Optimisation of a set of or principal components control charts using genetic algorithms |
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| Authors: | Francisco Aparisi Marco A de Luna Eugenio Epprecht |
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| Affiliation: | 1. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad , Universidad Politécnica de Valencia , 46022 Valencia , Spain faparisi@eio.upv.es;3. Departamento de Ingeniería Industrial y Mecánica , ITESM , Campus Guadalajara, 45140 Guadalajara , Mexico;4. Departamento de Engenharia Industrial , Pontificia Universidade Católica de Río de Janeiro , CEP: 22453-900, Gávea , Rio de Janeiro , Brasil |
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| Abstract: | When a multivariate process is to be monitored, there are the options of employing a set of univariate control charts or a single multivariate chart. This paper shows how to effectively design a multivariate control scheme consisting of two or three X charts, using genetic algorithms to optimise the charts parameters. The procedure is implemented using software tools, which we designed. A complete performance comparison of the scheme with the Hotelling's T 2 control chart can be made in order to help the user in choosing the most adequate option for the process under consideration. Also, if the user prefers to employ charts based on principal components rather than on the original variables, the software can be used in the same way to optimise a set of two or three control charts based on these components, and to compare their performance with the performance of the T 2 chart on the principal components. |
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| Keywords: | control chart optimisation multiple genetic algorithms |
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