This paper aims to prioritize the most efficient Six Sigma project that can generate the greatest benefit to the organization, according to the relative performance among a set of homogenous projects (in here, DMUs). The selection of a Six Sigma project is a multiple-criteria decision-making problem, which is difficult in practice because the projects are not yet complete and the values of evaluation indicators are often interval or imprecise data. Managers stress the need for developing an effective performance evaluation methodology for selecting a Six Sigma project.
This study proposes a modified model considering interval or imprecise data based on common weight data envelopment analysis (DEA) approach to solve problems on project selection.
By comparing its findings with an example from a previous study, the new model obtained realistic and fair evaluation results and significantly reduced the difficulties and the time spent during calculation. Moreover, not only the best project is identified, but also the exact indicator information is obtained.
This study solves the problem of selecting the most efficient Six Sigma project in the preference of interval or imprecise data. Many studies have shown how a Six Sigma project is chosen, but only a few have integrated interval data into the selection process.
Wen, Y., An, Q., Xu, X. and Chen, Y. (2018), "Selection of Six Sigma project with interval data: common weight DEA model", Kybernetes, Vol. 47 No. 7, pp. 1307-1324. https://doi.org/10.1108/K-07-2017-0250Download as .RIS
Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited