Augmented approach to desirability function based on principal component analysis
The desirability function approach is commonly used in industry to tackle multiple response optimization problems. The shortcoming of this approach is that the variability and correlated in each predicted response are ignored. It is now evident that the actual response may fall outside the acceptabl...
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| Format: | Article |
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Human Resource Management Academic Research Society
2022
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| _version_ | 1796983904625754112 |
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| author | Thorisingam, Yuvarani Mustafa, Mohd Shafie |
| author_facet | Thorisingam, Yuvarani Mustafa, Mohd Shafie |
| author_sort | Thorisingam, Yuvarani |
| collection | UPM |
| description | The desirability function approach is commonly used in industry to tackle multiple response optimization problems. The shortcoming of this approach is that the variability and correlated in each predicted response are ignored. It is now evident that the actual response may fall outside the acceptable region even though the predicted response at the optimal solution has a high overall desirability score. An augmented approach to the desirability function (AADF) and the Principal Component Analysis (PCA) is put forward to rectify this problem. This paper will discuss how the two methodologies have been used together where the goal is to determine the final optimal factor/level combination when several responses are to be optimized. Additionally, in this work optimization of multiple correlated responses was studied and AADF model was proposed based on PCA to optimize correlated multiple response problems. The proposed method is also demonstrated by numerical example from the literature to confirm the efficiencies. |
| first_indexed | 2024-03-06T11:13:00Z |
| format | Article |
| id | upm.eprints-100491 |
| institution | Universiti Putra Malaysia |
| last_indexed | 2024-03-06T11:13:00Z |
| publishDate | 2022 |
| publisher | Human Resource Management Academic Research Society |
| record_format | dspace |
| spelling | upm.eprints-1004912023-11-23T08:51:35Z http://psasir.upm.edu.my/id/eprint/100491/ Augmented approach to desirability function based on principal component analysis Thorisingam, Yuvarani Mustafa, Mohd Shafie The desirability function approach is commonly used in industry to tackle multiple response optimization problems. The shortcoming of this approach is that the variability and correlated in each predicted response are ignored. It is now evident that the actual response may fall outside the acceptable region even though the predicted response at the optimal solution has a high overall desirability score. An augmented approach to the desirability function (AADF) and the Principal Component Analysis (PCA) is put forward to rectify this problem. This paper will discuss how the two methodologies have been used together where the goal is to determine the final optimal factor/level combination when several responses are to be optimized. Additionally, in this work optimization of multiple correlated responses was studied and AADF model was proposed based on PCA to optimize correlated multiple response problems. The proposed method is also demonstrated by numerical example from the literature to confirm the efficiencies. Human Resource Management Academic Research Society 2022-05-04 Article PeerReviewed Thorisingam, Yuvarani and Mustafa, Mohd Shafie (2022) Augmented approach to desirability function based on principal component analysis. International Journal of Academic Research in Progressive Education and Development, 11 (2). 526 - 533. ISSN 2226-6348 https://hrmars.com/index.php/IJARPED/article/view/13270/Augmented-Approach-to-Desirability-Function-Based-on-Principal-Component-Analysis 10.6007/IJARPED/v11-i2/13270 |
| spellingShingle | Thorisingam, Yuvarani Mustafa, Mohd Shafie Augmented approach to desirability function based on principal component analysis |
| title | Augmented approach to desirability function based on principal component analysis |
| title_full | Augmented approach to desirability function based on principal component analysis |
| title_fullStr | Augmented approach to desirability function based on principal component analysis |
| title_full_unstemmed | Augmented approach to desirability function based on principal component analysis |
| title_short | Augmented approach to desirability function based on principal component analysis |
| title_sort | augmented approach to desirability function based on principal component analysis |
| work_keys_str_mv | AT thorisingamyuvarani augmentedapproachtodesirabilityfunctionbasedonprincipalcomponentanalysis AT mustafamohdshafie augmentedapproachtodesirabilityfunctionbasedonprincipalcomponentanalysis |