Life Cost-Based FMEA Incorporating Data Uncertainty

Abstract

Failure Modes and Effects Analysis (FMEA) is a design tool that mitigates risks during the design phase before they occur. Although many industries use the current FMEA technique, it has many limitations and problems. Risk is measured in terms of Risk Priority Number (RPN) that is a product of occurrence, severity, and detection difficulty. Measuring severity and detection difficulty is very subjective and with no universal scale. RPN is also a product of ordinal variables, which is not meaningful as a proper measure. This paper addresses these shortcomings and introduces a new methodology, Life Cost-Based FMEA, which measures risk in terms of cost. The ambiguity of detection difficulty and severity is resolved by measuring these in terms of time loss. Life Cost-Based FMEA is useful for comparing and selecting design alternatives that can reduce the overall life cycle cost of a particular system. Next, a Monte Carlo simulation is applied to the Cost-Based FMEA to account for the uncertainties in: detection time, fixing time, occurrence, delay time, down time, and model complex scenarios. This paper compares and contrasts these three different FMEAs: RPN, Life Cost-based point estimation, and Life Cost-Based using Monte Carlo simulation for data uncertainty.