A Study of X-bar Control Charts Design with Non-normally Data for Optimizing Cost and Monitoring Efficiency
| Autor: | Chia-Ju Li, 李嘉茹 |
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| Rok vydání: | 2007 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 95 Traditionally, when the issue of designing control chart is discussed, one usually assumes the observations in each sampled subgroup are normally distributed; therefore, the sample mean is also normally distributed. Even if the size of subgroup is large enough, the observations will be distributed normally according to the central limit theorem. However, the assumption may not be acceptable in practice. In this research, an economic-statistical design of X-bar chart with warning limit under Non-normal distributions will be developed using the Burr distribution. In the part of economic design, Gordon and Weindling (1975) cost model is used to minimize average cost per part produced. In the part of statistical design, average run length (ARL) is used as the statistical limiting conditions. The genetic algorithm (GA) is adopted to search for the optimal parameters, i.e. the sampling size (n), the sampling interval (s), the run length (r), the warning limit coefficients (w) and the control limit coefficients (k). By sensitive analysis we can get fixed sampling cost (CF) and cost correcting the assignable cause (CA2) don’t affect average cost per part produced. An increase in variation sampling cost (CV), cost of defective product (CD), cost of searching for assignable cause (CA1) and mean number of shift (θ) leads to increase average cost per part produced. In addition, An increase in shift coefficient (δ) and allowable semi-tolerance leads to increase average cost per part produced. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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