Fuzzy decision support system for sustainable operational performance optimization for boiler unit in milk process industry

Abstract

This work proposes a new sustainable operational performance optimization-based decision support system for assessing the failure behaviour of the Boiler Unit (BU) in the milk process industry. A novel fuzzy Jaya Lambda–Tau Optimization (JLTO) approach-based modelling was established for tabulating various reliability indices of BU. Fuzzy Set (FS) theory-based concepts were applied to consider the vagueness/uncertainty involved in the collected data. JLTO approach-based results show decrease in the boiler unit’s availability with the increase in uncertainty level. Further, to improve the boiler unit’s availability using qualitative data obtained from expert’s opinion, Failure Mode and Effect Analysis (FMEA) was performed. To address the shortcomings of conventional FMEA approach-based results and to pinpoint the riskier failure causes contributing to decrease in system’s availability, Fuzzy-Complex Proportional Assessment (FCOPRAS) decision-making approach was integrated with FMEA approach. Fuzzy Combinative Distance-based Assessment (FCODAS) approach was also applied to compare the ranking results for accurate decision-making. The proposed integrated framework predicts the failure behaviour with high accuracy by considering the uncertainty and finding the riskier failure causes of the considered system which is one of the main drawbacks of existing FS theory-based integrated models. The proposed model-based results will help in developing an optimal digitalized maintenance schedule, which will be beneficial for improving the overall performance of the considered unit. The digitalized maintenance schedule will also be useful for BU of various other industries across the globe. Sensitivity analysis was also done for assessing the robustness of the proposed sustainable operational performance optimization-based decision support system.