and extrapolation on election evening.

                                                                                      Predictive maintenance stands for predictive maintenance (of machines, etc.) Condition Monitoring is the prerequisite for predictive maintenance. 

                                                                                      Predictive maintenance can replace the previously common reactive maintenance (in case of failure) and preventive maintenance (e.g. every 25,000 km). Predictive maintenance uses the data recorded via  Condition Monitoringto predict the probable development of the future machine condition and to support the planning of maintenance and repair measures. Predictive Maintenance takes a predictive approach and predicts failures before they lead to downtime or quality losses. In the ideal case, proactively initiated maintenance measures can prevent the actual occurrence of the malfunction. The larger the data base (Big Data)and the more intelligent and sophisticated the analysis algorithms (Data-Mining) are, the more reliable the findings to be obtained.

                                                                                      Offshore plants, such as wind farms, are networked online with service centres and report automatically in case of unscheduled maintenance.

                                                                                      Condition monitoring and predictive maintenance pursue two goals:

                                                                                      1. Machine availability through prevention of downtimes

                                                                                      2. Machine efficiency through maximum utilisation of wear parts

                                                                                      Predictive maintenance is when you scratch yourself before it itches ;-) 
                                                                                      Predictive Maintenance makes Big Data to Smart Data

                                                                                      Process mining is a procedure for the systematic analysis and evaluation of business processes. 

                                                                                      Process mining is used to merge digital process tracks in real time in order to detect deviations and bottlenecks, for example. This makes it possible to make process knowledge contained in data and otherwise hidden, tangible in order to start new developments based on it or at least to find causes for poor performance. The starting point for process mining is the Data Lake,  in which a sufficient amount of process data is stored. The quality of this data and the  AI used determine the quality of the results of process mining.

                                                                                      Important fields of application are:

                                                                                      • Process harmonisation

                                                                                      • Process optimization

                                                                                      • Process stabilisation

                                                                                      • Process transparency

                                                                                      • Process cost reduction

                                                                                      Productivity 4.0 is the Taiwanese answer to the German term "Industrie 4.0".

                                                                                      Faced with the challenges of labour shortages and the ageing of Taiwan's workforce, the Ministry of Economy has launched the "Productivity 4.0" project to stimulate economic growth and improve industry.

                                                                                      By the way:

                                                                                      The Chinese answer to the German term "Industry 4.0" is Made in China 2025

                                                                                      Procrastination is the scientific term for "extreme postponement" of tasks. Colloquially, this behaviour is also known as "dawdling" or "procrastination". Postponement of activities is an everyday phenomenon and is familiar to most people.

                                                                                      In the case of digitisation projects, procrastination leads to urgently needed investments being postponed and thus losing touch with the competition.

                                                                                      Psychology professor Tim Pychyl writes in his book: "Prokrastination is like a credit card: it's really fun until the bill comes.


                                                                                      The QR code is a two-dimensional barcode. The abbreviation QR stands for "Quick Response Code" and was developed by the Japanese company Denso Wave in 1994. The QR code is a square graphic with three large black identification dots in the corners. The QR Code can contain up to 7098 digits or 4296 characters. The QR code has sophisticated features for error correction and can therefore still be read even if it is partially soiled or destroyed. The QR code is a further development of the data matrix code. Usually, a QR code is decoded with an app on a mobile phone. Modern mobile phones are able to read the QR code with the camera.

                                                                                      All types of barcodes allow control, monitoring, tracking, automation, simplification and optimisation in business processes.

                                                                                      Here you find a: List of all Barcodetypes


                                                                                      RAMI 4.0 is the abbreviation for: ReferenceArchitectureModel Industry 4.0 The model represents all essential aspects of Industry 4.0 in three axes:

                                                                                      1. The level hierarchy levels can be understood in the broadest sense as the well-known IT pyramid (ERP-MES shop floor). The functionalities have been extended to include the work piece, "Product", and access to the Internet of things and Services, "Connected World", to reflect the Industry 4.0 environment.

                                                                                      2. The Life Cycle & Value Stream level describes all steps over the entire product life cycle (from design to scrapping).

                                                                                      3. The layer Layers describes in six layers the digital image of an IoT-product, for example a machine.

                                                                                      The model combines the different user perspectives and creates a common understanding of Industry 4.0 technologies.

                                                                                      The maturity model is a strategy tool that can help to orientate oneself on the path of digitisation. It documents the current state and helps to develop a target state. Different levels of agreement between defined criteria and a degree of fulfilment of the criteria result in different degrees of maturity. Focusing on the essentials shows the direction, but requires further action afterwards.

                                                                                      There are different maturity models. Here you will find a selection. (Quelle: ifaa)

                                                                                      For example, the author uses the VDMA construction kit in his I4.0 maturity workshop. This workshop of the author is helpful for a first orientation and is also suitable to get a new orientation or a second opinion during the ongoing implementation. This workshop can also be used as a team event to inspire and motivate employees.

                                                                                      see Webservice

                                                                                      RFID (radio-frequency identification) is a technology for transmitter-receiver systems for the automatic and contactless identification and localisation of objects using radio waves. An RFID system consists of a transponder, which is located on or in the object and contains an identifying code, as well as a reader for reading this code.

                                                                                      Basically 3 different types of transponders can be distinguished:

                                                                                      1. The simplest category is only used to determine whether it is activated in the reception area of a reader. Otherwise no further identification is possible or necessary. These are used, for example, for anti-theft protection of clothing in department shops.  In this case only 2 states are queried: activated or not activated.

                                                                                      2. Read-only transponders can only be read, but not written. For example, they permanently transmit the serial number of an object when they enter the reception range of readers. This type is preferably used for tracking and tracing.

                                                                                      3. Read-Write transponders are transponders with readable and writable memory. They can be read and written selectively. These more complex RFID storage media offer the most options. For example, such read and write transponders have been used in the production area for years for tool coding.

                                                                                      Robots are smart objects that have been extended by a motion mechanism. The best known example is probably the lawn mowing robot. Usually, robots and humans are separated by a protective fence. The safety fence prevents the robot's movement from injuring or killing people through carelessness. But the safety fence also prevents the robot and humans from working together directly.

                                                                                      These restrictions no longer exist with a collaborative robot (Cobot for short). In human-robot collaboration, humans and robots work hand in hand. Here the robot assists the human. This means that the robot does not replace the human being, but complements his abilities and relieves him of stressful tasks. This can be overhead work or lifting heavy loads, for example.

                                                                                      The basic prerequisite for human-robot collaboration are the following sensitive skills:

                                                                                      • Proximity sensors which detect unwanted contact between man and robot in good time.

                                                                                      • Touch-sensitive sensors that reliably detect collisions of the robot with people and objects and stop the robot immediately in case of a collision.

                                                                                      In the factory of the future, people and robots work together collaboratively and optimally - without separation, without protective fencing.


                                                                                      Sequential Learning is a subfield of Machine Learning.

                                                                                      Simulation is used, for example, to detect errors at an early stage and prevent damage to a real system. In the CNC environment the virtualisation of NC machines, tools, devices and raw parts for 3D simulation purposes of the NC program is already standard in many places.

                                                                                      Simulation can also be used to depict extensive real factory processes, e.g. sequences of complete production lines are increasingly being simulated before assembly.

                                                                                      Intelligent sensor technology is increasingly conquering everyday life.

                                                                                      • When these raw data are evaluated and condensed over certain periods of time, then information is created 
                                                                                      • When this information is combined with digitised human knowledge, then intermediate results can be calculated or predicted 
                                                                                      • When these intermediate results are combined with digitised human experience, then you can generate first benefits 
                                                                                      • By combining these intermediate results with pattern finding algorithms(Data Mining), 
                                                                                         great benefits can be generated 

                                                                                      Dadurch kommt man zu neuartigen Erkenntnissen (=Smart Data) die es ermöglichen
                                                                                      neue Produkte, Prozesse oder Geschäftsmodelle zu entwickeln.


                                                                                      As Big Data or Data Lake denotes huge amounts of raw data. 
                                                                                      Through the use of Data Mining and Machine Learning new knowledge is gained from this, which is known as Smart Data. This method is also known as predictive analytics.

