Multi-Criterion Optimization for the EWMA and MEWMA Quality Control Charts Employing Genetic Algorithms
نویسندگان
چکیده
The EWMA quality control chart, and its multivariate version (MEWMA), may be designed to efficiently detect small shifts in the mean vector of a set of p quality characteristics of a production process. However, this work presents a method for the optimal design of the parameters of the MEWMA and EWMA charts to control processes where it is not convenient to detect small magnitude shifts and, at the same time, powerful enough to detect shifts considered important. This problem can be considered as a multiobjective optimization where two regions of different performance are defined. The objective of this paper is to find the best MEWMA and EWMA quality control charts given the previous regions, where the requirements for each region has to be balanced to decide which solution is better. For this purpose, friendly Windows software has been developed to optimize this problem, using Genetic Algorithms. Results show that the design using our approach outperforms the other designs. Key-Words: Genetic Algorithms, EWMA, MEWMA, Quality Control
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