OPTIMAL PREVENTIVE MAINTENANCE SCHEDULING IN PROCESS PLANTS Jeffrey D. Sorenson, LaRisa Sergent and Miguel Bagajewicz EXECUTIVE SUMMARY This work expands upon the previous work of Nguyen et al. which developed a new methodology for assessing the effectiveness of preventative maintenance scheduling guidelines on a small chemical processing plant. Here, the model is applied to larger processing plant – the FCC unit of a large refinery – and expanded to consider risk analysis. Effectively scheduled preventative maintenance has the potential to reduce production losses and maintenance costs, making it a matter worthy of great study and evaluation by process companies. Using a time horizon of ten years, Monte Carlo simulations are used to determine the optimal labor force for each process. Setting labor constant, Monte Carlo simulations were then used to evaluate preventative maintenance (PM) intervals for equipment by providing cost probabilities and average total cost. Optimization by setting different PM intervals for each equipment group
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