                                                                                      By the way:

                                                                                      The beginning of data collection and evaluation goes back a long way. This is how the country rules came into being. Farmers have always been particularly dependent on the weather and have therefore observed it closely. They noticed certain regularities, for example in the weather patterns or in the development of fruit and cereals. This pattern recognition enabled the farmers to improve their harvest. With the invention of computers, this was done by programming languages, thus improving the results.

                                                                                      The "Smart Factory" describes the change to a more resilient factory, in which man, machine and component communicate and only what is actually needed is manufactured. The raw and semi-finished products, as well as the finished products and the production aids (PRTs) necessary for their manufacture, carry intelligent and networked information carriers that communicate with their environment, people and equipment. The optimal combination of LEAN methods with the INDUSTRIAL 4.0 possibilities allows the Smart Factory to emerge step by step.

                                                                                      The formula is therefore: LEAN + INDUSTRY 4.0 = SMART FACTORY

                                                                                      With the help of "assistance systems" it is possible to manage a controllable process complexity without compromising process performance and process robustness. The increased use of sensor and actuator technology results in so-called cyber-physical systems, which relieve the assistance systems of tasks, make independent decisions and thus further relieve the human being. In the "Smart Factory", better energy and resource efficiency and higher productivity are achieved thanks to real-time control via the Internet of Things.

                                                                                      The following basics must be fulfilled in order to realise "Plug and Produce" in a "Smart Factory":

                                                                                      The master data is digitised completely and without errors.

                                                                                      A continuous connectivity in the brownfield can be established. To achieve this, it is necessary that all manufacturers of networkable products (assets) agree on the following 2 points:

                                                                                      1. to a common language such as OPC UA or umati. Under this premise, uniform OPC UA parameter sets are created promptly, which cover the respective subject-specific framework conditions.

                                                                                      2. to the need for a standardised Verwaltungsschale per Asset and deliver it with the asset.

                                                                                      This results in I4.0-Components and based on this MOM can make the „Plug and Produce“ work. A simple example is the printer installation. On Windows XP, or earlier, a printer installation was always an exciting task. In the days of Windows 10, a newly plugged in printer is completely self-configuring. ( = "Plug and Play").

                                                                                      "Smart Home" stands for the information, sensor and actuator technically upgraded and networked home:

                                                                                      This allows you to control e.g. heating, light, TV, music, coffee machine and co. from your sofa or on the road via app. All this is not absolutely necessary, but it does increase the comfort. In addition, it also increases security, as it allows automatic control of, for example, roller shutters, lighting, smoke detectors, surveillance systems and burglary protection:

                                                                                      "Smart-Home " is a nice example of the DIGITAL VALUE incl. its definition.

                                                                                      The term Smart Service stands for a digital service offering with integrated artificial Intelligence. The resulting digital products will be marketed via digital marketplaces.

                                                                                      One example is the Robo Advisor: 
                                                                                      The term Robo-Advisor is made up of the English words Robot and Advisor and stands for the automated form of investment. A Robo-Advisor helps to invest money digitally and, detached from human panic reactions (e.g. stock market crashes) or other suboptimal human decisions, calculates a digital investment strategy. The cleverer the AI, the better the results.

                                                                                      Another category is Smart Services, which require smart objects to provide services. This refers to networkable Assets such as machines or systems. An example is a modern heating system with e.g. a heat pump (=Asset),which is connected to the service centre via an internet router and is maintained remotely.

                                                                                      Smart objects combine mechanical, sensor, electrical and information technology components and are capable of wired or wireless communication, both with each other and with a higher-level data infrastructure.

                                                                                      Smart objects can be e.g. packaging, objects or workpieces equipped with a digital memory in the form of a data storage device. This links the digital world with the physical world. A prerequisite for this is the unambiguous identifiability of these objects. This is done, for example, by means of barcodes, RFID, NFC, or iBeacon which are recorded by scanners and computers. Figuratively speaking, the "intelligent" yoghurt cup of tomorrow knows whether it needs to be filled with strawberry or hazelnut yoghurt.

