Six-Sigma Project Selection Using National Quality Award Criteria and Fuzzy Multiple Criteria Decision-Making Method

Six-Sigma is a tool of significant value in achieving operational excellence. The project selection decision is the early stage of implementation for a Six-Sigma intervention. The present study proposes national quality award criteria as the Six-Sigma project selection criteria, and proposes a hierarchical criteria evaluation process. The strategic criteria are evaluated by the management team using a fuzzy multiple criteria decision-making method. The sub-criteria which contain additional operational issues are evaluated by the Six-Sigma Champion. The proposed methodology is successfully applied in solving the project selection problem deriving from a component manufacturer. The results show that the higher a project's priority is, the greater the financial gains will be on completion of the project. Accordingly, the proposed methodology can prioritize the financial gain - which is the key performance indicator for a Six-Sigma project.

[1]  Yu-Jie Wang,et al.  Applying FMCDM to evaluate financial performance of domestic airlines in Taiwan , 2008, Expert Syst. Appl..

[2]  Ping-Teng Chang,et al.  The fuzzy Delphi method via fuzzy statistics and membership function fitting and an application to the human resources , 2000, Fuzzy Sets Syst..

[3]  Antonio Rizzi,et al.  A fuzzy logic based methodology to rank shop floor dispatching rules , 2002 .

[4]  Taho Yang,et al.  Solving a multiresponse simulation-optimization problem with discrete variables using a multiple-attribute decision-making method , 2005, Math. Comput. Simul..

[5]  Greg Brue,et al.  Six Sigma For Managers , 2002 .

[6]  Juite Wang,et al.  A fuzzy multicriteria group decision making approach to select configuration items for software development , 2003, Fuzzy Sets Syst..

[7]  William F. Rodebaugh,et al.  The Project Selection Process , 2002 .

[8]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[9]  Mitsuo Gen,et al.  An efficient approach for large scale project planning based on fuzzy Delphi method , 1995, Fuzzy Sets Syst..

[10]  A. Kaufmann,et al.  Introduction to fuzzy arithmetic : theory and applications , 1986 .

[11]  W. Edwards Deming,et al.  Out of the Crisis , 1982 .

[12]  Peter S. Pande,et al.  The Six Sigma Way Team Fieldbook: An Implementation Guide for Process Improvement Teams , 2001 .

[13]  A. Seetharaman,et al.  Critical Success Factors of Total Quality Management , 2006 .

[14]  Bernard W. Taylor,et al.  Multiple criteria R&D project selection and scheduling using fuzzy logic , 1996, Comput. Oper. Res..

[15]  R. Yager On a general class of fuzzy connectives , 1980 .

[16]  Caroline M. Eastman,et al.  Response: Introduction to fuzzy arithmetic: Theory and applications : Arnold Kaufmann and Madan M. Gupta, Van Nostrand Reinhold, New York, 1985 , 1987, Int. J. Approx. Reason..

[17]  Ching-Hsue Cheng,et al.  A modified two-tuple FLC model for evaluating the performance of SCM: By the Six Sigma DMAIC process , 2007, Appl. Soft Comput..

[18]  Cheng-Ru Wu,et al.  Using expert technology to select unstable slicing machine to control wafer slicing quality via fuzzy AHP , 2008, Expert Syst. Appl..

[19]  Zeshui Xu,et al.  An interactive method for fuzzy multiple attribute group decision making , 2007, Inf. Sci..

[20]  Shuo-Yan Chou,et al.  A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective attributes , 2008, Eur. J. Oper. Res..

[21]  Salvatore Greco,et al.  Rough sets methodology for sorting problems in presence of multiple attributes and criteria , 2002, Eur. J. Oper. Res..

[22]  Mark Goldstein,et al.  Six Sigma Program Success Factors , 2001 .

[23]  Diane Ritter A tool for improvement using the baldrige criteria , 1993 .

[24]  Taho Yang,et al.  Multiple attribute decision-making methods for the dynamic operator allocation problem , 2007, Math. Comput. Simul..

[25]  Sheng-Lin Chang,et al.  Applying fuzzy linguistic quantifier to select supply chain partners at different phases of product life cycle , 2006 .

[26]  A. I. Ölçer,et al.  A new fuzzy multiple attributive group decision making methodology and its application to propulsion/manoeuvring system selection problem , 2005, Eur. J. Oper. Res..

[27]  Forrest W. Iii Breyfogle Implementing Six Sigma: Smarter Solutions Using Statistical Methods , 1999 .

[28]  Prasun Das Reduction in delay in procurement of materials using Six Sigma philosophy , 2005 .

[29]  Pei-Chann Chang,et al.  Fuzzy Delphi and back-propagation model for sales forecasting in PCB industry , 2006, Expert Syst. Appl..

[30]  Ya Ching Liu,et al.  A new approach for application of rock mass classification on rock slope stability assessment , 2007 .

[31]  Ching-Hsue Cheng,et al.  Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation , 2002, Eur. J. Oper. Res..

[32]  Taho Yang,et al.  Multiple-attribute decision making methods for plant layout design problem , 2007 .

[33]  Rick L. Edgeman,et al.  Six sigma seen as a methodology for total quality management , 2001 .

[34]  Robert A. Davis,et al.  Linking firm performance to the Malcolm Baldrige National Quality Award implementation effort using multiattribute utility theory , 2005 .

[35]  Chao-Ton Su,et al.  Optimizing the IC delamination quality via six-sigma approach , 2005 .

[36]  Nigel J. Smith,et al.  Application of a fuzzy based decision making methodology to construction project risk assessment , 2007 .

[37]  Faysal Khalaf,et al.  Application of Design for Six Sigma to manufacturing process design at Ford PTO , 2006 .

[38]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .