A heuristic approach of constructing new process capability indices, based on weighted variance control charting method, without any assumption on populations is presented. This method adjusts the values of the capability indices in accordance with the degree of skewness and kurtosis estimated from the sample data considering the variation above and below the target value separately. For the symmetric populations, however, these capability indices would be equivalent to the normality-based capability indices. A simulation study was conducted to evaluate the robustness of this new approach under a variety of non-normal skewed process data when the sample sizes are 75, 100, 150, and 200, and the Johnson-Kotz-Peam method is compared under the same situation as well. The results show that this heuristic approach performs better in evaluating process fallout when the underlying distribution belongs to lognormal and skewed unbounded distributions.
|Number of pages||10|
|Journal||International Journal of Industrial Engineering : Theory Applications and Practice|
|Publication status||Published - 2001 Sep 1|
All Science Journal Classification (ASJC) codes
- Industrial and Manufacturing Engineering