Background

The first industrial revolution involved the appropriation of water and steam power for mechanization. It was followed by the second industrial revolution, which used electric power for mass production, and by the third industrial revolution, which introduced electronics and information technology (Schwab 2017). The vision of interconnected small computers, which (Weiser 1991) described in the early 90s as Ubiquitous Computing, coupled with the penetration of the internet as well as the miniaturization of computers and electronic assemblies is now commonly known as the Internet of Things (IoT). How IoT technology influences industrial contexts (e.g. manufacturing processes and tools) is commonly described as “the fourth industrial revolution (Industry 4.0)” or Industrial Internet of Things. It encompasses an interconnected mix of physical hardware and digital software spheres. This revolution is characterized by an increasingly complex connection between semi-autonomous machines, materials, locations, and companies that is enabled by advances in information technology.

The first three revolutions had far-reaching effects on cooperation relationships, division of labor, coordination processes and power relations within companies. Many experts assume that the current upheaval and interwoven connection will have, again, far-reaching effects not only on the actual manufacturing and applied production goods, but also on the internal organization of and external cooperation between companies. Developments such as autonomous, connected, and ubiquitous cyber-physical systems (CPS) and the connection of data-, technology- and process-driven manufacturing will shift human-technology interaction as well as cooperation processes.

This context gives CSCW researchers an occasion to observe workplaces where technology is embedded in a different way as before this fourth industrial revolution. Indeed, the industry of the future is an information system of great complexity that produces a large amount of digital data. In order to be useful, these data must be treated in an “intelligent” way. The success of the new forms of empowerment, claimed by the advocates of this new form of organization, also qualified as “data-centric”, depends on the ability of the organization to deploy the computer-based system that allows this intelligent treatment. In fact, this deployment issue is addressed by researchers interested in the factories of the future; they have raised concerns and solved issues from a technical and economical point of view (Brettel et al. 2014; Petrick and Simpson 2013). However, the social and human dimensions have been neglected so far, but early CSCW research has already shown its importance when focusing on supportive technology at the shopfloor (P. Carstensen et al. 1999; P. H. Carstensen and Schmidt 2002). When designing the industry of the future, the shopfloor cannot be reduced to its technological artifacts or its computer-based part (Schmidt 1991). Moreover, most economic and political players are aware of the importance of human and social factors in the successful development of Industry 4.0 (Kassner et al. 2017). Nevertheless, the understanding of the latter has so far been the subject of little research during the discussion about new shopfloor systems.

Yet, the vision of the fourth industrial revolution is not replacing humans in production, but instead enabling a paradigm shift in human-technology interaction and how we cooperate with humans (Ludwig et al. 2018). This means that, although modern technologies will indeed bring a great deal of automatization to industry, they will always work together with workers for the accomplishment of productive outcomes in effective and efficient ways. Put it another way, in this fourth industrial revolution, it – this is the hope – “will be [the] machines that adapt to the needs of human beings and not vice versa” (Henning et al. 2013). Even though modern technology and machines offer new possibilities and functionalities that have come along with (and will continue to come along with) the interest in the IoT, they will also increase the complexity of the practices associated with the ecologies of technology they encompass (Ludwig et al. 2017, 2018; Schmidt 1993). This will be a result of: (a) increasingly complex devices; (b) an increasing number of less obvious connections and dependencies between IoT devices and things; (c) more and more changes that ensembles of IoT technologies will need to undergo in order to fully integrate the most recent technological options and advances; and (d) a new interweaving of the ‘digital’ and the ‘physical’ world (Ludwig et al. 2019; Sheridan 2016).

Although new technologies are gaining more and more influence in industry, its appropriation and its role in the emergence and the transformation of practice are still vague. Some transformations might fail because they focus on the deployment of a technological artifact instead of being the result of a negotiation process between technical artifacts, social dynamics and physical places (Lewkowicz and Liron, 2019). Companies often rely on the important and historically grown employee-related expertise (Brödner 1986; Wurhofer et al. 2018). Employees and their “work capacity” have been ensuring the economic success within most companies since several decades. As production in Europe needs to cope with technological change and social change, it is justified to regard particularly the “smart factories” as socio-technical systems and to understand the role of the “operator 4.0” within this evolving environment, the “human cyber-physical production system” (Romero et al. 2016). Adopting a practice lens (Kuutti and Bannon 2014) seems a way to ensure a negotiation of the intended practice together with a local adaptation of the CPS.

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