Integrating human factors into discrete event simulation: a proactive approach to simultaneously design for system performance and employees’ well being

The aim of this research is to: (1) Develop an approach to integrating both human fatigue-recovery patterns and human learning into Discrete Event Simulation models of a production system to predict productivity and quality; (2) Validate the predicted fatigue against operators’ perceived fatigue; and (3) Demonstrate how this Human Factors-enabled simulation approach can be applied in a case study comparing two manufacturing line designs in the context of electronics assembly. The new approach can predict the accumulation of operator fatigue, fatigue-related quality effects and productivity changes based on system design configurations. In the demonstration comparison, fatigue dosage was 7--33% lower in the proposed system where HF was taken into consideration at the engineering design (ED) stage. In the existing system, the fatigue dose measure correlated with quality deficits with 26% of the variance accounted for -- a large portion given the multi-causal nature of production deficits. ED models that do not include human aspects may provide unreliable results in terms of productivity and quality estimates. This research shows that it is possible to design production systems that are more productive while being less hazardous for the system operator.