The Next Level of Intelligent and Self-Optimizing Factories
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Industry 4.0+: The Next Level of Intelligent and Self-optimizing Factories Erwin Rauch(&) Free University of Bolzano, 1, Universitätsplatz, 39100 Bolzano, Italy [email protected] Abstract. For almost a decade now, production science has been dealing with Industry 4.0. In recent years, a large number of technological innovations have been developed and introduced into practice, enabling the implementation of smart and connected manufacturing systems. Over the next years, researchers and practitioners will face new challenges in Industry 4.0 to achieve the original vision of an intelligent and self-optimizing factory. We are currently at a crossroads between the first level of Industry 4.0, which was characterized by technologically driven innovations, and a future level of Industry 4.0+, which will be based on data-driven innovation. This article introduces these two phases of Industry 4.0 and gives a direction of research trends with growing attention in manufacturing science and practice. In the context of Industry 4.0+, two research directions, in particular, are expected to generate groundbreaking changes in production and its environment. This is, on the one hand, the introduction of Artificial Intelligence into manufacturing and on the other hand the use of nature as inspiration in the form of Biological Transformation. Keywords: Industry 4.0 Á Industry 5.0 Á Society 5.0 Á Intelligent manufacturing Á Self-optimization Á Artificial intelligence Á Biological transformation 1 Introduction Digital technologies are increasingly changing society. In the production sector, the term ‘Industry 4.0’ (I4.0) in particular introduced a new era of digitally networked production almost 10 years ago. The basic idea of Industry 4.0 was to be able to unfold the advantages through comprehensive connectivity on the shop floor as well as, by connecting products, machines, employees with the production system and with all those involved in the value chain, thereby minimizing information disruptions and the resulting inefficiencies by smart factories. To manage interconnected systems between physical assets and computational capabilities so-called cyber-physical systems (CPS) were introduced as transformative technologies leveraging the interconnectivity of machines. Since the proclamation of Industry 4.0 in 2011 at the Hannover Fair [1], a lot has happened in this direction. While Industry 4.0 was mainly limited to Germany in the first few years, almost all European countries have now launched Industry 4.0 initiatives. A look at scientific databases such as Scopus shows that since 2017 a large number of international publications have been added. Most of the larger companies © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020 V. Ivanov et al. (Eds.): DSMIE 2020, LNME, pp. 176–186, 2020. https://doi.org/10.1007/978-3-030-50794-7_18 Industry 4.0+ 177 have already started initiatives and pilot projects to introduce new technologies related to Industry 4.0 in production as well as logistics. Many of the small and medium-sized companies (SME) do not yet have such a smart and connected manufacturing system, but will be able to achieve this goal in the medium-term as results from research are already transferred into broader industrial practice [2]. The next groundbreaking level to be achieved, are intelligent and self-optimizing manufacturing systems. While a smart factory can be understood as a manufacturing system, which is capable to apply previously acquired knowledge an intelligent factory may be seen as a factory, which can autonomously acquire new knowledge and apply it for self-optimization purposes. To achieve this goal the results from the first era of Industry 4.0 play, an important role as connectivity and modern technologies are a prerequisite for the next level of Industry 4.0 called ‘Industry 4.0+’ in this article. Currently, several authors are speaking also about Industry 5.0 [3, 4] although it might be seen more like the second level of Industry 4.0 with a final vision of an intelligent and self-learning and self-optimizing factory. Based on the results of the first level, production resources can collect a large amount of high-quality data using sensors, vertical and horizontal data integration guarantees seamless data exchanges, a large amount of big data can be stored and managed via cloud technologies and be processed into more structured data with big data technologies. The next level of Industry 4.0+ is aimed at taking advantage of this data creating intelligent and self-optimizing factories, whereby we are already still far away from this vision. It is important to look for new and innovative solutions to how this new level of data quantity and quality can be utilized in companies for self-monitoring and intelligent self-optimization of the manufacturing system. Artificial intelligence (AI) and biological transformation in manufacturing may open up completely new possibilities