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Industrial revolutions and future view

Industry 4.0 is a name given to 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 is commonly referred to as the fourth industrial revolution.[5]

Industry 4.0 fosters what has been called a "smart factory". Within modular structured smart factories, 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 communicate and cooperate with each other and with humans in real-time both internally and across organizational services offered and used by participants of the value chain.[1]



The term "Industry 4.0", shortened to I4.0 or simply I4, originates from a project in the high-tech strategy of the German government, which promotes the computerization of manufacturing.[6]

The term "Industry 4.0" was revived in 2011 at the Hannover Fair.[7] 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 and partners are recognized as the founding fathers and driving force behind Industry 4.0.

On 8 April 2013 at the Hannover Fair, the final report of the Working Group Industry 4.0 was presented.[8]. This working group was headed by Siegfried Dais (Robert Bosch GmbH) and Henning Kagermann (German Academy of Science and Engineering).

As Industry 4.0 principles have been applied by companies they have sometimes been re-branded, for example the aerospace parts manufacturer Meggitt PLC has branded its own Industry 4.0 research project M4. [9]

Design principlesEdit

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

  • Interconnection: The ability of machines, devices, sensors, and people to connect and communicate with each other via the Internet of Things (IoT) or the Internet of People (IoP)[10]
  • Information transparency: The transparency afforded by Industry 4.0 technology provides operators with vast amounts of useful information needed to make appropriate decisions. Inter-connectivity allows operators to collect immense amounts of data and information from all points in the manufacturing process, thus aiding functionality and identifying key areas that can benefit from innovation and improvement.[11]
  • Technical assistance: First, the ability of assistance systems to support humans by aggregating and visualizing information comprehensively for making informed decisions and solving urgent problems on short notice. Second, the ability of cyber physical systems to physically support humans by conducting a range 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.


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.[12] The required automation technology is improved by the introduction of methods of self-optimization, self-configuration,[13] self-diagnosis, cognition and intelligent support of workers in their increasingly complex work.[14] The largest project in Industry 4.0 as of July 2013 is the BMBF leading-edge cluster "Intelligent Technical Systems Ostwestfalen-Lippe (it's OWL)". Another major project is the BMBF project RES-COM,[15] as well as the Cluster of Excellence "Integrative Production Technology for High-Wage Countries".[16] In 2015, the European Commission started the international Horizon 2020 research project CREMA[17] (Providing Cloud-based Rapid 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[18] released an interview featuring an expert discussion between executives at Robert Bosch – Siegfried Dais (Partner of the Robert Bosch Industrietreuhand KG) and Heinz Derenbach (CEO of Bosch Software Innovations GmbH) – and McKinsey experts. This interview addressed the prevalence of the Internet of Things in manufacturing and the consequent technology-driven changes which promise to trigger a new industrial revolution. At Bosch, and generally in Germany, this phenomenon is referred to as Industry 4.0. The basic principle of Industry 4.0 is that by connecting machines, work pieces and systems, businesses are creating intelligent networks along the entire value chain that can control each other autonomously.

Some examples for Industry 4.0 are machines which can predict failures and trigger maintenance processes autonomously or self-organized logistics which react to unexpected changes in production.

According to Dais, "it is highly likely that the world of production will become more and more networked until everything is interlinked with everything else". While this sounds like a fair assumption 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 so far 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 quality service or product with the least cost is the key to success and industrial factories are trying to achieve as much performance as possible to increase their profit as well as their reputation. In this way, various data sources are available to provide worthwhile information about different aspects of the factory. In this stage, the utilization of data for understanding current operating conditions and detecting faults and failures is an important topic to research. e.g. in production, there are various commercial tools available to provide overall equipment effectiveness (OEE) information to factory management in order to highlight the 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. Furthermore, peer-to-peer comparison and fusion of health information from various components provides a precise health prediction in component and system levels and forces factory management to trigger required maintenance at the best possible time to reach just-in-time maintenance and gain near-zero downtime.[19]

During EDP Open Innovation conducted in Oct 2018 at Lisbon, Portugal, Industry 4.0 conceptualization was extended by Sensfix B.V. a Dutch company with introduction of M2S terminology. It essentially is characterizing upcoming service industry to cater to millions of machines, managed by the machines themselves.


Challenges in implementation of Industry 4.0:[20]

  • IT security issues, which are greatly aggravated by the inherent need to open up those previously closed production shops
  • Reliability and stability needed for critical machine-to-machine communication (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 outages
  • Need to protect industrial know-how (contained also in the control files for the industrial automation gear)
  • Lack of adequate skill-sets to expedite the transition towards the 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 blue collar workers
  • Low top management commitment
  • Unclear legal issues and data security
  • Unclear economic benefits/ excessive investment
  • Lack of regulation, standards and forms of certifications
  • Insufficient qualification of employees

Role of big data and analyticsEdit

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 comprises:

  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 and in order to provide useful insight to the factory management, data has to be processed with advanced tools (analytics and algorithms) to generate meaningful information. 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.[21][22]

Impact of Industry 4.0Edit

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 begun to address the issue of IoT security
  4. Machine safety
  5. Manufacturing Sales
  6. Product lifecycles
  7. Manufacturing Industries: Mass Customisations instead of mass manufacturing using IOT, 3D Printing and Machine Learning
  8. Industry value chain
  9. Workers' education and skills
  10. Socio-economic factors

An article published in February 2016 suggests that Industry 4.0 may have a beneficial effects for emerging economies such as India.[23] The aerospace industry has sometimes been characterized as "too low volume for extensive automation" however Industry 4.0 principles have been investigated by several aerospace companies, technologies have been developed to improve productivity where the upfront cost of automation cannot be justified, one example of this is the aerospace parts manufacturer Meggitt PLC's project, M4. [24] The discussion of how the shift to Industry 4.0, especially digitalization, will affect the labour market is being discussed in Germany under the topic of Work 4.0.[25]

Technology road map for Industry 4.0Edit

A "road map" enables whomsoever in industry to directly realize each move and what act need to be accomplish, who needs to make them and when. This method is decoded into a project plan, defining the characteristics of activity in each of the accompanying stages of formation. Considering an internationalized world, the need to actualize development strategies that can secure the sustainable competitiveness of establishments is the main issue. It is in this topic that Industry 4.0 road map grants itself as a visually pictured clear trail to boost the competitiveness of organizations.

