Industry 3.X and TPM deciphered

Following our last article "Industry 4.0... well let's talk about 3.X!, we propose to continue with a brief description of the TPM supplemented by the different types of technologies in Industry 4.0.

What is the TPM?

Machines’ defects or failures during production have negative effects on the production schedule as well as on employee morale. Total Productive Maintenance (TPM) is at the origin of the equipment reliability. It is essentially machine-centric and its productivity measured by the OEE (Overall Equipment Efficiency, also called TRS for Synthetic Efficiency Ratio). *

The focus is on reducing the 16 OEE generalized losses, classified into three groups: equipment losses, labor-related losses, and material-, tool- and energy-related losses.

The JIPM (Japan Institute for Plant Maintenance) has defined in 1989 the eight pillars of the TPM management approach :

Autonomous management and maintenance of equipment

Waste elimination / Improvements on a case-by-case basis

Scheduled maintenance

Improvement of knowledge and know-how:

Safety, working conditions and environment

Quality control or maintenance

Mastering product design and associated equipment

Efficiency of related services or "TPM at the office"

These eight pillars will remain the industry fundamental. The question is simple: "How will the 3.X consolidate and ensure ever more efficient maintenance? ".

What does Industry 3.X bring us?

The analysis of Big Data, the Internet of Things, artificial intelligence, virtual and augmented reality, and cyber-physical systems are considered the main levers of the next digital upgrade.

  • Big Data analysis

The term "big data" refers to large, technically complex data sets for typical data analysis and processing applications. Big Data analysis allows companies to "predict". Companies can predict events using in-depth analysis of large data sets that will be actively monitored. The amount of information stored is growing four times faster than the global economy, while computing speeds are growing nine times faster. This remains very important because from the beginning of the digital data creation until 2003, there were 5 exabytes of information created and now the same amount of information is created every two days. A study with over 2,000 business participants from 9 major industry sectors and 26 countries, shows that 80% of global CEOs have recognized the importance of data mining and analytics for their organizations. Large data can extract new data from existing data, providing important technical and business information that helps make clearer and more efficient decisions.

Cloud computing and machine learning are also leading technologies in Big Data analytics, cloud computing is a scalable platform that helps to use IT resources more efficiently, helping automate and reducing system costs. isolated. Cloud manufacturing is the concept that reflects the idea of a smart factory, that is, the collaboration of advanced production models with cloud computing technology to achieve computer-based and service-oriented production. (Givehchi, Tresk and Jasperneite, 2013).

  • Internet of Things (IoT)

The idea of the Internet of Things appeared for the first time in the 1980s to meet the needs of automated teller machines (Shon, 1996). Many of these devices have been networked. The Internet of Things (IoT) is the terminology used for physical devices or components that can be connected via the network and have the ability to communicate with each other via Radio Frequency Identification (RIFD) or intelligent sensors (Gilchrist, 2016b ). According to ISO / IEC JTC1 (2015), IoT is an infrastructure of interconnected objects, people, systems and information resources as well as intelligent services to enable them to process information from the physical and virtual world and react. However, it is a concept similar to physical cyber systems (CPS). According to an estimate, around 25 billion devices / objects will be interconnected and will communicate with each other, and this will be used by 2020. The Internet of Things allows businesses to add transparency to processes and make it analytically measurable. These sensors can be worn by the operators, placed on the production lines, on the machines directly, in the warehouses ...

Similarly, the new RFID type solutions make it possible to guarantee a perfect products traceability on the value chain and also to measure everyday performance through the collection of relevant data. IoT's ability to offer enhanced intelligence helps organizations optimize decision-making capabilities, ensure efficient data collection, and generate the right reports for their specific environment. IoT helps the company gain "intelligence" by giving them the ability to analyze their physical processes that were not measurable before. All of this contributes to better strategic and operational capacity and, in some cases, to a competitive advantage (Kopetz, 2011).