                                                                                      Smart objects have partially or completely the following characteristics through Embedded System :

                                                                                      1. Capability for identification and data storage

                                                                                      2. Integrated sensor technology for recording the environment

                                                                                      3. Ability to make independent decisions through data evaluation

                                                                                      4. Integrated actuators to influence the environment

                                                                                      5. Existing communication and networking capabilities

                                                                                      6. Integrated HMI, in case of human interference

                                                                                      In the event that a Smart Object meets the characteristics of points 2 to 4, it is therefore also a  Cyber-Physical System

                                                                                      Example: An automatic awning control system includes

                                                                                      • a sensor that measures the wind force (see point 2 above)

                                                                                      • a software that decides when the awning must be retracted automatically (see point 3 above)

                                                                                      • an actuator that retracts the awning using an electric motor (see point 4 above)

                                                                                      In terms of INDUSTRY 4.0, all  Assets Smart Objects as well. 

                                                                                      Through this service-oriented architecture, SOA allows IT systems to be structured and distributed. This allows IT components such as databases, servers and web services to be encapsulated in order to orchestrate the business processes.

                                                                                      see Webservice

                                                                                      Social media differ from traditional media such as television or newspapers in the way they communicate.  This takes place simply and interactively via digital channels. The currently best known examples of social media services are providers such as Facebook, Xing or WhatsApp. The great advantage of social media is the easy way in which information can be exchanged between users and sometimes devices. The German economy is also increasingly using this medium in its internal and external processes. Social media support a global corporate presence with high accessibility, enabling multimedia and the greatest possible topicality. The decisive difference to other media (newspaper, radio and television) is the ability of the recipient to respond immediately to any information. In the production area there are first applications, e.g. machine operators can contact the forklift driver to reorder material.

                                                                                      Software as a Service (SaaS) is a service that is offered in the Cloud .

                                                                                      Not to be confused with: Plattform as a Service (PaaS
                                                                                      PaaS refers to a service that is provided in theCloud .

                                                                                      This means that the user does not buy and install the required software, but only uses the software via the Internet when needed. The service recipient pays a usage fee for use and operation. Compared to a traditional licence model, the PaaS or SaaS model saves the service recipient the purchase and operating costs, IT administration, maintenance work and updates.

                                                                                      Differentiating PaaS from SaaS offerings: 
                                                                                      SaaS applications are functional software solutions for specific tasks and have a built-inne graphische Bedienoberfläche. Sie sind in der Regel explizit für Endanwender gemacht. Beispiel: Microsoft Office 365

                                                                                      PaaS applications are development environments, they include programming languages and other helpful programming tools and are intended for software developers to develop SaaS applications, for example. Example: Google App Engine

                                                                                      Master data are data records that remain unchanged over a longer period of time. The updating of master data takes place occasionally or periodically, or as required. master data contains basic information about objects relevant to the business:

                                                                                      • Customer master data includes e.g: Address, contact person, products used, etc.

                                                                                      • Article master data includes e.g: type, size, technical data

                                                                                      • Tool master data includes e.g: type, diameter, length, coating

                                                                                      A fundamental problem in almost all companies is incomplete master data!

                                                                                      In the age of Industry 3.0, this lack was compensated for by employees' knowledge of the head and handwritten additions to circulation documents. In the age of Industry 4.0 this way of working is no longer up to date, because assistance systems or  MOMsystems automatically generate process data from master data through data enrichment and for this purpose the master data must be complete and error-free.

                                                                                      Standardisation stands for unification or standardisation of "something". The standardisation before production steps is achieved by the introduction of Lean Management, or so-called "Best Practice" processes. A promise of INDUSTRY 4.0 is the control of any variance. This promise is only valid for the products and not for the processes!  The processes have to be standardised so that products of any variance can be produced.

                                                                                      The great enthusiasm for digitisation in the 90 years during and after the CIM (computer-integrated manufacturing) euphoria has led to the fact that almost every user request has been solved by special programming. This resulted in different processes in every factory for partly otherwise identical work steps. Through the introduction of Lean, some of these special solutions could be dissolved and standardised. Many companies are now attempting to transfer the large remainder of these company-specific processes to the digital world. This will fail for the following two reasons:

                                                                                      • The software of the future comes from the Cloud and requires standardised processes.

