| Summary: | 碩士 === 國立交通大學 === 工業工程與管理系所 === 97 === Process capability indices (PCIs) have been proposed in the manufacturing industry to provide numerical measures on process reproduction capability, which are effective tools for quality assurance and guidance for process improvement. The assumption that the process is stable (the process mean and variance are not change) must be made before PCIs are calculated. In practice, the process is dynamic. If the process mean has a small shift, and the control chart doesn’t detect, then the PCIs will overestimate the true process capability. For this reason, the PCIs have to be adjusted under those cases. Motorola, Inc. introduced its Six Sigma quality initiative to the world in the 1980s. Some quality practitioners questioned why the Six Sigma advocates claim it is necessary to add 1.5 . Bothe (2002) provided the adjustment method for normality processes. Bothe (2002) provided a statistical reason for including such a shift in the process average that is based on the chart’s subgroup size. Data in Bothe’ study was assumed to be approximately normally distribution, but the process output is usually not from approximately normally. Some research is about the PCIs adjustment for process output has a non-normal distribution. In fact, the process variance could also change. In this paper, we consider the variance change adjustments to compute reliable estimates for capability index Weibull distribution data. For illustration purpose, an application example is presented.
|
|---|
