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Pca-based Desirabilty Index for Multi-objective Optimization
| Content Provider | Semantic Scholar |
|---|---|
| Author | Wonggasem, Kris Weihs, Claus |
| Copyright Year | 2011 |
| Abstract | The desirability index (DI) is a method for multi-objective optimization accepted widely in industrial quality management. However desirability functions (DFs) of the quality criteria are assumed to be independent, which not hold in general for practical applications and may cause biased optimization results. In this study, principal component analysis (PCA) is used to eliminate correlation among DFs. Then the uncorrelated quality indices are aggregated into overall DI. The effectiveness of the proposed procedure is demonstrated with an application in turning operation. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://phoenix.eng.psu.ac.th/pec9/icet/paper/ie/P36.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |