Utilizing confidence bounds in Failure Mode Effects Analysis (FMEA) Hazard Risk Assessment

Abstract

The objective of this contribution is to provide a review and suggest possible extensions of the Failure Mode Effects Analysis (FMEA), Hazard Risk Assessment (HRA) [2] and to demonstrate the importance of these tools to general probabilistic design for reliability (PDfR) [8]. FMEA was first introduced in the 1960s by the U.S. National Aeronautics and Space Administration (NASA) and is currently used extensively across many industries. FMEA is useful in understanding the failure modes of various products, qualifying the effects of failure and aiding in the development of mitigation strategies. It is a useful tool in improving quality, reliability, and the maintainability of designs, and is a critical component in risk management strategies and evaluations. This is, actually, the approach of the prognostics and health monitoring/management (PHM) engineering. Failure mode effects and criticality analysis (FMECA) [1] is an extension of (FMEA). While FMEA is a bottom-up, inductive analytical method which may be performed at either the functional or piece-part level, FMECA extends FMEA by including a criticality analysis that is aimed, like PDfR is, at charting the probability of failure modes against the severity of their consequences. The result highlights failure modes with relatively high probability and severity of consequences, allowing remedial effort to be directed where it will produce the greatest value. FMECA tends to be preferred over FMEA in space and North Atlantic Treaty Organization (NATO) military applications, while various forms of FMEA predominate in other industries. Being extensions of the FMEAs, FMECAs add severity and probability ranking aspects to the problems of interest. This is accomplished through an appropriate HRA - an engineering process of where the risk of an event is quantified by examining the chain of the preceding events, starting with, e.g., the failure mode, then stepping through to the end effects. The approach allows quantification of risk through the use of probabilistic risk analysis (PRA) and is addressed and discussed in detail. Failure oriented accelerated testing (FOAT) [9] could and should be viewed as an important constituent part of the effort. It is shown that care must be taken to establish the appropriate probabilities, to identify the statistical independence of the random variables of importance, as well as to assess the trustworthiness of the available or obtained data. It is indicated that an important drawback of the FMEA is the lack of pure operational (field) failure data. These data are frequently utilized from the computerized maintenance management system (CMMS) software, which does not always provide a true snapshot of the Mean Time Between Failures (MTBF) or other critical characteristics of the product. This results in the situation that personal judgment plays a large part in the development of the FMEA. Several papers have been published recently on development of Fuzzy FMEA methodologies (see, e.g., [7]). This application of fuzzy logic to Hazard Risk Analysis will allow additional uncertainty and inaccuracy to be modeled throughout FMECA development, leading to a more robust decision making with consideration of various uncertainties.