  • Artificial Intelligence

AI was introduced as a field of research in the late 1950s. Artificial intelligence is a sub-domain of computer science, whose sole purpose is to give machines or robots a human intelligence as they become independent platforms and able to make intelligent decisions autonomously (McCarthy, 2007). There are two types of AI: Artificial Narrow Intelligence (ANI) which is related to single-task applications in a very specific area that we are witnessing today (ie Go game), then there is Artificial General Intelligence (AGI) which is still developing. The concept of AGI is broad, deep and contains features that surpass human intelligence in many dimensions such as analytic speed, memory, multitasking, pattern recognition and adaptability with new auto information. Learned (Muehlhauser, 2013). According to Hawking et al. (2014), the success in creating the AGI would be the biggest event in human history, but they are not sure whether it is also the last, unless one learns to avoid risk, hence the experts’ hesitant vision in relation to AI.

How many jobs will be replaced by robots and AI in the coming years? And how many new jobs and positions will there be created? The answer is not given but, as an example, Japan's largest bank, Mitsubishi UFJ Finance, has recently installed robots for its customer service operations and IPsoft, a call center, is using an AI robot called "Amelia" able to self-learn outside preprogrammed knowledge. "Amelia" can now process more than 60% of all incoming requests.

  • Virtual and Augmented Reality

The Smart Factory will be supported by advanced human resources programs in "Virtual Reality and Augmented Reality". Virtual Reality (VR) is a computer-simulated environment. It is presented to the user as a real environment. It can support employee training programs and business process support with compatible digital devices. On the other hand, Augmented Reality (AR) has a head start and allows the user to interfere with a simulated environment (Boud et al., 1999). According to Jason Ganz, CEO of Agora VR, "Internet has allowed us to learn anything - VR and AR will allow us to experiment everything". Experts suggest that some of the management tasks will be held virtually as, for example, meetings and strategic conferences. In addition, the RV and RA will assist the Human Resources Department in training and the continuous coaching system for transition in a digital environment.

  • Cyber-physical systems

In order to make the smart factory operational or functional, we will need "Cyber Physical Systems (CPS)". CPS’s are intelligent systems that bridge virtual and physical components used in production, logistics and products. It is the concept that combines with the Internet of Services (IoS) to make 3.X industry possible, opening up new possibilities for innovative applications and processes. CPS’s will facilitate the paradigm shift from business models and market models to all stakeholders in the value chain including suppliers. All these technologies combined to other technologies such as additive manufacturing, for example 3D printing, selective laser sintering, cobotic, AGV, etc., are the basis for the future factory, which brings together virtual and physical systems via physical cyber systems. Such a fusion of technical processes and business processes will be a gateway to the concept known as the "Smart Factory" (MacDougall, 2014).

All these technologies already known, how will they contribute to production sites? And especially as part of a TPM approach? In the next article, we will present the contributions of the digitized environment to the TPM and more broadly, practical solutions that we put in place within our customers’ companies.

Sources :

Boud, A. C., Haniff, D. J., Baber, C., & Steiner, S. J. (1999). Virtual reality and augmented reality as a training tool for assembly tasks. In Information Visualization, 1999. Proceedings. 1999 IEEE International Conference on (pp. 32-36). IEEE.

Gilchrist, A. (2016b). Middleware Industrial Internet of Things Platforms. In Industry 4.0 (pp. 153-160). Apress.

Givehchi, O., Trsek, H., & Jasperneite, J. (2013). Cloud computing for industrial automation systems—A comprehensive overview. In Emerging Technologies & Factory Automation (ETFA), 2013 IEEE 18th Conference on (pp. 1-4). IEEE.

Hawking, S., Russell, S., Tegmark, M., & Wilczek, F. (2014). Stephen Hawking: \'Transcendence looks at the implications of artificial intelligence-but are we taking AI seriously enough?'. The Independent, 2014(05-01), 9313474

Kopetz, H. (2011). Internet of things. In Real-time systems (pp. 307-323). Springer US.

