4.6 Article

Optimization of Quality, Reliability, and Warranty Policies for Micromachines under Wear Degradation

期刊

MICROMACHINES
卷 13, 期 11, 页码 -

出版社

MDPI
DOI: 10.3390/mi13111899

关键词

MEMs; burn-in; quality; reliability; warranty; maintenance; optimization; degradation

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This work presents an optimization technique that determines inspection, warranty period, and preventive maintenance policies for degraded micromachines. The proposed mathematical model examines the impact of quality control on reliability and warranty duration, and integrates individual costs into a single measure to derive optimal parameters for quality and maintenance policies.
This work presents an optimization technique to determine the inspection, warranty period, and preventive maintenance policies for micromachines suffering from degradation. Specifically, wear degradation is considered, which is a common failure process for many Micro-Electro-Mechanical Systems (MEMS). The proposed mathematical model examines the impact of quality control on reliability and the duration of the warranty period given by the manufacturer or the supplier to the customer. Each of the above processes creates implementation costs. All the individual costs are integrated into a single measure, which is used to build the model and derive the optimal parameters of the quality and maintenance policies. The implementation of various levels of the quality, warranty, and maintenance policies are compared with their optimum level options to highlight their contribution to the assurance and improving product quality. To the authors' best knowledge, the introduction of a warranty period is implemented for the first time in the open literature concerning this type of optimization model for MEMs and surely can bring additional advantages to their quality promotion strategy. The proposed optimization tool provides a comprehensive simultaneous answer to the optimal selection of all the values of the design variables determining the overall maintenance and quality management approach.

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