Integrating MCDM methods with FMEA framework for risk assessment of machine tools

碩士 === 國立臺北科技大學 === 工業工程與管理系 === 107 === Failure Mode and Effect Analysis (FMEA) is a risk assessment technique that is widely used in various fields. Usually, FMEA uses three risk factors to calculate the Risk Priority Number (RPN), which are Occurrence (O), Severity (S), and Detection (D). The ran...

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Bibliographic Details
Main Authors: TSAI, YU-CHE, 蔡育哲
Other Authors: LIOU, JIANN-HAW
Format: Others
Language:zh-TW
Published: 2019
Online Access:http://ndltd.ncl.edu.tw/handle/9jy538
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Summary:碩士 === 國立臺北科技大學 === 工業工程與管理系 === 107 === Failure Mode and Effect Analysis (FMEA) is a risk assessment technique that is widely used in various fields. Usually, FMEA uses three risk factors to calculate the Risk Priority Number (RPN), which are Occurrence (O), Severity (S), and Detection (D). The ranking of the failure modes is according to the RPN values. However, many scholars believe that the traditional FMEA contains many shortcomings, such as neglect the relative importance of the three risk factors O, S, D, or different scores of risk factors produce the same RPN value. This study proposes a new risk assessment model that combines Multiple Criteria Decision Making (MCDM) with FMEA to remedy the shortcomings of traditional FMEA. In order to prove the reliability and accuracy of the model, this study used a CNC machine tool as a practical case. First, the failure modes affecting the machine tool are surveyed from experts, and the expert’s opinions are summarized by the Grey theory. The traditional FMEA risk factors do not consider the budget and environmental problems. Therefore, this study added two risk factors: expected cost (E) and environmental impact (G) to reflect the actual situation. To fix the problem of the same risk factor weight in the traditional FMEA, the weight of each risk factor is calculated by the Best-Worst Method (BWM) in this study. Then, the rank of failure modes is calculated by the complex proportional assessment with the method of gray interval numbers (COPRAS-G), which provides the basis for decision makers to prevent accidents. Furthermore, this study provides a web-based system to help decision makers to analyze the failure modes and demonstrate the usefulness of the proposed model.