A Decision-Making Framework for Optimal Maintenance Management : An Integrated Simulation- Mathematical Programming- Expert System Approach

This study presents an integrated simulation- mathematical programming-expert system approach to develop an optimal solution for maintenance management in a complex public infrastructure system. First, a model of maintenance system is made through a computerized simulation with respect to the collected data on maintenance actions and unexpected failures. Then, the Taguchi method is adopted to develop different scenarios. For each scenario, a precise measurement of cost and reliability based on customer dissatisfaction rate (i.e. modified reliability) is calculated. Regression is applied to observe the association of components’ maintenance workload with cost and modified- reliability. Then, the preferred solution for maintenance management is achieved by developing a mathematical model, with the aim of reliability and cost improvement. Finally, after identifying the most significant components in terms of cost and reliability by sensitivity analysis, the maintenance actions taken during the program are determined using an expert system. Results demonstrated that the optimization model Outdo Taguchi scenarios achieved the optimum one as it met both targets, simultaneously. Having determined the significant components of the system and enhanced the methodology by signaling maintenance specialists, it can be especially helpful in assisting administrators in lowering the accident rate arising from the shortcomings in maintenance plans