Efficient Fine Tuned Trapezoidal Fuzzy-Based Model for Failure Mode Effect Analysis Risk Prioritization

Abstract

Many industries struggle with different project failures including Enterprise Resource Planning (ERP) implementations projects which has high failure rates too. Failure Mode Effect Analysis (FMEA) is an extensively utilized to analyze failure modes in risk assessment in various industry projects including ERP implementation projects. Nevertheless, in the traditional FMEA system, ignoring the Interdependencies among various failure modes as well as the relative importance of risk and non-injective and non-subjective nature of conventional RPN functions leads to challenges in analysing and assessing the risk. This may mislead in the addressing the prioritization of the Risk. Therefore, an efficient FMEA framework is proposed using Fine Tuned Trapezoidal Fuzzy-based Technique for Order of Preference by Similarity to Ideal Solution (FTTF-TOPSIS). The developed FMEA framework focuses to avoid data complications while preparing or collecting the data by using a hierarchical matrix management for data preparation. Uncertain risk, cost, and relative dependency are considered as additional parameters regarded by the work to calculate RPN. Mathematical models such as conservative method together with the Square Root Kragten Method (SRKM) are used to find the relative dependency along with uncertain risks. Thereafter, a highly reasonable along with credible outcome to rank the risk, FTTF-TOPSIS is employed. Finally, to demonstrate the proposed method's efficiency together with benefits, a comparation is made with the other models.