Name
Abstract | ||
|---|---|---|
Process capability indices are summary statistics which measure the actual or the potential performance of process characteristics relative to the target and specification limits. In most traditional methods, precise estimation is used to assess the capability of manufacturing processes. In this paper we introduce an algorithm based on Buckley's estimation approach, and use a family of confidence intervals to estimate process capability indices C"p, C"p"k and C"p"m. The estimators of these indices thus obtained are triangular shaped fuzzy numbers. We also present and illustrate method for the comparison of estimated process capability indices. Numerical examples are given to show the performance of the method. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.ins.2006.08.016 | Inf. Sci. |
Keywords | Field | DocType |
traditional method,precise estimation,fuzzy number,process capability,fuzzy estimation,confidence interval,estimated process capability index,potential performance,process capability index,process characteristic,estimation approach,fuzzy set | Process capability,Fuzzy logic,Algorithm,Fuzzy set,Artificial intelligence,Statistics,Confidence interval,Fuzzy number,Process capability index,Machine learning,Mathematics,Estimator | Journal |
Volume | Issue | ISSN |
177 | 6 | 0020-0255 |
Citations | PageRank | References |
34 | 2.05 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. Parchami | 1 | 56 | 5.22 |
| M. Mashinchi | 2 | 159 | 15.19 |