The key benefits of technology road mappingEdit

  • Setting up coalition of technical and commercial master plans
  • Making better communication across teams and companies
  • Inspecting prospective competitive strategies and ways to carry out those strategies
  • Competent time management and mapping out
  • Conceptualizing outputs including goals, activities, and progresses.[26]

See alsoEdit


  1. ^ a b c Hermann, Pentek, Otto, 2016: Design Principles for Industrie 4.0 Scenarios, accessed on 4 May 2016
  2. ^ Jürgen Jasperneite:Was hinter Begriffen wie Industrie 4.0 steckt in Computer & Automation, 19 December 2012 accessed on 23 December 2012
  3. ^ Kagermann, H., W. Wahlster and J. Helbig, eds., 2013: Recommendations for implementing the strategic initiative Industrie 4.0: Final report of the Industrie 4.0 Working Group
  4. ^ 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. ^ Marr, Bernard. "Why Everyone Must Get Ready For The 4th Industrial Revolution". Forbes. Retrieved 14 February 2018.
  6. ^ BMBF-Internetredaktion (21 January 2016). "Zukunftsprojekt Industrie 4.0 - BMBF". Retrieved 30 November 2016.
  7. ^ "Industrie 4.0: Mit dem Internet der Dinge auf dem Weg zur 4. industriellen Revolution". (in German). 1 April 2011. Retrieved 30 November 2016.
  8. ^ Industrie 4.0 Plattform Last download on 15. Juli 2013
  9. ^ "Time to join the digital dots". 22 June 2018. Retrieved 25 July 2018.
  10. ^ Bonner, Mike. "What is Industry 4.0 and What Does it Mean for My Manufacturing?". Retrieved 24 September 2018.
  11. ^ Bonner, Mike. "What is Industry 4.0 and What Does it Mean for My Manufacturing?". Retrieved 24 September 2018.
  12. ^ "This Is Not the Fourth Industrial Revolution". 29 January 2016 – via Slate.
  13. ^ Selbstkonfiguierende Automation für Intelligente Technische Systeme, Video, last download on 27. Dezember 2012
  14. ^ Jürgen Jasperneite; Oliver, Niggemann: Intelligente Assistenzsysteme zur Beherrschung der Systemkomplexität in der Automation. In: ATP edition - Automatisierungstechnische Praxis, 9/2012, Oldenbourg Verlag, München, September 2012
  15. ^ "Herzlich willkommen auf den Internetseiten des Projekts RES-COM - RES-COM Webseite". Retrieved 30 November 2016.
  16. ^ "RWTH AACHEN UNIVERSITY Cluster of Excellence "Integrative Production Technology for High-Wage Countries" - English". 19 October 2016. Retrieved 30 November 2016.
  17. ^ "H2020 CREMA - Cloud-based Rapid Elastic Manufacturing". 21 November 2016. Retrieved 30 November 2016.
  18. ^ Markus Liffler; Andreas Tschiesner (6 January 2013). "The Internet of Things and the future of manufacturing | McKinsey & Company". Retrieved 30 November 2016.
  19. ^ Mueller, Egon; Chen, Xiao-Li; Riedel, Ralph (2017). "Challenges and Requirements for the Application of Industry 4.0: A Special Insight with the Usage of Cyber-Physical System". Chinese Journal of Mechanical Engineering. 30 (5): 1050–1057. doi:10.1007/s10033-017-0164-7.
  20. ^ "BIBB : Industrie 4.0 und die Folgen für Arbeitsmarkt und Wirtschaft" (PDF). (in German). August 2015. Retrieved 30 November 2016.
  21. ^ 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. doi:10.13140/2.1.1464.1920.
  22. ^ Lee, Jay; Lapira, Edzel; Bagheri, Behrad; Kao, Hung-an (October 2013). "Recent advances and trends in predictive manufacturing systems in big data environment". Manufacturing Letters. 1 (1): 38–41. doi:10.1016/j.mfglet.2013.09.005.
  23. ^ Anil K. Rajvanshi (24 February 2016). "India Can Gain By Leapfrogging Into Fourth Industrial Revolution". The Quint. Retrieved 30 November 2016.
  24. ^ "Time to join the digital dots". 22 June 2018. Retrieved 25 July 2018.
  25. ^ Federal Ministry of Labour and Social Affairs of Germany (2015). Re-Imagining Work: White Paper Work 4.0.
  26. ^ Sarvari, Peiman Alipour; Ustundag, Alp; Cevikcan, Emre; Kaya, Ihsan; Cebi, Selcuk (16 September 2017), "Technology Roadmap for Industry 4.0", Springer Series in Advanced Manufacturing, Springer International Publishing, pp. 95–103, doi:10.1007/978-3-319-57870-5_5, ISBN 9783319578699