Industry 4.0

Industry 4.0 is a name for the current trend of automation and data exchange in manufacturing technologies. It includes cyber-physical systems , the Internet of things , cloud computing [1] [2] [3] [4] and cognitive computing .

Industry 4.0 creates what has been called a smart factory. Within the modular structured smart factories, the cyber-physical systems monitor physical processes, create a virtual copy of the physical world and make decentralized decisions. Over the Internet of Things, cyber-physical systems, and the Internet of Services , both internal and cross-organizational services are used by participants of the value chain . [1]


The term “Industry 4.0” originates from a project in the high-tech strategy of the German government , which promotes the computerization of manufacturing. [5]

The term “Industry 4.0” was revived in 2011 at the Hannover Fair . [6] In October 2012 the Working Group on Industry 4.0 presented a set of Industry 4.0 implementation recommendations to the German federal government. The Industry 4.0 workgroup members are recognized as the founding fathers and driving force behind Industry 4.0.

Industry 4.0 Workgroups [7]

Co-Chair Henning Kagermann and Siegfried Dais
WG 1 – The Smart Factory: Manfred Wittenstein
WG 2 – The Real Environment: Siegfried Russwurm
WG 3 – The Economic Environment: Stephan Fische
WG 4 – Human Beings and Work: Wolfgang Wahlster
WG 5 – The Technology Factor: Heinz Derenbach

Industry 4.0 Workgroup members
Reinhold Achatz, Heinrich Arnold, Klaus Träger, Johannes Helbig, Wolfram Jost, Peter Leibinger, Reinhard Floss, Volker Smid, Thomas Weber, Eberhard Veit, Christian Zeidler, Reiner Anderl, Bauernhansl Thomas , Michael Beigl, Manfred Brot, Werner Damm, Jürgen Gausemeier, Otthein Herzog, Fritz Klicke, Gunther Reinhart, Bernd Scholz-Reiter, Bernhard Diener, Rainer Platz, Gisela Lanza, Karsten Ortenberg, August Wilhelm Scheer , Henrik von Scheel , Dieter Schwer, Ingrid Sehrbrock, Dieter Spatz, Ursula M Staudinger, Andreas Geerdeter, Wolf-Dieter Lukas, Ingo Rühmann, Alexander Kettenborn and Clemens Zielinka.

On April 8, 2013 at the Hannover Fair, the final report of the Working Group Industry 4.0 was presented. [8]

Design principles

There are four design principles in Industry 4.0. These principles support companies in identifying industry 4.0 scenarios. [1]

  • Interoperability: The ability of machines, devices, sensors, and people to connect and communicate via Internet of Things (IoT) or the Internet of People (IoP)
    • Adding IoT will further automate the process to a large extent [9]
  • Information transparency: The ability of information systems to create a virtual copy of the world by. This requires the aggregation of raw sensory data to higher-value context information.
  • Technical assistance: First, the ability of assistance systems to support humans by aggregating and visualizing information. Second, the ability of cyber physical systems to physically support humans by conduct of tasks that are unpleasant, too exhausting, or unsafe for their human co-workers.
  • Decentralized decisions: The ability of cyber physical systems to make decisions on their own and to perform their tasks as autonomously as possible. Only in the case of exceptions, interferences, or conflicting goals, are tasks delegated to a higher level.


Current use of the term has been criticized in the field of technological innovation and the concept of innovation in the field of innovation. [10]

The characteristics given for the German government’s Industry 4.0 strategy are: the strong customization of products under the conditions of highly flexible (mass-) production. The required automation technology is improved by the introduction of methods of self-optimization, self-configuration, [11] self-diagnosis, cognition and intelligent support of workers in their increasingly complex work. [12] The largest project in Industry 4.0 as of July 2013 is the leading edge-cluster BMBF “Intelligent Technical Systems Ostwestfalen-Lippe (it’s OWL)”. Another major project is the BMBF project RES-COM, [13] Cluster of Excellence “Integrative Production Technology for High-Wage Countries”. [14]In 2015, the European Commission launched the international Horizon 2020 research project CREMA [15] (Providing Cloud-based Rapid Manufacturing Elastic Manufacturing Based on the XaaS and Cloud Model) as a major initiative to foster the Industry 4.0 topic.


