Applying a Hybrid MCDM Model for Six Sigma Project Selection | Zendy

FuKwun Wang | Zendy; Chen-Hsoung Hsu | Zendy; GwoHshiung Tzeng | Zendy

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Applying a Hybrid MCDM Model for Six Sigma Project Selection

Author(s) -

FuKwun Wang,

Chen-Hsoung Hsu,

GwoHshiung Tzeng

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/730934

Subject(s) - multiple criteria decision analysis , analytic network process , dimension (graph theory) , six sigma , selection (genetic algorithm) , vikor method , relation (database) , process (computing) , computer science , operations research , engineering , mathematics , data mining , operations management , artificial intelligence , analytic hierarchy process , lean manufacturing , pure mathematics , operating system

Six Sigma is a project-driven methodology; the projects that provide the maximum financial benefits and other impacts to the organization must be prioritized. Project selection (PS) is a type of multiple criteria decision making (MCDM) problem. In this study, we present a hybrid MCDM model combining the decision-making trial and evaluation laboratory (DEMATEL) technique, analytic network process (ANP), and the VIKOR method to evaluate and improve Six Sigma projects for reducing performance gaps in each criterion and dimension. We consider the film printing industry of Taiwan as an empirical case. The results show that our study not only can use the best project selection, but can also be used to analyze the gaps between existing performance values and aspiration levels for improving the gaps in each dimension and criterion based on the influential network relation map

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