Maintenance policy optimization for buffered serial systems considering energy-saving based on dual time windows

Abstract

This paper proposes a novel optimal maintenance policy considering energy-saving based on dual time windows is proposed for a serial production system with limited buffering. The machines suffer from degradation, and the degradation process obeys the Gamma random process. Based on the dual time windows, condition-based preventive maintenance and opportunistic maintenance are activated: when a machine reaches a set state (i.e., threshold deterioration state), the preventive maintenance action is taken, and the time of preventive maintenance performed is determined by the time window w; meanwhile, the time window W is used to determine whether the other machines need opportunity maintenance. To reduce energy consumption, and increase the proportion of effective energy in the manufacturing process, the energy-saving time window is used to find the energy-saving opportunities for the system. The impact of different maintenance thresholds and dual time windows on the maintenance cost per effective product is discussed through Monte Carlo simulation. A practical example of an automotive manufacturing system is provided, and comparative analyses with other maintenance policies are used to illustrate the superiority of the proposed policy in energy saving, cost reduction, and quality improvement.