Modeling system behavior for risk and reliability analysis using KBARM

Failure Mode and Effects Analysis (FMEA) is a technique used in the manufacturing industry to improve production quality and productivity. It is a method that evaluates possible failures in the system, design, process or service. It aims to continuously improve and decrease these kinds of failure modes. Adaptive Resonance Theory (ART) is one of the learning algorithms without consultants, which are developed for clustering problems in artificial neural networks. In the FMEA method, every failure mode in the system is analyzed according to severity, occurrence and detection. Then, risk priority number (RPN) is acquired by multiplication of these three factors and the necessary failures are improved with respect to the determined threshold value. In addition, there exist many shortcomings of the traditional FMEA method, which affect its efficiency and thus limit its realization. To respond to these difficulties, this study introduces the method named Fuzzy Adaptive Resonance Theory (Fuzzy ART), one of the ART networks, to evaluate RPN in FMEA.

Section: Fmea and Its Shortcomingsmentioning

confidence: 98%

An alternative evaluation of FMEA: Fuzzy ART algorithm

Keskin

Özkan

2008

“…have proposed a systematic procedure for calculating probabilities of operator action failure in CREAM. The importance of integrating approaches such as fuzzy modeling to the use of HRA is also stated by Sharma et al …”

Section: Human Reliability Analysismentioning

confidence: 99%

Human Reliability Analysis in Spaceflight Applications

Calhoun

Savoie

Randolph-Gips

et al. 2012

Predicting and mitigating human error in manned spaceflight can be the difference between mission success and lost vehicle or crewmember. The National Aeronautics and Space Administration (NASA) has used the Cognitive Reliability Error Analysis Model analysis developed by the nuclear industry during the last 30 years of manned spaceflight to predict human error. Although the analysis has proven to be reliable, it does not take into account operations specific for long duration spaceflight such as crew training and ground support. This article first explains the principles of the Cognitive Reliability Error Analysis Model and how it is used at NASA. Then, the probability for error for an International Space Station ingress procedure is calculated using standard performance shaping factors developed for the nuclear power industry. Lastly, the environmental and operational constraints of space flight are used to develop new performance shaping factors specific to a NASA‐operated spacecraft. Copyright © 2012 John Wiley & Sons, Ltd.

“…It has made numerous progresses: Chang et al integrated grey relational analysis (GRA) and the decision‐making trial and evaluation laboratory (DEMATEL) method, to rank the risk of failure, wherein the grey relational analysis is used to modify RPN values to lower duplications and the ordered weighted rule is followed; then, the DEMATEL method is applied to examine the direct and indirect relationships between FMs and CFs, giving higher priority when a single CF causes FMs to occur multiple times . Sharma et al presented a methodological and structured approach (which makes use of both qualitative and quantitative techniques) to model, analyze and predict the failure behavior of two units, namely the forming and press units of a paper machine, using knowledge‐based approximate reasoning methodologies . Zhou and Thai proposed a new FMEA method, in which FST is used to calculate the fuzzy risk priority numbers (FRPNs), and grey theory is applied to calculate the grey relational coefficient.…”

Section: Preliminariesmentioning

confidence: 99%

“…57 Sharma et al presented a methodological and structured approach (which makes use of both qualitative and quantitative techniques) to model, analyze and predict the failure behavior of two units, namely the forming and press units of a paper machine, using knowledge-based approximate reasoning methodologies. 58 Zhou and Thai proposed a new FMEA method, in which FST is used to calculate the fuzzy risk priority numbers (FRPNs), and grey theory is applied to calculate the grey relational coefficient. The rankings of the failure modes are both determined by fuzzy risk priority numbers and the grey theory.…”

Section: Failure Mode and Effects Analysis Models Based On Grey Theorymentioning

confidence: 99%

An Evidential Failure Mode and Effects Analysis Using Linguistic Terms

Xiao

Fei

et al. 2016

Failure mode and effects analysis (FMEA) has been extensively used in reliability engineering domain. Risk priority number (RPN), defined as the product of occurrence (O), severity (S), and detection (D) of a failure, is the most important measure used in FMEA for prioritizing risk. In this paper, a new evidential FMEA using linguistic term is presented. First, the linguistic terms have been applied in the form of assessment distribution, which enables the experts to express their assessments in a more realistic way and hence improving the applicability of the FMEA. Second, a novel method to transform the experts' linguistic judgments into basic probability assignments (BPAs) is proposed. Third, the flexibility of assigning a weight to each criterion in the FMEA provides a means of specifically identifying weak areas in the system/component studied. At the same time, the weights can be utilized as the discounting coefficients to address the problem existing in conflicting evidence combination. An example is illustrated to show the practical application of the proposed FMEA methodology in engineering. Copyright © 2016 John Wiley & Sons, Ltd.