Download PDFOpen PDF in browserYearly Plant Maintenance Budget Evaluation: A Simulation ApproachEasyChair Preprint 48886 pages•Date: January 11, 2021AbstractThe main objective of any production unit is profit. It can be achieved by minimizing the maintenance cost without compromising on the lower bound reliability and availability. Maintenance budget markedly impacts maintenance costs so it is crucial to appropriately assess it for an organization to maintain their competitiveness. Precise estimation of maintenance budget is necessary to initiate and complete the maintenance activity as desired. The existing methodologies of budget estimation are all non-scientific and based on plant specific values of budget influencing parameters and contextual in nature. This work attempts to resolve this. Maintenance parameters affect the maintenance budget and this depends upon the level of identified maintenance parameters. In this paper, different maintenance scenarios are described. Monte Carlo simulations are deployed to evaluate steady state value of maintenance budget by assigning random values to the budget parameters within specified range corresponding to a chosen maintenance scenario. Mat Lab code is deployed for its implementation. Descriptive analysis is carried out on yearly maintenance budget data generated by Monte Carlo simulation for all identified maintenance scenarios. Descriptive tools such as histogram, box and whisker plot, central tendency and dispersion measures are employed to organize and describe the characteristics of maintenance budget data. The results are validated by comparing it with world class and best practices values reported in the literature. The study shows that maintenance parameters have significant effect on the plant maintenance budget. It is, therefore necessary to take corrective measures on the budget parameters, if the values of these drop below certain levels. This study will avoid using historic data or subjective expert judgments in selection of maintenance budget. Keyphrases: Descriptive Analysis, Maintenance Management, Maintenance budget, Monte Carlo simulation
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