Intuitionistic fuzzy modelling-based integrated framework for performance analysis of juice clarification unit

Abstract

The current work seeks to propose an Intuitionistic Fuzzy (IF) modelling based integrated framework for analysing the performance issues of a Juice Clarification Unit (JCU) in a sugar mill industry. IF-Lambda Tau approach based mathematical modelling has been developed using AND/OR gate transitions expression for both membership and non-membership functions. Membership and non-membership function-based reliability parameters have been tabulated at different spreads. Availability of the considered system shows decreasing trend with the increase in spread values. Furthermore, for improving the system’s availability, risk analysis has been carried by implementing IF-Failure Mode & Effect analysis (IF-FMEA) approach. IF Hybrid Weighted Euclidean Distance (IFHWED) based IF-FMEA output scores for all listed failure causes has been tabulated for identifying the most critical failure causes responsible for decrease in system’s availability. IF-Technique for Order of Preference by Similarity to Ideal Solution (IF-TOPSIS) approach was also applied within IF-FMEA approach, and the obtained ranking results are compared for effective decision making of critical failure causes. The proposed IF modelling based integrated framework is highly capable in considering the indeterminacy/hesitation effect involved in the collected raw data/information beside the presence of vagueness/fuzziness, which is missing with the well existed fuzzy set theory based models. The capability of considering the indeterminacy/ hesitation effect in the raw data/information with proposed model results in high accuracy in the performance evaluation of the considered system, and will be further useful for developing an optimum maintenance schedule. Sensitivity analysis has also been carried out to evaluate the robustness of proposed integrated framework.