A Multi-Objective Optimization Approach for Smart Preventive Maintenance in High-Speed Presses Using MOPSO and Real-Time Reliability Analysis
نویسندگان
1 Phd student in Industrial Management, Rudehen Branch, Islamic Azad University, Rudehen, Iran
2 Department of Industrial Management, Nowshahr Branch, Islamic Azad University, Nowshahr, Iran
3 Department of Industrial Management, West Tehran Branch, Islamic Azad University, Tehran, Iran
4 Department of Industrial Management, Firozkoh Branch, Islamic Azad University, Firozkoh, Iran
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چکیده
High-speed presses are critical in modern manufacturing but face challenges due to wear and unplanned downtime. This study introduces an innovative multi-objective framework integrating Multi-Objective Particle Swarm Optimization (MOPSO) with real-time reliability monitoring for preventive maintenance and repair scheduling. The model increases system reliability and minimizes total system costsover a defined operational horizon. It leverages Weibull reliability modeling to predict degradation and incorporates IoT-enabled data for dynamic updates. Decision variables, including preventive maintenance intervals and actions, are optimized while adhering to reliability thresholds. The proposed approach balances the trade-offs between frequent, costly preventive actions and higher risks of failure. A practical case study on a high-speed press demonstrates the framework's effectiveness, yielding a Pareto-optimal set of solutions that guide maintenance strategies. This research provides manufacturers with a flexible, data-driven tool to enhance uptime, reduce costs, and maintain operational excellence in competitive industrial environments.
