Abstract
In this article, we use a genetic algorithm to obtain an economically optimal preventive maintenance frequency for different equipment, the parts inventory policy (number and type of spare parts to keep in stock), and labor allocation in process plants. To assess cost, we improved a previously published Monte Carlo simulation-based maintenance model (Nguyen et al. Ind. Eng. Chem. Res. 2008, 47(6), 1910−1924). Two examples, a Tennessee Eastman example and a fluid catalytic cracking unit in a refinery, are provided.
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