in this direction. Although the theoretical basis of AI and approaches of bio-inspired manufacturing existed already years ago, now is the right time to take full advantage of these concepts as large amounts of data are available in factories and computational capabilities increased significantly in the last years. This article introduces the concept of implementing Industry 4.0 on two levels, a first technology-driven level, and a second data-driven level. In this visionary look in the future, the author gives an outlook on how to achieve the vision of intelligent and self-optimizing factories of the future with Industry 4.0+. To reach this vision researchers and practitioners will need to deal with artificial intelligence and the concept of biological transformation, which will most probably dominate research in manufacturing in the next decade. 2 Literature Review 2.1 Industry 4.0 – The Fourth Industrial Revolution Industry 4.0 is the umbrella term for the Fourth Industrial Revolution, which has particularly occupied scientists in production engineering over the past almost 10 years. The term was presented for the first time at the Hannover Messe 2011 by German scientists (Acatech - National Academy of Science and Engineering), who wanted to 178 E. Rauch sensitize the public and policymaker to a new high-tech strategy for Germany. In the following two years, a working group was set up in Germany to develop recommen- dations for the implementation of Industry 4.0. In 2013, the final report “Recom- mendations for implementing the strategic initiative INDUSTRIE 4.0” was presented to the public [1]. In the following years, mainly from 2014 to 2016, most of the European countries launched national initiatives and funding programs to roll out Industry 4.0. To name just a few, these are the “Piano Nazionale di Industria 4.0” in Italy [5], “Smart Industry - a strategy for new industrialization for Sweden” in Sweden [6], “Industrie 4.0 Österreich” in Austria [7]or“Industria Conectada 4.0” in Spain [8]. According to a keyword search for “Industry 4.0” (selecting only non-European countries) mainly since 2017, Industry 4.0 has also achieved significant status as a term on an international level. Especially in Asia, the term Industry 4.0 is widespread. Thailand with the initiative “Thailand 4.0” [9]or“Made in India” [10] can be men- tioned here as an example. In the North American region (USA and Canada) the concepts of Industry 4.0 are often known under the terms “Internet of Things” (IoT), Smart Manufacturing or Intelligent Manufacturing [11]. If we look back to the beginnings of Industry 4.0, what were the challenging goals for this new Fourth Industrial Revolution back then? The final report of Kagermann et al. [1] may be used as one of the first documents on Industry 4.0. Industry 4.0 is the Fourth Industrial Revolution after three previous revolutions. After mechanization at the end of the 18th century (1st Industrial Revolution) and electrification at the beginning of the 20th century (2nd Industrial Revolution), computer technology, electronics, and automation were introduced at the beginning of the 1970s (3rd Industrial Revolution). The Fourth Industrial Revolution is characterized by the aim to connect machines, people, products, and the entire value network by vertical and horizontal data integration to create smart and connected factories. According to [1] “smart factories constitute a key feature of Industry 4.0 being capable of managing complexity, being less prone to disruption and able to manufacture goods more efficiently”. In the widest vision of Industry 4.0, smart factories become intelligent factories. They will lead to the emergence of dynamic, real-time optimized, self-organizing manufacturing systems with production facilities that are autonomous, capable of controlling themselves in response to different situations, self-configuring, self- regulating, self-aware and self-optimizing [1, 12]. In such intelligent factories, employees will be freed up from having to perform routine tasks, enabling them to focus on creative, value-added activities. They will thus retain a key role, particularly in terms of supervision and quality assurance [1]. A smart factory enables rapid and flexible adaptation or reconfigurability through connected machines able to get data as well as to offer information to other elements in the manufacturing system (e.g. people, products). Intelligent factories can think, learn, remember and in a given moment share that amount of knowledge, or react in certain situations [13]. Intelligent manufacturing systems are highly automated at the manufacturing level and are self-repairing, self- optimizing and self-configuring by taking advantage of AI and neural networks tech- nology [14]. Industry 4.0+ 179 2.2 Industry 5.0 – Is this the Next Industrial Revolution? After about 10 years of industry 4.0 and ever shorter innovation cycles in a highly dynamic environment, many scientists are naturally asking and looking for the next big hype in production science.