Two-phase selection framework that considers production costs of suppliers and quality requirements of buyers

Abstract

Buyers are faced with selecting the optimal supplier, while suppliers are left to consider production costs. In this study, we developed a two-phase selection framework that allows buyers to evaluate the performance of suppliers while taking production costs into account for value maximisation. This scheme is a win-win solution capable of promoting long-term relationships between buyers and suppliers. Under the assumption of normality, the first phase involves constructing a new Six Sigma quality capability analysis chart (SSQCAC) which takes production costs into account. The objective is to evaluate all potential suppliers using the 100 × (1–α)% upper confidence limit (UCL) of an integrated Six Sigma quality index (SSQI) Q_PIh when dealing with products with smaller-the-better (STB), larger-the-better (LTB), or nominal-the-best (NTB) quality characteristics. According to interval estimation theory, this method can have a significant impact on the consumption of resources; i.e. the production costs of the supplier can be decreased by reducing the production quality to below that required by the buyer. The proposed method also filters out unsuitable suppliers in order to simplify the decision problem and reduce computational demands and operational risks/costs without compromising the quality of the final product. In the second phase, a detailed analysis is conducted using Euclidean distance measure to select the optimal supplier from among the remaining candidates. We conducted a real-world case study to evaluate the efficacy of the proposed method. We also conducted comparisons with existing methods to demonstrate the advantages of the proposed method and its managerial implications. Suggestions for future study are also provided.

Keywords:

• supplier selection
• Six Sigma quality index
• process capability index
• Euclidean distance

Acknowledgements

The authors would like to thank the Editor and three anonymous referees for their helpful comments and careful reading, which significantly improved the presentation of this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary data

Supplemental data for this article can be accessed doi:10.1080/00207543.2019.1566663.

Additional information

Funding

This work is financially supported by National Natural Science Foundation of China under [grant number: 71762008], Guilin University of Technology under [grant number: GUTQDJJ6616075], and the Ministry of Science and Technology Taiwan under [grant number: MOST 106-2221-E-167-003-CC3].