Shon, S. W. (1996). U.S. Patent No. 5,499,238. Washington, DC: U.S. Patent and Trademark Office.

MacDougall, W. (2014). Industrie 4.0: Smart manufacturing for the future. Germany Trade & Invest.

McCarthy, J. (2007). WHAT IS ARTIFICIAL INTELLIGENCE? Retrieved March 15, 2017, from

Muehlhauser, L. (2013, September 15). What is AGI? Retrieved March 26, 2018, from

Industry 4.0… well let’s talk about 3.X!

Industry 4.0 has become obvious for everyone... but we must keep a sense of proportion!

The term Industry 4.0 was introduced for the first time during the 2011 Hanover Fair (Wahlster, 2012). It comes from an initiative launched by the German Federal Government as part of its overall High-Tech strategy. An introduction to the Industry 4.0 concepts can be found in Lasi et al. (2014).

For the record, the first industrial revolution reflects the automation of production through steam and water (Industry 1.0); for the second one, the electrification (2.0) has arrived, and finally, more recently, the third one saw the digital computer advent (3.0). All these revolutions were related to inventions based on breakthrough scientific discoveries (Watt, Tesla, von Neuman) opening up new industries.

Bear in mind that even other revolutionary inventions, such as Marconi's (1909 Nobel Prize) wireless telecommunication, which is the basis of today's global communication, as well as varied possibilities for supply chain control in the modern production are not considered "revolutions" for the industry.

Thus, the Industry 4.0 concept is not linked to a technical revolution following a breakthrough scientific discovery!

Indeed, main tools required for the Industry 4.0 implementation have already existed for a long time: sensors, robots, big data, Internet of Things, cloud computing, 3D printer. More than a technological revolution, Industry 4.0 represents rather a complete reorganization of the mode of production with the modern tools, giving a bigger weight to the network. 

This new generation of factories aims to boost the dynamism of European industry through several actions: modernization of production, increase of competitiveness, flexibility in demand, positioning in front of the challenges of globalization...

If it's not a revolution, then why is it THE subject today? 

Every company today has to communicate on digital. According to recent studies, several hundreds of billions of 4.0 investments are launched each year in the world. Companies expect returns on investment in less than two years by generating several additional revenue points while reducing costs - 2 to 4% according studies. In this context, the main players are banking on this high-potential market and are making war on platforms for the factory of the future: Siemens with MindSphere, GE with Predix, Bosch with IoT Bosch Suite, ABB with ABB Ability, etc.

Today, global players such as Siemens, Bosch, SAP and Deutsche Telekom have positioned themselves, have entered into alliances and are offering Industry 4.0 offerings while developing demonstrators (Kohler C & C, 2015).

Countries do not hesitate to follow this movement because they see it as an opportunity to inspire new life into their countries, their regions, their cities. In addition, technological fertility with a large computational capacity and new generations increasingly "trendy", are the key ingredients to promote this digital transition since the Internet bubble.

From our point of view, Industry 4.0 will initially be a catch-up factory: the "pick and place" allows Japanese machines for several decades to load and unload cycle machines automatically. The same goes for robotic handling trucks transporting semi-products, from station to station, on less and less predefined routes. Until now, they had never convinced the French manufacturers while they have been working to the satisfaction of everyone in Japan for more than 20 years. This catch-up achieved, the factory will already have a more current "look" As for what will be in the future, probably an extension of the current breakthroughs in more industrial fields and more opportunities.

Therefore, calling Industry 4.0 a "revolution" represents an inconsistency with the first three revolutions, as it is simply a natural evolution of computer-integrated manufacturing (CIM). rather it is materialized by small steps that one could possibly call V.3.1, V.3.2, etc.

