A synthetic control chart for monitoring the process mean and variance
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Data
2006-04-10
Autores
Costa, A. F B [UNESP]
Rahim, M. A.
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Resumo
Purpose - The aim of this paper is to present a synthetic chart based on the non-central chi-square statistic that is operationally simpler and more effective than the joint X̄ and R chart in detecting assignable cause(s). This chart will assist in identifying which (mean or variance) changed due to the occurrence of the assignable causes. Design/methodology/approach - The approach used is based on the non-central chi-square statistic and the steady-state average run length (ARL) of the developed chart is evaluated using a Markov chain model. Findings - The proposed chart always detects process disturbances faster than the joint X̄ and R charts. The developed chart can monitor the process instead of looking at two charts separately. Originality/value - The most important advantage of using the proposed chart is that practitioners can monitor the process by looking at only one chart instead of looking at two charts separately. © Emerald Group Publishing Limted.
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Palavras-chave
Control theory, Markov processes, Statistical analysis, System monitoring, Algorithms, Condition monitoring, Process control, Statistical methods, Chi-square statistics, Control charts, Process mean, Variance, Process engineering
Como citar
Journal of Quality in Maintenance Engineering, v. 12, n. 1, p. 81-88, 2006.