Special issue on ‘transdisciplinary approaches to digital manufacturing for industry 4.0’

The concept of Industry 4.0 (I4.0) outlines the vision of a smart factory characterised by the complete networking of all production parts and processes, consisting of real-time control via cyber-physical systems, increased use of robots, intelligent and adaptable production systems, which should contribute to greater productivity through resource efficiency. The convergence of production and interaction, work and communication requires increasingly transdisciplinary competencies for creating a smart factory, which is economically successful and competitive. These competencies consist, among others, of divers expert knowledge, flexibility, and creativity for moving toward I4.0. I4.0 is not just aboutmachines, but also about people. The Internet of things, data and services aremerging the physical and digital world. This is where people now move and work. Workers inside this new factory model are the bearers of this knowledge and the drivers of innovation.Modern factories should not only pay special attention to agile processes and sustainability but also to social and human aspects. They should support sustainable development, resource-efficient production systems, innovation and a successful economy, and active participatory and collaborative processes. They should also anticipate and counterbalance the impact of technologies on human beings and societies. Transdisciplinary Engineering (TE) is an emerging field that extends and evolves engineering approaches by transcending the technical disciplines. TE is an applied science field combining natural sciences, applied sciences, social sciences and humanities to achieve a higher level of comprehension and awareness of the context in which industrial products, processes, systems, and services will be implemented and experienced by users (Borsato et al. 2016). Research in TE also incorporates social science methodologies to acquire the necessary knowledge about users and context. TE is inherently aimed at solving ill-defined, socially relevant problems (Wognum et al. 2018). Many researchers have studied transdisciplinary processes and have tried to understand the essentials of transdisciplinarity. Numerous engineering problems can be characterised as ill-defined and socially relevant, too. Although transdisciplinary engineering cannot widely be found in the literature yet, a transdisciplinary approach is deemed relevant for many complex engineering problems. An overview of the literature on research into transdisciplinary processes and their relevance in engineering domains has been recently published (Wognum et al. 2019). Achieving an I4.0 environment is a complex problem. It is characterized by the need to create a vertical networking of smart production systems, such as smart factories and smart products, and the networking of smart logistics, production and marketing and smart services, with a strong needs-oriented, individualised and customer-specific production operation. In addition, strong horizontal integration by means of a new generation of global valuecreation networks is needed, including integration of business partners and customers, and new business and cooperation models across countries and continents. Moreover, I4.0 is founded on acceleration through advanced technologies that will transform the manufacturing production. More specifically, isolated, optimised machines and/or cells will be aligned in a network to achieve a fully integrated, automated, and optimised production flow, leading to greater efficiencies and changing traditional production relationships between suppliers, producers, and customers, as well as between human and machine. The practical goals of a transdisciplinary approach to the design of manufacturing systems in an I4.0 context are related to avoiding loss andmisuse in data exchange (Engelmann et al. 2018) and to achieve its potential benefits. IoTs and CPSs involve a high amount of data and information, but they have to be properly managed to improve human-machine interaction and properly monitored (Schmitt, Bettinger, and Rock 2018). They need to control the adaptive behaviours of both machines and interfaces (Beisheim, Kiesel, and Rudolph 2018). As a consequence, adopting a transdisciplinary INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING 2020, VOL. 33, NO. 4, 321–324 https://doi.org/10.1080/0951192X.2020.1752071