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Reliability allocation is an important procedure in the early stage of product design. However, there is not a good design scheme for the reliability allocation of mechanical products. Firstly, the reliability allocation of mechanical products is still at the system level or component level, which makes it impossible to obtain more detailed reliability input parameters. Secondly, to simplify the allocation process, the interactions among allocation objects are usually ignored, which makes the result of reliability allocation not optimistic. Thirdly, the uncertainty of reliability-based mechanical product optimization has not been dealt with effectively. Therefore, this paper proposes a multi-criteria decision-making (MCDM) for mechanical product optimization design based on meta-action reliability, which integrates decision-making trial and evaluation laboratory (DEMATEL), uncertain linguistic ordered weighted averaging (ULOWA) operator, and preference ranking organization method for enrichment evaluations (PROMETHEE) II method. Also, the interval number is used to deal with the uncertainty flexibly in the decision-making process. Finally, the application and feasibility of the proposed method are illustrated with the automatic pallet changer (APC) of a CNC machine tool as an example. This method provides guidance for the reliability optimization design of mechanical products. [ABSTRACT FROM AUTHOR]

Failure mode and effects analysis (FMEA) is one of the important methods for risk analysis, and has been used in various fields to improve the reliability of systems. However, in the fuzzy environment, the aggregation, weight calculation, risk evaluation and prioritization of evaluation information limit its wide application. Therefore, this paper proposes an extended multi-objective optimization by ratio analysis plus full multiplicative form (MULTIMOORA) method based on the ordered weighted geometric averaging (OWGA) operator and Choquet integral for FMEA. Firstly, trapezoidal fuzzy numbers (TrFNs) are used for describing the fuzzy ratings of failure modes. Secondly, considering the uncertainty preferences of decision-makers, the OWGA operator is adopted for aggregating the evaluation information given by multiple decision-makers. Thirdly, the TrFNs ranking method based on the relative preference relation is combined with Choquet integral to model the interactions among risk factors, thus capturing their importance weights. On this basis, an extended MULTIMOORA method is proposed to determine the risk priority of failure modes. Finally, two case studies are provided to illustrate the effectiveness and practicability of the proposed method. [ABSTRACT FROM AUTHOR]