Abstract
We developed type-2 fuzzy percentile-based standard PCIs for non-normal data via Clements' method. For modeling uncertainty and imprecision of data, interval type-2 fuzzy sets are utilized. To prove usefulness and applicability of the proposed type-2 fuzzy percentile-based standard PCIs, a numerical illustration is performed for the data randomly generated from Log-normal distribution. The results show that in comparison with their crisp types, the proposed type-2 fuzzy percentile-based standard PCIs for non-normal processes are more informative, sensitive and flexible to evaluate the process performance of the industrial processes.
| Original language | English |
|---|---|
| Pages (from-to) | 769-781 |
| Number of pages | 13 |
| Journal | Journal of Intelligent and Fuzzy Systems |
| Volume | 27 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2014 |
Bibliographical note
Publisher Copyright:© 2014-IOS Press and the authors. All rights reserved.
Keywords
- clements' method
- interval type-2 fuzzy set
- non-normal processes
- Process capability index