Stochastic Optimization of Maintenance Expenditures in Industrial Facilities Subject to Equipment Reliability Constraints

Abstract

Maintenance planning in industrial facilities profoundly influences operating efficiency and cost-effectiveness. This study presents a stochastic optimization approach aimed at minimizing maintenance expenses while maintaining system dependability. We formulate a stochastic model using reliability constraints based on equipment failure distributions, addressing the probabilistic aspects of equipment deterioration and unforeseen failures. A genetic algorithm is used to address the resultant non-linear optimization issue. Findings from a simulated industrial plant model indicate a substantial decrease in maintenance expenses and enhanced equipment availability relative to conventional time-based maintenance approaches. This research offers a comprehensive decision-making instrument for industrial maintenance planning among uncertainty.