Simulation-based derived maintenance spares criticality assessment

Effective inventory control policies for maintenance spare parts necessitates criticality evaluation, which is predominantly done using historical data. This approach disregards uncertainty and risks like changes in reliability and failure rate that maintenance-intensive facilities experience. Therefore, incorporating these anticipated variabilities in the evaluation offers more appropriate and robust maintenance and inventory decision support. Moreover, an assessment considering the contribution of individual spares towards the whole system, based on the various criteria, offers a more comprehensive and accurate criticality analysis. A novel simulation-based spare parts criticality evaluation approach is proposed, integrating maintenance and spares policies of deteriorating multi-component system to derive the information quantifying the various criticality criteria. In addition to the conventional criticality criteria, this study considers the stochastic component dependencies propagating secondary failures (failure interactions) and the respective labour time incurred. Component degradation and dependencies are modelled while forecasting the various criticality criteria values, which are assigned weights based on indices derived through expert analysis. Ultimately the evaluation for each maintenance spare of the system, based on the aggregate criticality index is undertaken to offer a quantitative and robust criticality assignment. The applicability of the proposed approach was demonstrated through a case study evaluating the spare part criticality problem of a turbocharger subsystem in a thermal power plant.