Performance analysis of "Injection Moulding Machine" under fuzzy environment through contemporary arithmetic operations on right triangular generalized fuzzy numbers (RTrGFN).

This article focuses on the performance analysis of a conventional repairable industrial system, specifically an Injection Moulding Machine, under uncertain conditions using a fuzzy environment. It introduces the Right Triangular Generalized Fuzzy Number (RTrGFN) membership function and applies the lambda-tau methodology combined with fuzzy arithmetic operations to evaluate key reliability parameters such as failure rate, repair time, Mean Time To Failure (MTTF), Mean Time To Repair (MTTR), Mean Time Between Failures (MTBF), availability, reliability, and Expected Number of Failures (ENOF). Real maintenance data from an Injection Moulding Machine at Polyplastics Company in Haryana, India, is used to validate the approach, addressing uncertainties caused by incomplete records and human errors. The study demonstrates that the proposed fuzzy-based methodology provides a practical and flexible framework for reliability assessment, aiding maintenance planning with an emphasis on an 80% confidence level for decision-making. Future research directions include extending this approach to other industrial systems and developing new membership functions for enhanced performance prediction.