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위험 요인 평가를 위한 FMEA의 일반 RPN 모형과 활용에 관한 연구
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Publication Year
2022-03
Journal
품질경영학회지
Publisher
한국품질경영학회
Citation
품질경영학회지, Vol.50 No.1, pp.125-138
Keyword
FMEARPNcRPNCobb-Douglas Production Function
Abstract
Purpose: Failure Mode and Effect Analysis (FMEA) is a widely utilized technique to measure product reliability by identifying potential failure modes. Even though FMEA techniques have been studied, the form of Risk Priority Number (RPN) used to evaluate risk priority in FMEA is still questionable because of its shortcomings. <br>In this study, we suggest common RPN(cRPN) to resolve shortcomings of the traditional RPN and show the extensibility of cRPN. <br>Methods: We suggest cRPN which is based on Cobb-Douglas production function, and represent the various application on weighting risk factors, weighted RPN in a mathematical way, and show the possibility of statistical approach. We also conduct numerical study to examine the difference of the traditional RPN and cRPN as well as the potential application from the analysis on marginal effects of each risk factor. <br>Results: cRPN successfully integrates previously suggested approaches especially on the relative importance of risk factors and weighting RPN. Moreover, we analyze the effect of corrective actions in terms of econometric analysis using cRPN. Since cRPN is rely on the reliable mathematical model, there would be numerous applications using cRPN such as smart factory based on A.I. techniques. <br>Conclusion: We propose a reliable mathematical model of RPN based on Cobb-Douglas production function. <br>Our suggested model, cRPN, resolves various shortcomings such as consideration of the relative importance, the effect of combinations among risk factors. In addition, by adopting a reliable mathematical model, quantitative approaches are expected to be applied using cRPN. We find that cRPN can be utilized to the field of industry because it is able to be applied without modifying the entire systems or the conventional actions.
ISSN
1229-1889
Language
Kor
URI
https://aurora.ajou.ac.kr/handle/2018.oak/35556
DOI
https://doi.org/10.7469/JKSQM.2022.50.1.125
Type
Article
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Kang, Ju Young Image
Kang, Ju Young강주영
Department of Business Intelligence
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