4.7 Article

Failure Mode and Effect Analysis for Machine Tool Risk Analysis Using Extended Gained and Lost Dominance Score Method

Journal

IEEE TRANSACTIONS ON RELIABILITY
Volume 69, Issue 3, Pages 954-967

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TR.2019.2955500

Keywords

Risk analysis; Machine tools; Reliability; Fuzzy sets; Linguistics; Industries; Analytical models; Cloud model; failure mode and effects analysis (FMEA); gained and lost dominance score method (GLDS); interaction; risk analysis

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Enhancing the reliability of machine tools and preventing the potential failures in the manufacturing process is one of the most important tasks for the development of industry. The failure mode and effects analysis (FMEA) is the well-known and widely utilized approach to identify and evaluate potential failures for preventing risk in various enterprises. It is a group-oriented technique ordinarily conducted by a group of experts from related fields. Obviously, an effective approach should be developed, which is used to integrate risk evaluation information from multiexperts by considering group and individual risk attitudes. This article proposes a hybrid FMEA framework for addressing machine tool risk analysis problem by integrating cloud model, Choquet integral, and gained and lost dominance score (GLDS) method. In this framework, an improved Shapley cloud-Choquet weighting averaging operator is defined to fuse random and uncertain risk information by considering the correlations among experts. An extended GLDS method with developed Choquet integral based on distance measure of normal clouds is presented to prioritize the risk priority of each failures, in which the group and individual risk attitude and risk interactions are considered simultaneously. Finally, a real risk analysis of machine tool in a machine tool industry is introduced to illustrate the application and feasibility of the proposed approach, and comparison and sensitivity studies are also conducted to validate the effectiveness of the hybrid framework.

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