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    Maintenance Simulation and Optimization in Refineries and Process Plants

    Published: Jan 2013

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    This chapter outlines recent efforts to perform Monte Carlo simulation to obtain an assessment of the effect of existing corrective and preventive maintenance practices incorporating details of available labor, task assignment rules, and parts inventory on the plant economics. In addition, the use of a genetic algorithm in conjunction with the Monte Carlo simulation to obtain the economically optimal preventive maintenance frequency, the parts inventory policy (number and type of spare parts to keep in stock), and the labor allocation is presented. The performance of the algorithm is illustrated using the data of a fluid catalytic cracking plant.


    Preventive maintenance, corrective maintenance, genetic algorithms, optimization

    Author Information:

    Bagajewicz, Miguel
    University of Oklahoma, Norman, OK

    Committee/Subcommittee: D02.04

    DOI: 10.1520/MNL5820131213927