Life Cost-Based FMEA Using Empirical Data

Failure Mode and Effect Analysis (FMEA) is a design tool that helps designers identify risks. The traditional FMEA involves ambiguity with the definition of risk priority number: the product of occurrence, detection difficulty, and severity subjectively measured in a 1 to 10 range. Life-cost Based FMEA alleviates this ambiguity by using the estimated cost of failures. Yet, the methods still relies on judgment of experts in determining variables such as frequency, detection time, fixing time, delay time, and parts cost. To resolve this subjectivity, this paper proposes a systematic use of empirical data for applying life-cost-based FMEA. A case study of a large scale particle accelerator shows the advantages of the proposed approach in predicting life cycle failure cost, measuring risk and planning preventive, scheduled maintenance and ultimately improving up-time.