Systems-theoretic interdependence analysis in robot-assisted warehouse management

Abstract

The safe and efficient application of collaborative robots requires an understanding of actual work practices transformation, emerging from the adoption of new technological instruments. Functional systems-thinking is largely absent in literature about collaborative robot applications. In this context, this study proposes a framework that combines two safety analysis methods, being the Functional Resonance Analysis Method and Interdependence Analysis. Both safety and efficiency are examined by selected case study highlights to gain an in-depth understanding of human operators’ role as the central driver of human–machine (eco)systems in a warehouse distribution system, in which warehouse robot assistance is provided. Whereas the Functional Resonance Analysis Method first maps the work system interactions as a whole, Interdependence Analysis is subsequently applied to investigate individual inter-agent exchanges by the principles of Observability, Predictability, and Directability as a core principle for goal coordination between multiple agents, including warehouse robot agents. The case study examples reveal the combined effects of the working system environment and the robot application but also demonstrate possible operational solutions to deal with socio-technical complexity.