Data driven supplier selection as a circular economy enabler: A Taguchi capability index for manufactured products with asymmetric tolerances. (January 2021)

• Record Type: Journal Article
• Authors: Wang, Chin-Hsin; Ali, Mohd Helmi; Chen, Kuen-Suan; Negash, Yeneneh Tamirat; Tseng, Ming-Lang; Tan, Raymond R.
• Is Part Of: Advanced engineering informatics. Volume 47(2021)
• Publication Date: 2021-01
• Subjects: Loss function -- Taguchi capability index -- Data driven supplier selection -- Membership function -- Circular economy -- Fuzzy numbers; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2021.101249
• Languages: English
• ISSNs: 1474-0346

Abstract

Highlights: This study develops a Taguchi capability index for TBL perspectives incurred due to poor product quality. A practical challenge is that many quality characteristics possess asymmetric tolerances. A data driven supplier selection model uses a Taguchi capability index with asymmetric tolerances. Mathematical programming obtains the confidence intervals to construct fuzzy membership functions. Abstract: Prior studies have failed to account for the effect of product quality on the sustainability of supply chain networks. To address this gap, this study develops a Taguchi capability index that considers the economic, environmental, and social losses incurred due to poor product quality that leads to process losses. These product quality measures give a foundation for the operationalization of the circular economy concept, which is now receiving a growing level of attention from both firms and governments throughout the world. Sustainable supply chain management models that integrate upstream and downstream operations are increasing in popularity due to globalized competition, where the quality of components from each supplier affects the quality of the final product. One practical challenge is that many quality characteristics possess asymmetric tolerances. This study develops a comprehensive supplier selection model based on process quality, using a Taguchi capability index with asymmetric tolerances as an instrument for data driven supplier selection. Mathematical programming is used to obtain the confidence intervals of the indices to construct fuzzy membership functions. A fuzzy hypothesis testing method is then used to select suppliers taking into account uncertainty associated with measurement data. A case study illustrates the effectiveness of the methodology to assist firms in selecting the suppliers, and thus improve the sustainability of supply chain networks as a circular economy enabler.