Abstract
Failure mode and effect analysis (FMEA) is used for risk assessment. The risk priority number (RPN) is the product of the three indicators of severity (S), probability of occurrence (O), and detection (D), which is an important measure to determine the risk priority. A new geometric mean FMEA method based on information quality is presented. First, a fuzzy evaluation distribution form is proposed, which constructs a more flexible and reasonable expression of experts’ opinions in decision-making. Second, a geometric mean method to combine several probability distributions based on information quality is proposed to calculate the RPN. Finally, a numerical case study is illustrated to show the efficiency of the proposed method.
Highlights
The world is full of uncertainty, and risk is the possibility of an event having unintended consequences
Deng: New Geometric Mean Failure mode and effect analysis (FMEA) Method Based on Information Quality [26] and Soft Set Theory [27]
In order to solve this problem, this paper proposes a new FMEA method, which combines fuzzy probability distribution, generalized information quality and geometric mean to overcome the shortcomings of traditional risk priority number (RPN)
Summary
The world is full of uncertainty, and risk is the possibility of an event having unintended consequences. One of the most important parameters is Risk Priority Number (RPN), which is the product of severity (S), occurrence probability (O) and detection (D) [9]. The higher the score, the higher the risk of a failure mode and the higher the priority of attention. This traditional risk assessment method is simple, but it has the following weaknesses [10]: First, this is a traditional risk assessment method, but it ignores the relative. Deng: New Geometric Mean FMEA Method Based on Information Quality (an acronym in Portuguese of interactive and multicriteria decision making) [26] and Soft Set Theory [27]. D numbers [39], as the generalization of basic probability assignment, are combined with FMEA [40], [41]
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