Incorporating human factors-related performance variation in optimizing a serial system

Abstract

Work-related health problems cause an operator to be in different health-states and to have different performance levels in terms of productivity and the number of defective items produced. Human factors studies usually investigate workplace risk factors to reduce the negative effects of occupational health problems. However, they rarely optimize the performance of operation systems. To this end, this paper presents an analytical modeling framework integrating human factor aspects (workplace risk factors) into a serial assembly system performance optimization model. First, a health-state Markov chain is developed to model an employee’s work-related health conditions, which varies due to workplace risk factor exposure levels. Then, the total cost of the assembly system is minimized with respect to incorporating operational and financial consequences of the work-related health-states with other features of the system such as customer demand, inventory capacity and production costs. Ultimately, this study compares the optimum total cost of the system with and without including human factors. The results of numerical analysis show that the total cost increases from 0.1 percent to 32 percent in the presence of different workplace risk factors. This research opens a new window to considering a human factors (ergonomic) intervention not only as an occupational health and safety solution, but also as an operation improvement method leading to the design of safer and more efficient systems. Managers may also take the advantages of this study by having more opportunities to better deal with production variations via improving workplace ergonomic conditions.