A quantitative method for Failure Mode and Effects Analysis

Braaksma, Jan; Meesters, Aljar; Klingenberg, W.; Hicks, C

doi:10.1080/00207543.2011.632386

Cited by 34 publications

(15 citation statements)

References 16 publications

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“…However, there are still some differences between the proposed FMEA method and the fuzzy one. For example, FM 6 and FM 8 have the same priority in the fuzzy FMEA method, but the rankings are totally different in the proposed FMEA method. The explanation can also attribute to the weights problem and different ranking features.…”

Section: Comparison and Discussionmentioning

confidence: 99%

“…Among them, failure modes and effects analysis (FMEA) is regarded as one of the most effective methods and is widely used in the process of service and production. 8,9 Second, RPN is also doubted by many experts due to its shortcomings, 10 which are listed below: 6 It has been proven to be an efficient technique in preventing potential failures during its long-term applications.…”

Section: Introductionmentioning

confidence: 99%

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An interval probability‐based FMEA model for risk assessment: A real‐world case

Ouyang

Zheng

Zhu

et al. 2019

Quality & Reliability Eng

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Failure mode and effect analysis (FMEA) is an effective quality tool to eliminate the risks and enhance the stability and safety in the fields of manufacturing and service industry. Nevertheless, the conventional FMEA has been criticized for its drawbacks in the evaluation process of risk factors or the determination of risk priority number (RPN), which may lead to inaccurate evaluation results. Therefore, in this paper, we develop a novel FMEA method based on rough set and interval probability theories. The rough set theory is adopted to manipulate the subjectivity and uncertainty of experts' assessment and convert the evaluation values of risk factors into interval numbers. Meanwhile, the interval exponential RPN (ERPN) is used to replace the traditional RPN due to its superior properties, eg, solving the problems of duplicate numbers and discontinuity of RPN values. Furthermore, an interval probability comparison method is proposed to rank the risk priority of each failure mode for avoiding the information loss in the calculation process of RPN. Finally, a real case study is presented, and the comparison analysis among different FMEA methods is conducted to demonstrate the reliability and effectiveness of the proposed FMEA method.

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Section: Comparison and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An interval probability‐based FMEA model for risk assessment: A real‐world case

Ouyang

Zheng

Zhu

et al. 2019

Quality & Reliability Eng

View full text Add to dashboard Cite

show abstract

“…3.1 Building an influential network relationship with DEMATEL DEMATEL techniques have recently been considered for solving complex problems, such as those related to failure mode and effects analysis (Braaksma et al 2012) and product-service system (Phumbua and Tjahjono 2012). This DEMATEL method is widely used to solve various types of complex problems and can be used to effectively understand complex structures and provide viable options for problem-solving (Tzeng and Huang 2011).…”

Section: Proposed Hdmcdm Approachmentioning

confidence: 99%

Application of a hybrid dynamic MCDM to explore the key factors for the internal control of procurement circulation

Chen

2014

International Journal of Production Research

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Decisions related to the internal control measurement of procurement circulation are inherently multiple criteria decisionmaking problems and are strategically important to enterprises. Although efforts have been made to discover systematic methods for enhancing purchasing performance, the criteria have been assumed to be independent, which is not actually the case. Most conventional decision models cannot capture the complex interrelationships the criteria. Here, we propose a workable hybrid dynamic multiple criteria decision-making (HDMCDM) method to solve the problems arising from the complex dynamics in the real world. The relationship between the criteria and the criteria weights for the HDMCDM are developed by combining the decision-making trial and evaluation laboratory (DEMATEL) method with the fundamental concept of the analytic network process (ANP), the DEMATEL-based ANP (DANP). VlseKriterijumska Optimizacija I Kompromisno Resenje is then used to aggregate the performance gaps with the weights obtained from the DANP. The results obtained for a specific company show that the four dimensions of internal control of procurement circulation have a mutual influence relationship, with the dimension of 'receiving and storage' demonstrating the greatest influence and 'recorded liabilities' the least. Empirical analysis helps to improve the scores for achieving the aspiration levels for each factor.

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“…Furthermore, it is argued that RCM regards maintenance as a reliability rather than an economic problem (Waeyenbergh and Pintelon, 2002) and that it is unclear how RCM may lead to cost reduction (Gupta and Mishra, 2016). Additionally, RCM is mainly based on expert judgement, and its neglect of quantitative data is considered a weakness (Teoh and Case, 2005), which has also been addressed by more quantitative approaches to RCM (see for example Braaksma et al (2012) or the approaches listed in 'group B' in the review of Gupta and Mishra (2016, p. 140)). However, it has also been acknowledged that the availability of useable quantitative data is often limited in practice (Braaksma et al, 2013).…”

Section: Limitationsmentioning

confidence: 99%

“…One of their conclusions is that "[i]t is desirable to develop a RUL estimation model based on very few or no data situations" (Si et al, 2011, p. 11). Other instances where data problems have been recognized are Braaksma et al (2012), Kumar and Patnaikuni (2012), Jongen (2012) and Denkena et al (2014).…”

Section: Case Study Challenge 1: Due To a Limitation Of Readily Availmentioning

confidence: 99%

Manoeuvring physical assets into the future

Ruitenburg¹

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A quantitative method for Failure Mode and Effects Analysis

Cited by 34 publications

References 16 publications

An interval probability‐based FMEA model for risk assessment: A real‐world case

An interval probability‐based FMEA model for risk assessment: A real‐world case

Application of a hybrid dynamic MCDM to explore the key factors for the internal control of procurement circulation

Manoeuvring physical assets into the future

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