                                                                                      • The huge volume of historical special solutions cannot be digitised with the available resources.

                                                                                      INDUSTRY 4.0 is therefore only successful if you leave the beaten track and adopt standardised best practice solutions. In the sense of update capability, with rapidly increasing software penetration in all areas of every company, any other approach would be doomed to failure in the long term anyway. In this sense, all i4.0 Komponenten of Industry 4.0 first of all require a standardised communication protocol such as OPC UA and a management shell.

                                                                                      Standardisation realises simple Interoperability

                                                                                      Supervised Learning is a subfield of Machine Learning.


                                                                                      The body of a management shell can contain several partial models.

                                                                                      In the context of Industry 4.0, traceability stands for the traceability of workpieces or products. This means that it can be determined at any time when and where and by whom the individual parts were manufactured, processed, stored and transported. The realisation of the traceability of products over the entire life cycle is one of the prerequisites for Industry 4.0!

                                                                                      During the production of each workpiece, each individual production step is tracked and stored, e.g. by means of sensors. If at a later point in time a damage occurs with this workpiece, then it can be traced back exactly how the workpiece was produced.

                                                                                      Traceability is the technical requirement for traceability! For this purpose, each individual part to be tracked must be given a digital identification (e.g. with RFID or DataMatrix-Code, etc.).

                                                                                      A transaction platform, also known as a matching platform, mediates between two or more user groups, who are both dependent on interaction.

                                                                                      Hotel booking or dating platforms

                                                                                      Transformer technologies translate established technologies into modern, more advanced technologies. This includes the further development and improvement of existing possibilities.

                                                                                      Not everything around Industry 4.0 has to be disruptive. Many good solutions are transformational.

                                                                                      TSN stands for Time Sensitive Networking.

                                                                                      The aim of TSN is to improve real-time communication in computer networks through a set of standards. This is a further step to enable interoperability in the brownfield. TSN is processed and developed by the Time-Sensitive Networking Task Group.

                                                                                      You will find further information here.


                                                                                      umati stands for (universal machine tool interface) and is a universal interface for machine tools.
                                                                                      umati is an initiative of the VDW (Verein Deutscher Werkzeugmaschinenfabriken) in association with partners.
                                                                                      umati was launched as a project in Hannover at EMO 2017.

                                                                                      Based on the platform-independent standard  OPC UA umati can be used license-free as an open standard and is therefore suitable as a communication platform for connecting a wide range of devices.


                                                                                      ValueFacturing® is a cognitive assistance system for high-performance digital manufacturing. On the one hand, it acts as a data hub and link between the ERP system and the shop floor (vertical integration) and on the other hand as a link between the individual units (machines and plants) executing the production process on the shop floor (horizontale Integration).

                                                                                      In addition, the assistance system includes a "data pump" that collects raw data, which is generated in huge quantities by digitalisation and is processed by pattern recognition (Data Mining) refined. This provides novel insights that make it possible to master increasing quality requirements, shorter delivery times, shortening product life cycles and a growing number of variants.

                                                                                      Additionally ValueFacturing MES functions (Manufacturing Execution System) and is currently developing into a MOM (Manufacturing Operations Management) .

                                                                                      With decentralised networking, the communication points speak directly to each other. With centralised networking, the communication points do not speak directly to each other but via a so-called HUB. This significantly reduces the number of interfaces required for this.

                                                                                      The more communication participants, the greater the difference.

                                                                                      The prayerful repetition that INDUSTRIAL 4.0 must run exclusively decentralised can be called into question by the above table and can already be refuted by autonomous driving.

                                                                                      Of course, autonomously driving cars must communicate decentrally. However, they need additional central support, otherwise it would not be possible to receive forward-looking information.

                                                                                      Industry 4.0 requires both decentralised communication and centralised support.

                                                                                      Within the framework of horizontal networking, all machines, plants, software systems and people are networked at shop floor level using information technology. A major task is to provide the necessary interfaces to enable communication between the machines and plants that regularly work with proprietary data formats (brownfield). Within the framework of vertical networking, meaningful data from physical (=horizontal) production is connected to the planning ERP/PPS system. This vertical networking can extend into the Cloud .