The industry evolution (adapted from Schrauf and Berttram, 2016)

Industry V.3.x or "Advanced Digitization", will target businesses moving towards the customer through e-commerce, digital marketing, social media and the customer experience. Ultimately, virtually every aspect of the business will be transformed by the vertical integration of R & D, production, marketing and sales and other internal operations, as well as new business models based on these advances. Indeed, we are moving towards the complete digital ecosystem.

But the reality is a bit more complicated

A study of the DZ Bank (sample of 1000 companies with a turnover between € 0.5 M and € 125 M) published in 2014, showed that 35% of Mittelstand companies thought that digitization was not very relevant compared to their value chain and another 14%, that it played a weak role.

How is this situation explained?

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    Cultural and Psychological Barriers: below, the many sources of uncertainty for business leaders that are hindering the introduction of Industry 4.0:

Obstacles perceived by business leaders in the deployment of Industry 4.0 (Kagermann et al., 2013)

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    Financial resources may be lacking for businesses to implement the digitized industry;
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    From a management stand point, there is a lack of global digital vision. Leaders struggle to perceive the potential of digitized industry and the associated ROI;
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    Today, the majority of companies are overwhelmed by the complexity of the "digital" theme and all the implications in the business;
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    Cybersecurity: for the German Academy of Technology (Acatech), there is no security solution efficiency, only those that exist are not used systematically. Although the threats are real in the application: infection of equipment with malware via office networks, insertion of malware by USB key or external hardware, illegal access by a remote maintenance network, deliberate sabotage or misbehavior , incitement to reveal personal data including passwords by phishing (fraudulent emails, phishing) and by "social engineering" (criminals take a false identity, for example in an email where they can present themselves as tax authorities or a human resources interlocutor).

Although clean techniques of Lean production systems are not yet in place in all the workshops of production sites, the "Smart Factory" with the very promising German label "Industry 4.0" is already making the show.


While the Toyota Production System (TPS) has been shown to be the most efficient production system, Industry 4.0 is still in a framing phase with the ambitious goal of becoming a cyber-production system. Partial and sometimes limited knowledge about Lean production systems leads to distorted ideas that both approaches are incompatible.

The implementation of a ferocious digitization without a management of the "just necessary" in a logic of change management would lead to waste in today's industry, where the machine-man continues to cohabit and will in the next decade. Certainly, the digitized industry will make the production system more flexible, but it is not certain that it will be faster, smoother, more stable and more accurate. Industry 3.X itself will materialize anyway, with or without this politico-economic initiative. In fact, digitization in the industry has been going on for a long time and is still going on.

Of course, it is the connection, the availability and the processing of the data that will make the difference in the future. Critical minds might even say that the 3.X industry is a self-fulfilling prophecy to a certain extent and will not meet the high expectations it raises.

We will see in a future publication the different types of technologies proposed by, let us be indulgent, the "4.0" and a brief definition of the TPM.

Sources :

Kagermann, H., Wahlster, W., & Helbig, J. (2013) Recommendations for implementing the strategic initiative Industrie 4.0 – Final report of the Industrie 4.0 Working Group. Frankfurt am Main: Communication Promoters Group of the Industry-Science Research Alliance, acatech.

Kohler C&C (2015). Industrie 4.0 : quelles stratégies numériques ? 1–67.

Lasi, H., Fettke, P., Kemper, H.-G., Feld, T., and Hoffman, M. n, “Industry 4.0,” Business & Information Systems Engineering, vol. 6, no. 4, p.239, 2014.

Nelles, J., Kuz, S., Mertens, A., and Schlick, C. M., “Human-centered design of assistance systems for production planning and control: The role of the human in industry 4.0,” in Industrial Technology (ICIT), 2016 IEEE International Conference on, pp. 2099–2104, IEEE, 2016.

Schrauf, S., Berttram, P. (2016). How digitization makes the supply chain more efficient, agile, and customer-focused.

Wahlster, W., “From industry 1.0 to industry 4.0: Towards the 4th industrial revolution,” in Forum Business meets Research, 2012.