Applying a Hybrid MCDM Model for Six Sigma Project Selection

Fu-Kwun Wang,Chen-Hsoung Hsu,Gwo-Hshiung Tzeng

doi:10.1155/2014/730934

Abstract

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.

Highlights

Six Sigma is a business strategy that seeks to identify and eliminate the causes of errors or defects, which are defined as any factors that could lead to customer dissatisfaction or failures in business processes, by focusing on outputs that are critical to customers [1,2,3]
Banuelas et al [7] reported that several approaches including cost-benefit analysis, cause and effect matrices, Pareto analysis, priority indices, analytic hierarchy process (AHP), the theory of constraints (TOC), and quality function deployment (QFD) have been applied to the selection of Six Sigma projects by various organizations in the UK
We developed dimensions and criteria that align with the strategy of a soft packaging material (SPM) manufacturing company to evaluate and select Six Sigma projects

Summary

Introduction

Six Sigma is a business strategy that seeks to identify and eliminate the causes of errors or defects, which are defined as any factors that could lead to customer dissatisfaction or failures in business processes, by focusing on outputs that are critical to customers [1,2,3]. Banuelas et al [7] reported that several approaches including cost-benefit analysis, cause and effect matrices, Pareto analysis, priority indices, analytic hierarchy process (AHP), the theory of constraints (TOC), and quality function deployment (QFD) have been applied to the selection of Six Sigma projects by various organizations in the UK Other methods such as the Balanced Scorecard method [8], data envelopment analysis (DEA) [9], a multiobjective model [10], a fuzzy-AHP with goal programming approach [11], and a hierarchical criterion evaluation process based on national quality award criteria [12] were used to select Six Sigma projects. These sixteen knowledge-based experts were the corporation general manager, the plant assistant general manager, the R&D manager, the purchasing manager, the vice plant manager, and the section managers

Research Problem

A Hybrid MCDM Model

C10 C11 C12 C13 C14 C15 C16 C17

Conclusion