With the introduction of Industry 4.0, occupational health and safety finds itself confronted with new types of hazards. Many Industry 4.0 innovations involve increased machine intelligence. These properties make socio-technical work in Industry 4.0 applications inherently more complex. At the same time, system failure can become more opaque to its users. This paper reviews and assesses safety analysis methods as the breakdown of interaction coupling in socio-technical systems on the one hand, and the degree of failure tractability on the other hand; the latter being used as a proxy for complexity. Previous literature confirms that traditional health and safety risk assessment methods are unable or are ‘ill-equipped’ to deal with these system properties. This paper studies the need to introduce new paradigms and safety methods related to complexity thinking with theories borrowed from the study of complex adaptive systems, all to assess the arena of abruptly changing hazards introduced by Industry 4.0. At the same time, this review makes clear that there is no one-solution-fits-all method. Occupational health and safety (OHS) covers many different hazard types and will need a combination of old, new and yet-to-be-developed safety assessment methods.
Collaborative human–machine interaction will be progressively intensified in industrial applications. The aim of this article is to examine current approaches to cobot safety by showing that these approaches can additionally benefit from systems thinking methods. The first part of this article covers a narrative literature review on predominantly techno‐centric robot safety approaches, with a strong focus on containing kinetic energy and ensuring separation with humans. The second part introduces systems thinking methods to analyze a socio‐technical perspective on cobot safety, including joint cognitive systems and distributed cognition perspectives. This explorative research dimension is expected to overcome an overly narrow interpretation of safety issues, anticipating the challenges ahead in ever more complex cobot applications. This article embraces a socio‐technical perspective to explore the potential of Joint Cognitive Systems to manage risk and safety in cobot applications. Three systemic safety analysis approaches are presented and tested with a demonstrator case study concerning their feasibility for cobot applications: System‐Theoretic Accident Model and Processes (STAMP); Functional Resonance Analysis Method (FRAM); and Event Analysis of Systemic Teamwork (EAST). These methods each provide interesting extensions to complement the traditional understanding of risk as required by current and future industrial cobot implementations. The power of systemic methods for safer and more efficient cobot operations lies in revealing the distributed and emergent result from joint actions and overcoming the reductionist view from individual failures or single agent responsibilities. The safe operation of cobot applications can only be achieved through alignment of design, training, and operation of such applications.
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