Working Situation Health Monitoring: Proposal of Method and Case Study

Abstract

In a working situation on an automated assembly machine, technical drifts during operation can lead to machine dysfunctions. These dysfunctions may cause the operator supervising the machine to adapt and respond to reduce the effect of these technical drifts on the rest of the working situation. To respond to these dysfunctions the operator may expose him or herself to hazards and thus be in a hazardous situation. (Lamy & Perrin, 2020) showed the feasibility of identifying this kind of potentially hazardous situation by observing the working situation. Here, we propose a method called Working Situation Health Monitoring (WSHM). The goal of this method is to identify these potentially hazardous situations by analyzing the potential drift of working situations and monitor the advent of potentially hazardous situations using equipment and production data. It consists of three steps: firstly, we model the working situation studied to characterize the nominal working situation; secondly, we analyze cause-and-effect relationships between potential process drifts, potential operator responses and potentially hazardous situations; and thirdly, we construct a health indicator of the working situation based on knowledge of potentially hazardous situations identified in the second step and by equipment data. This paper also presents the application of the method to a case study (an educational automated assembly machine).