Integration of PCA and DEA for identifying and improving the impact of Six Sigma implementation on job characteristics in an automotive industry. Issue Volume 29:Issues 2(2017) (3rd April 2017)
- Record Type:
- Journal Article
- Title:
- Integration of PCA and DEA for identifying and improving the impact of Six Sigma implementation on job characteristics in an automotive industry. Issue Volume 29:Issues 2(2017) (3rd April 2017)
- Main Title:
- Integration of PCA and DEA for identifying and improving the impact of Six Sigma implementation on job characteristics in an automotive industry
- Authors:
- Azadeh, A.
Nasirian, B.
Salehi, V.
Kouzehchi, H. - Abstract:
- ABSTRACT: This study presents an integrated approach, based on data envelopment analysis (DEA) and principal component analysis (PCA) methods, to evaluate the influence of Six Sigma deployment on key job characteristics in an automotive industry. The job characteristics are defined as satisfaction, stress, and security. A standard questionnaire is designed and distributed among the employees at the company's production site, who were affected by the implementation of Six Sigma. DEA and PCA methods are applied to measure the performance of the sub-groups of employees in the company. Consequently, the most efficient and inefficient sub-groups are determined. According to the findings of this investigation, it was perceived that the implementation of Six Sigma has had the greatest impact on job satisfaction. Additionally, a design of experiment was carried out to recognize the most effective job factor, which was identified to be the overall working conditions for the related case study. This is the first study that integrates DEA and PCA toward identifying and optimizing job characteristics in terms of Six Sigma implementation. The approach, employed in this study, can be easily used in the other manufacturing systems, in order to assist them to identify and improve their key job characteristics.
- Is Part Of:
- Quality engineering. Volume 29:Issues 2(2017)
- Journal:
- Quality engineering
- Issue:
- Volume 29:Issues 2(2017)
- Issue Display:
- Volume 29, Issue 2 (2017)
- Year:
- 2017
- Volume:
- 29
- Issue:
- 2
- Issue Sort Value:
- 2017-0029-0002-0000
- Page Start:
- 273
- Page End:
- 290
- Publication Date:
- 2017-04-03
- Subjects:
- data envelopment analysis (DEA) -- design of experiment (DOE) -- job characteristics -- optimization -- principal component analysis (PCA) -- Six Sigma
Quality control -- Periodicals
Production management -- Quality control -- Periodicals
658.5 - Journal URLs:
- http://www.tandfonline.com/toc/lqen20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/08982112.2016.1182633 ↗
- Languages:
- English
- ISSNs:
- 0898-2112
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7168.152050
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 270.xml