Optimal Preventive Maintenance Planning Considering Human Error: A Cost-Effective Approach

Abstract

Proper preventive maintenance (PM) not only reduces equipment failure costs but also effectively minimizes direct operational expenses. The optimal planning of PM operations plays a crucial role in reducing equipment damage and enhancing organizational efficiency. Human error is a decisive factor in maintenance operations but is often overlooked in achieving optimal maintenance implementation. In this paper, a novel mathematical model aimed at minimizing maintenance-related costs is proposed. This model investigates the impact of human errors on the effective rate of equipment aging and maintenance costs. The results obtained from the proposed model provide valuable insights for decision-makers, enabling them to implement maintenance operations that are optimal by reducing costs and human errors. To validate the developed model, real-world testing is conducted, and its effectiveness is assessed using a sensitivity analysis. The sensitivity analysis is performed on the Weibull distribution parameters and the length of each maintenance period. The research findings indicate that the optimal human error, based on its associated costs, is determined to be 0.020. This finding encourages decision-makers to reduce the human error probability to 0.020 to achieve cost savings.