Analyzing resilient attention management of expert operators using functional resonance analysis method

Abstract

Manufacturing worksites have developed to have a socio-technical aspect with complex interactions between human operators, automated machines, and the environment. The operators must adapt to and cope with daily performance variabilities in these socio-technical systems to maintain resilient productions. However, more than conventional methods are needed to clarify the operators’ adaptive aspects that interactive factors play a critical role. This study investigates attention management in multitasking as one crucial aspect of the adaptive behavior of manual operations in actual manufacturing worksites. The framework considering the functional structure of tacit knowledge was employed for this purpose. Data from a case study focusing on multitasking in steel plate processing was utilized. First, we extracted the attention characteristics with eye movement and interview analysis regarding the proximal and distal terms of tacit knowledge. Then, we took a model constructive approach using work domain analysis (WDA) and functional resonance analysis method (FRAM). The results showed that the expert operator could maintain the systematic attention strategy even when multitasking. Furthermore, the simulation results showed that extracted experts’ attention strategy contributed to the resilient work performance. The current study confirmed that the framework based on FRAM could investigate the adaptive nature of expert skills in socio-technical systems.