Human Robot Collaboration: an assessment and optimization methodology based on dynamic data exchange

Abstract

When talking about Human Robot Collaboration (HRC), Industry 4.0 leverages on the central role of workers that needs to be assessed over multiple dimensions, including ergonomics, costs, productivity and time performance measures. The aim of this research work is to develop a reference methodological approach to enable a holistic HRC assessment and optimization by considering several assessment parameters. Due to the wide complexity of the topic, the authors propose a simulation-based Digital Twin (DT) approach in order to recreate, with satisfactory accuracy, the real workplace in a simulated environment. Regular update of the DT is foreseen both under a static as well as dynamic (by using a set of multiple sensors) way thus enabling DT capability. Ergonomics, costs and performance assessment methods are seamlessly integrated within the simulation environment thus providing a comprehensive setting for sustainable HRC testing based on holistic assessment of different issues. Moreover, the authors present an infrastructure for the implementation of the proposed approach as well as go into the details of the dynamic data exchange between the workplace and the DT by proposing a data acquisition architecture.