In June 2013, consultancy firm McKinsey [16] released an interview featuring an expert discussion between executives at Robert Bosch – Siegfried Dais (Partner of the Bosch Robert Bosch Industrietreuhand) and Heinz Derenbach (CEO of Bosch Software Innovations GmbH) – and McKinsey experts. This interview addresses the prevalence of the Internet of Things in Manufacturing and the technology-driven changes that promise to trigger a new industrial revolution. At Bosch, and in Germany, this phenomenon is referred to as Industry 4.0. The basic principle of Industry is that by connecting machines, workpieces and systems, businesses are creating intelligent networks along the entire value chain.

Some examples for Industry are those that can predict failures and trigger maintenance processes that are self-organizing or that are self-organizing.

According to Dais, “it is highly likely that the world of production will become more and more”. While this sounds like a reality and the driving force behind the Internet of Things, it also means that the complexity of production and supplier networks will grow enormously. Networks and processes have been limited to one factory. But in an Industry 4.0 scenario, these boundaries of individual factories will most likely no longer exist. Instead, they will be lifted in order to interconnect multiple factories or even geographical regions.

There are differences between a typical traditional factory and an Industry 4.0 factory. In the current industry environment, providing high-end product quality assurance is the key to success and success in improving performance and profitability. In this way, various data sources are available to provide valuable information about different aspects of the factory. In this stage, the use of data for understanding current operating conditions and detecting faults and failures is an important topic to research. eg in production, there are various commercial tools to provide overall equipment effectiveness (OEE)root causes of problems and possible faults in the system. In contrast, in an Industry 4.0 factory, in addition to condition monitoring and fault diagnosis, components and systems are able to gain self-awareness and self-predictiveness, which will provide management with more insight on the status of the factory. More, peer-to-peer comparison, and the need for more accurate information. -Zero downtime. [17]


Challenges in Implementation of Industry 4.0: [18]

  • IT security issues, which are greatly aggravated by the former need for closed production
  • Reliability and stability needed for critical machine-to-machine (M2M), including very short and stable latency times
  • Need to maintain the integrity of production processes
  • Need to avoid any IT snags, as those would cause expensive production tools
  • Need to protect industrial know how (also in the control of industrial automation gear)
  • Lack of adequate skill-sets to expedite the market towards fourth industrial revolution
  • Threat of redundancy of the corporate IT department
  • General reluctance to change by stakeholders
  • Loss of many jobs to automatic processes and IT-controlled processes, especially for lower educated parts of society [19]

Role of big data and analytics

Modern information and communication technologies like cyber-physical system , big data analytics and cloud computing , will help early detection of defects and production failures, thus enabling their prevention and increasing productivity, quality and agility benefits that have significant competitive value.

Big data analytics consists of 6Cs in the integrated industry 4.0 and cyber physical systems environment. The 6C system included:

  1. Connection (sensor and networks)
  2. Cloud (computing and data on demand)
  3. Cyber ​​(model & memory)
  4. Content / context (meaning and correlation)
  5. Community (sharing & collaboration)
  6. Customization (personalization and value)

In this scenario, the data has been processed to generate meaningful information (analytics and algorithms). Considering the presence of visible and invisible issues in an industrial factory, the information generation algorithm has to be capable of detecting and addressing invisible issues such as machine degradation, component wear, etc. in the factory floor. [20] [21]

Impact of Industry 4.0

Proponents of the term claim Industry 4.0 will affect many areas, most notably:

  1. Services and business models
  2. Reliability and continuous productivity
  3. IT security: Companies like Symantec , Cisco , and Penta Security have already entered the issue of IoT security
  4. Machine safety
  5. Product lifecycles
  6. Industry value chain
  7. Workers’ education and skills
  8. Socio-economic factors
  9. Industry Demonstration: To help industry understand the impact of Industry 4.0, Cincinnati Mayor John Cranley, signed a proclamation to state “Cincinnati to be Industry 4.0 Demonstration City”. [22]
  10. An article published in February 2016 suggests that Industry 4.0 can have a beneficial effect for emerging economies such as India . [23]

See also

  • Computer-integrated manufacturing
  • Digital modeling and manufacturing
  • Industrial control system
  • Intelligent Maintenance Systems
  • Machine to machine
  • Predictive manufacturing system
  • Cyber ​​manufacturing
  • Service 4.0
  • World Economic Forum 2016
  • Fourth Industrial Revolution


