- 作者: Chao-Yu CHOU, Chung-Ho CHEN, Hui-Rong LIU, and Pin-Hao WANG
- 中文摘要: When an control chart is used to monitor a process, three parameters should be determined: the sample size, the sampling interval between successive samples, and the control limits of the chart. Duncan presented a cost model to determine the three parameters for an chart. In their 1995 paper, S.M. Alexander and coworkers combined Duncan? cost model with the Taguchi loss function to present a loss model for determining the three parameters. In this paper, the Burr distribution is employed to obtain a statistical minimum-loss design of charts for non-normal data. The Alexander loss model is used as the objective function, and the cumulative function of the Burr distribution is applied to derive the statistical constraints of the design. An example is presented to illustrate the solution procedure. From the results of the sensitivity analyses, we find that small values of the skewness coefficient (say, a3 < 0.4) have no significant effect on the optimal design; however, when a3 > 0.4, an increase in a3 leads to slight increases in both the sample size and the sampling interval, and to a wider control limit. Meanwhile, an increase in the kurtosis coefficient (a4) results in an increase in the sample size and in a wider control limit.
- 英文摘要: --
- 中文關鍵字: loss function, control chart, statistically minimum-loss design, the Burr distribution
- 英文關鍵字: --