                                                                                      Both horizontal and vertical networking must be completely bidirectional (in both directions)!

                                                                                      Virtual reality (or "virtual reality") replaces human perception without exception with virtual information. The user is completely immersed in this virtual and digital 3D world and no longer perceives the real environment. The user requires virtual reality glasses such as the Oculus Rift.

                                                                                      The Virtual Reality (VR) user sees 100% virtual images. Example see here.

                                                                                      The Augmented Reality (AR) user sees a mixture of real and virtual images, which are not spatially related to each other.

                                                                                      The Mixed Reality (MR) user sees a mixture of real and virtual images that have a spatial relationship to each other.

                                                                                      Visualisation is the representation of information in visible form, which can consist of pictures, texts, numbers, etc.

                                                                                      The speedometer in the car shows the actual speed driven and enables the driver to comply with existing speed limits, which would not be possible with the necessary accuracy without visualisation.

                                                                                      In the sense of I 4.0, visualisation stands for the preparation of raw data to quickly graspable representations with high information content.

                                                                                      The weather radar makes the course of the rain clouds visible. The visualisation of machine states is also made possible by visualisation in the form of a modern HMI. 

                                                                                      • Delimitation:
                                                                                        Visualisation displays states only pictorially, without reacting automatically to critical states.

                                                                                      • Condition Monitoring reacts to critical conditions or to values outside a defined range.

                                                                                      • Predictive Maintenance can calculate in advance, based on the conditions, when maintenance should be performed.


                                                                                      Wearables are mini-computers that are worn on the user's body during use (e.g. Smartwatch, fitness wristbands, data glasses) A Wearable can also be integrated into clothing or shoes.

                                                                                      Wearables measure e.g. bodily functions, such as the pulse. 
                                                                                      Wearables are also used as digital blood sugar and blood pressure measuring devices.

                                                                                      For 2 applications or 2 assets to communicate with each other they need a communication method.

                                                                                      A traditional communication method from the days of Industry 3.0 is to monitor a folder on a network drive. When a file arrives, it is parsed (evaluated line by line) and appropriate actions are initiated. This method has considerable disadvantages, e.g. the initiating partner has no information about what is happening on the other side.

                                                                                      In the days of INDUSTRY 4.0 this method has no future, because now people communicate via web service. A web service is a service that enables communication between machines or applications via a computer network. WebServices have no user interface for humans. The realisation is carried out by means of service-oriented architecture (SOA).

                                                                                      Both SOAP and REST are suitable web services.

                                                                                      SOAP stands for Simple Object Access Protocol and is an industrial standard of the World Wide Web.

                                                                                      REST stands for Representational State Transfer and represents a simple alternative to SOAP.

                                                                                      Both SOAP and REST web services meet the required capabilities for IoT. The decision for SOAP or REST is often made by the software development culture or by the project requirements of a company.

                                                                                      WiFi (often also written Wi-Fi) is the short form of wireless fidelity. WiFi is a label or brand name and stands for a radio network standard that enables devices to receive WLAN.

                                                                                      WLAN stands for "Wireless Local Area Network". Translated this means "wireless local area network". WLAN allows you to connect terminal devices (e.g. laptops & smartphones) to the Internet without cables.

                                                                                      WiFi is often used as a synonym for WLAN. Strictly speaking, however, WLAN and WiFi are not the same thing. However, these differences are less relevant for users. Whether WLAN or WiFi - in the end, you can use both terms synonymously, because both stand for "wireless network" in the German-speaking world.

                                                                                      Please note, however, that the term "WLAN" is not used in most foreign language countries. If you want to use WLAN abroad, use the term "WiFi".

                                                                                      Profitability potentials

                                                                                      The key question is: How can the economic potential of Industry 4.0 investments be methodologically assessed?

                                                                                      Die Antwort liegt in Prozess- und Potenzialanalysen. Der verlinkte Fachartikel der Zeitschrift Controlling gibt hier Antworten: 
                                                                                      Veröffentlichung der Zeitschrift für Controlling

                                                                                      Copyright: Johann Hofmann