Mental workload: a prerequisite for future maintenance design

Abstract

The European Agency for Safety and Health at Work (2010) states that 15-20% of workplace accidents are maintenance-related, and 10-15% of these incidents result in fatalities. Due to the specialized expertise and knowledge required for this task, maintenance activities induce significant occupational stress (Sugiharto, 2019). Recognizing the necessity of evaluating physical workload becomes imperative for enhancing performance and working conditions, aiming at effective anthropocentric design (Bernard et al., 2021). However, this is not the only workload that operators experience. Mental workload can adversely affect maintenance activities, potentially leading to human errors and posing serious threats to complex system safety. The succession of maintenance tasks, whether simple or complex, demands mental resources such as decision-making, memory, and attention. The link between physical and mental workload exists within the activity, the individual and the surrounding environment with which he interacts (Causse, 2010). Taking into account Human Factors & Ergonomics (HFE) during the design cycle allows for the anticipation and optimization of interactions between operators and system components in terms of maintainability. Poorly executed studies on intrinsic or extrinsic equipment maintainability can generate human errors, which can affect performance and the safety of operators and systems. For this reason, anticipating the assessment of these dimensions makes collaboration with the design office more effective, so that HFE recommendations can be better taken into account during the design cycle. To this end, simulating maintenance tasks in an immersive environment, utilizing digital simulation tools (Virtual Reality, Augmented Reality, Mixed Reality), and physical simulation (mock-up), encourages the exploration of the relationship between the user and the maintenance environment. However, in the field of maintainability, it seems that no certified method for measuring mental workload has yet been established. Multiple categories of measures exist to assess mental workload: subjective measures, objective measures of performance and physiological measures. Some categories provide a singular perspective on mental workload, while others offer a more detailed understanding of its dynamics (Cegarra & Chevalier, 2008). Optimizing the selection of mental workload measurement methods and associated tools requires consideration of the constraints of the maintenance activity. The combination of measurement methods is fundamental to understanding the origin, variations, and limitations of mental workload, ensuring a holistic understanding of participants' cognitive activities and facilitating interpretation.