  1. ^ Jump up to:c Hermann, Pentek, Otto, 2016: Principles for Industry Design 4.0 Scenarios , accessed on 4 May 2016
  2. Jump up^ Jürgen Jasperneite: Was hinter Begriffen wie Industry 4.0 stecktinComputer & Automation, 19 Dezember 2012 accessed on 23 December 2012
  3. Jump up^ Kagermann, H., W. Wahlster and J. Helbig, eds., 2013: Recommendations for implementing the industrial initiative Industry 4.0: Final report of the Industry 4.0 Working Group
  4. Jump up^ Heiner Lasi, Hans-Georg Kemper, Peter Fettke, Thomas Feld, Michael Hoffmann: Industry 4.0. In: Business & Information Systems Engineering 4 (6), pp. 239-242
  5. Jump up^ BMBF-Internetredaktion (2016-01-21). “Zukunftsprojekt Industrie 4.0 – BMBF” . . Retrieved 2016-11-30 .
  6. Jump up^ “Industry 4.0: Mit dem Internet der Dinge auf dem Weg zur 4. Industriellen Revolution” . (in German). 2011-04-01 . Retrieved 2016-11-30 .
  7. Jump up^ “Securing the Future of German Manufacturing Industry: Recommendations for Implementing the Strategic Initiative INDUSTRY 4.0: Final Report of the Industry 4.0 Working Group” (PDF) . . Retrieved 2016-11-30 .
  8. Jump up^ Industry 4.0 PlattformLast download on 15. Juli 2013
  9. Jump up^ “IOT role in industry 4.0” . May 19, 2016 – via TechiExpert.
  10. Jump up^ “You Have Reached a 404 Page” . 22 September 2013 – via Slate.
  11. Jump up^ Selbstkonfiguierende Automation for Intelligent Technische Systeme, Video, last download on 27. Dezember 2012
  12. Jump up^ Jürgen Jasperneite; Oliver, Niggemann: Intelligent Assistenzsysteme zur Beherrschung der Systemkomplexität in der Automation. In: ATP edition – Automatisierungstechnische Praxis, 9/2012, Oldenburg Verlag, München, September 2012
  13. Jump up^ “Herzlich willkommen auf den Internetseiten Projekts RES-COM – RES-COM Website” . . Retrieved 2016-11-30 .
  14. Jump up^ “RWTH AACHEN UNIVERSITY Cluster of Excellence” Integrative Production Technology for High-Wage Countries “- English” . . 2016-10-19 . Retrieved 2016-11-30 .
  15. Jump up^ “CREMA H2020 – Cloud-based Rapid Elastic Manufacturing” . . 2016-11-21 . Retrieved 2016-11-30 .
  16. Jump up^ Markus Liffler; Andreas Tschiesner (2013-01-06). “The Internet of Things and the future of manufacturing | McKinsey & Company” . . Retrieved 2016-11-30 .
  17. Jump up^ “Tec.News: 26” (PDF) . . Retrieved 2016-11-30 .
  18. Jump up^ “Industry 4.0” . Retrieved 9 Oct 2017 .
  19. Jump up^ {{cite
    • Low top management commitment
    • Unclear legal issues and data security
    • Unclear economic benefits / Excessive investment
    • Lack regulation, standard and forms of certifications
    • Insufficient qualification of employees

    web | url = | format = PDF | title = BIBB: Industry 4.0 und die Folgen für Arbeitsmarkt und Wirtschaft | date = August 2015 | website = Doku.iab .de | accessdate = 2016-11-30}}

  20. Jump up^ Lee, Jay; Bagheri, Behrad; Kao, Hung-An (2014). “Recent Advances and Trends of Cyber-Physical Systems and Big Data Analytics in Industrial Informatics” . IEEE Int. Conference on Industrial Informatics (INDIN) 2014 .
  21. Jump up^ Lee, Jay; Lapira, Edzel; Bagheri, Behrad; Kao, Hung-an. “Recent advances and trends in big data environment prediction . Manufacturing Letters . 1 (1): 38-41. doi : 10.1016 / j.mfglet.2013.09.005 .
  22. Jump up^ “Cincinnati Mayor Proclaimed” Cincinnati to be Industry 4.0 Demonstration City ” ” . . Retrieved 2016-07-30 .
  23. Jump up^ Anil K Rajvanshi (2016-02-24). “India Can Gain By Leapfrogging Into Fourth Industrial Revolution” . The Quint . Retrieved 2016-11-30 .