Failure mode effects and criticality analysis (FMECA) using fuzzy logic for ship dynamic positioning (DP) systems

Predicting the failure modes effect and criticality analysis (FMECA) of a dynamic positioning (DP) system using fuzzy logic is aim this research. The identification DP systems subsystems, classification into critical less-critical levels based on Risk Priority Number (RPN) to depict main root causes in are some objectives support goal. offers details number issues, including their effects functionality dependability equipment. Based information provided, it was determined that produced identical RPN values, ranking scale erroneous. A new method tested but could not really prioritize with same because few choices severity, occurrence detection template. To compensate for this, excel function employed putting as key criteria ranking. Due high severity index, results show faulty component identified scenario SSTs (F1) categorized very critical. SSCs (F12), SSPr (F7), SSTs(F2), SSPs(F15) additional failures. In study, data validation were done rule MATLAB. From findings, can be inferred F1, F2, F5, F6, F7, F8, F10, F11, F15 have values similar type RPN. According initial risk level results; there 19 medium level, 2 low 1 level. final RPN-based results, 18 scenarios 4 contrast, 5 17 Without logic, justification score traditional FMECA given directly. This makes ABS greater than FMECA. highest treated parts, so recommended value special attention by making necessary repairs or replacements order lengthen equipment's lifespan.