Name
Abstract | ||
|---|---|---|
The process capability analysis aims at measuring the capability degree of the process distribution in meeting the specification limits. Process capability indices are used to indicate the capability degree of a process. A process whose distribution falls inside the specification limits is a capable process and its capability indices are at least 1. In case of vague and imprecise information, process capability analyses have been extended by using ordinary fuzzy sets in the literature. In this paper we extend the fuzzy process capability analysis from ordinary fuzzy sets to intuitionistic fuzzy sets. We realize this extension by using both intuitionistic fuzzy numbers and interval-valued intuitionistic fuzzy sets. We also propose defuzzification methods for intuitionistic fuzzy numbers and interval-valued intuitionistic fuzzy sets. Numerical examples show the applications of the proposed analyses and help the readers understand them. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.3233/JIFS-141877 | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS |
Keywords | Field | DocType |
Process capability,intuitionistic,fuzzy set,fuzzy number,interval-valued,defuzzification | Process capability,Defuzzification,Fuzzy classification,Fuzzy set operations,Fuzzy set,Artificial intelligence,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
32 | 3 | 1064-1246 |
Citations | PageRank | References |
1 | 0.36 | 17 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cengiz Kahraman | 1 | 2056 | 160.11 |
| A. Parchami | 2 | 56 | 5.22 |
| Sezi Çevik Onar | 3 | 145 | 19.67 |
| Başar Öztayşi | 4 | 251 | 27.56 |