MAINTENANCE STRATEGY SELECTION

Abstract

This report presents design and development of an intelligent decision support module for selecting the optimum maintenance strategy in a process type industry. The evaluation of different maintenance strategies (such as reliability centered maintenance (RCM), total productive maintenance (TPM), preventive maintenance (PM), Condition based maintenance (CBM) etc.) has been carried out using fuzzy logic technique. The proposed model provides a decision analysis capability that is often missing in existing CMMS's. The performance of the worst fifteen machines is identified according to four essential maintenance criteria such as Frequency, Downtime, Spare part cost and maintenance cost. These criteria were selected based on their importance and past experiences by analytical hierarchy process (AHP) technique. Computations were performed using these criteria as inputs in fuzzy logic toolbox in MATLAB software and accordingly output has been evaluated. The main practical implication of this report is the proposal of an intelligent model that can be linked to CMMS's to add value to data collected in the form of provision of decision support capabilities. A user-friendly decision support module has been developed, which can take the above mentioned criteria as Inputs and directly show the output i.e. the optimum maintenance strategy. Further, results are discussed and future work has been outlined