Industry 4.0

Paradoxes and Conflicts

Jean-Claude André

• Publisher: Wiley-ISTE
• Year: 2019
• ISBN:
  9781119644637
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Electrical Engineering & Telecommunications
• Index: Technology & Engineering

Digital technology opens up extraordinary fields for applications that will deeply change the nature of jobs and trade, the very concept of work and the expectations of user–producers. The "masters of algorithms" have disrupted production and services, and this trend will continue for as long as electric energy and the elements of Industry 4.0 are in continued development. Beyond data control, a power struggle is working its way through the links in the value chain: intermediation, control of resources and command over human and physical networks, as well as partnerships, creativity and the political system. Industry 4.0: Paradoxes and Conflicts examines the need for a serious and technological review, as well as for research and training regarding citizenship and politics. This is a new situation in terms of relationships of competence and authority, which must be the subject of scientific as well as political reflections for the whole social body, which needs to be educated about choices. Throughout the book, the author poses the following question: instead of submitting to choices, would it not be better to exercise foresight?

1
Industry 4.0: Definition and the Acceleration of Innovations

“An innovation is therefore recognized by what it generates in terms of individual and collective uses, which are all the more numerous and varied because it is important […]. But we can also argue that the characteristic of true innovation is to restructure the real needs of Humanity by opening them to the possible, by definition totally unpredictable” (Ménissier 2011). These sentences obviously situate the concept of Industry 4.0 in the fields of innovation seen as a conjecture in advance of the real practice, likely to generate the relationships of individuals and their societies with the future. But one would have spoken of Industry 4.0, if in 30 years the price of a gigabyte had not been reduced by a factor of 3,000,000! If, in 20 years, we had not multiplied by 100 the number of people or companies connected to the Internet in the world (Quigley 2011; Bregman 2017)…

1.1. General framework

The concept of Industry 4.0 was quickly defined in the Preface to this reflection. Whether it is called “Industry 4.0”, as in Europe, the “Internet of Things” (IoT), as in the United States, or simply “Smart Manufacturing”, information and communication technologies (ICTs) are seriously reshaping modern manufacturing. Indeed, this digitization of manufacturing is likely to transform many of the industry’s production methods: the way in which products are sought to reach a market (design), and the way in which they are designed, manufactured and produced, distributed and consumed in relation to manufacturing supply/demand, possibly even individualized. The concept is part of a dynamic permitted by the unprecedented development of digital technology and the possibility of creating complex and sometimes truly customized objects (see Figure 1.1; André 2017).

Figure 1.1. Changes in manufacturing production patterns. For a color version of this figure, see www.iste.co.uk/andre/industry.zip

The manufacturing lines of Industry 4.0 include the following elements according to Chatilla (2017):

• – high-performance computing (HPC);
• – software tools for numerical modeling, simulation and design, including computer-aided software;
• – computer-aided design (CAD) and more generally computer-aided engineering;
• – artificial intelligence (AI) for innovation, training, expertise, health; trade (chatbots) (see Ezratty 2018);
• – computer-aided manufacturing and automation software packages, including systems that take advantage of generative technology in design techniques;
• – enterprise resource planning systems;
• – manufacturing execution systems and inventory management systems;
• – an additive manufacturing essential component, because it allows the physical production of complex parts locally from the digitization of the object to be produced;
• – robotics.

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Chatbots: A virtual agent is a computer program that is able to interact with a human user in real time. According to research conducted by Forrester Research (2018), 31% of the companies surveyed already use virtual agents. Very rudimentary in the mid-1960s (at MIT), they were considered one of the key components of the “self-service” business model, as they could reduce costs and speed up the resolution of concrete customer problems (see intelligent virtual assistants in the Preface).

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These different axes are shown in Figure 1.2 (Dario 2017) and Figure 1.3 (Tinant 2018) (see also WEF 2018a). There was a time when innovation was thought of as a vertical process (example of cars purchased up to the beginning of the 21st Century). This system did not take the end user into account very much (with just a few possibilities) at the time of purchase in time-consuming design. However, it is the end user who regulates or will regulate the life of companies today with their opinion as the starting point for a customized production operation, made agile and flexible. However, computerized media formats humans result in the channeling of their individual desires (Stiegler 2006). So, digital transformation technology allows a change in the customer–supplier relationship culture: is this permanent cooperation rather than contractual negotiation, with confident, lively and direct contact between company and user? But from which user?

Figure 1.2. Industry 4.0 (AM, additive manufacturing; IoT, Internet of Things). For a color version of this figure, see www.iste.co.uk/andre/industry.zip

Figure 1.3. Another presentation of Industry 4.0 broken down into its main components. For a color version of this figure, see www.iste.co.uk/andre/industry.zip

But from a practical point of view, the industrialists involved in the 4.0 adventure must move away from their design methods (“correct and create” principle), which for a long time have proved their worth. AI can be used for new methods based on the development of highly accurate dynamic models such as the “Digital twin” or “Double digital” (Goossens 2017).

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Digital twin: This is based on a simulation system that validates the achievement of the desired effects with correction possibilities, enabled today by the advent of powerful, easy-to-use mathematical tools for system modeling.

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The promises of Industry 4.0 must allow productivity gains, in particular for increasingly individualized manufacturing; among the expected technical progress, the following proposals are the subject of the prevailing discourses concerning the field:

• – a new generation of smart objects, which will allow customization by transforming manufacturing companies into service companies (the product is then only an element (a means) of market value, the data collected by the product, which can enrich databases (Big Data) to provide new offers);
• – exploitation of the immense potentialities of AI by going as far as autonomous systems;
• – implementation of a more innovative manufacturing ecosystem (alliances of digital technology and its simulation capabilities, ability to produce complex custom-made objects through additive manufacturing, open innovation, etc.);
• – supply-chain improvement through real-time factory connections, complete digital definition of products and processes; transfer from one factory to another;
• – proposal of an eco-efficient component of Industry 4.0 by reducing the use of materials and the energy used for manufacturing. Co-bots and augmented reality will increase workers’ efficiency. Industrial Big Data will reduce machine downtime (predictive maintenance) and the volume of waste produced.

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Co-bot: A co-bot, cobot or cooperative robot is a robot designed to produce a material transformation while physically interacting with humans in a shared workspace.

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In short, everything is good in Industry 4.0. However, what this test will attempt to show is that this wide space of promise is already being polluted, at least in part, by technical, scientific, environmental and organizational limitations with effects on operators and jobs in companies and more broadly on society a...