Six-Sigma project selection using national quality award criteria and Delphi fuzzy multiple criteria decision-making method

Expert Systems with Applications

Volumn 36, Issue 4, 2009, Pages 7594-7603

  Yang, Taho ^a   Hsieh, Chiung Hsi ^a  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Delphi method; Fuzzy set; Multiple criteria decision making; National quality award; Six Sigma project

Indexed keywords

BENCHMARKING; DECISION MAKING; FUZZY SETS; MANAGEMENT; PHILOSOPHICAL ASPECTS; PROCESS MONITORING; TECHNOLOGICAL FORECASTING;

DELPHI METHOD; FUZZY SET; MULTIPLE CRITERIA DECISION-MAKING; NATIONAL QUALITY AWARD; SIX-SIGMA PROJECT;

PROCESS ENGINEERING;

EID: 60249084122     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2008.09.045     Document Type: Article

References (43)

1. Bellman R.E., and Zadeh L.A. Decision-making in a fuzzy environment. Management Science 17 (1970) B141-B164
2. Breygogle III F.W. Implementing Six Sigma smarter solutions using statistic methods (1999), Wiley, New York
3. Brue G. Six Sigma for managers (2002), McGraw-Hill, New York
4. Chang P.T., Huang L.C., and Lin H.J. The fuzzy Delphi method via fuzzy statistics and membership function fitting and an application to the human resources. Fuzzy Sets and Systems 112 (2000) 511-520
5. Chang I.S., Tasuhiro Y., and Tozawa T. An efficient approach for large scale project planning based on fuzzy Delphi method. Fuzzy Sets and Systems 76 (1995) 277-288
6. Chang P.C., and Wang Y.W. Fuzzy Delphi and back-propagation model for sales forecasting in PCB industry. Expert Systems with Applications 30 (2006) 715-726
7. Chang S.L., Wang R.C., and Wang S.Y. Applying fuzzy linguistic quantifier to select supply chain partners at different phases of product life cycle. International Journal of Production Economics 100 (2006) 348-359
8. Chang C.W., Wu C.R., and Chen H.C. Using expert technology to select unstable slicing machine to control wafer slicing quality via fuzzy AHP. Expert Systems with Applications 34 (2008) 2210-2220
9. Cheng C.H., and Lin Y. Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation. European Journal of Operational Research 142 (2002) 174-186
10. Chou S.Y., Chang Y.H., and Shen C.Y. A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective attributes. European Journal of Operational Research 189 (2008) 132-145
11. Coffin M.A., and Taylor III B.W. Multiple criteria R&D project selection and scheduling using fuzzy logic. Computers and Operations Research 23 (1996) 207-220
12. Das P. Reduction in delay in procurement of materials using six sigma philosophy. Total Quality Management and Business Excellence 16 (2005) 645-656
13. Davis R.A., and Stading G.L. Linking firm performance to the Malcolm Baldrige national quality award implementation effort using multiattribute utility theory. Managerial Finance 31 (2005) 19-34
14. Deming W.E. Out of the crisis. 2nd ed. (1986), MIT Press, Cambridge, MA
15. Eckes G. Six Sigma execution (2006), McGraw-Hill, New York
16. Edgeman, R. L. (2000). Quoted in "New voices of quality: 21 for the 21st century". In: M. Maguire, (Ed.), Quality Progress (Vol. 33, pp. 31-39).
17. George M.L., Rowlands D., Price M., and Maxey J. The lean Six Sigma pocket tool book (2006), McGraw-Hill, New York
18. Greco S., Matarazzo B., and Slowinski R. Rough set methodology for sorting problems in presence of multiple attributes and criteria. European Journal of Operational Research 138 (2002) 247-259
19. Hutchins D. The power of Six Sigma in practice. Measuring Business Excellence 4 (2000) 26-33
20. Jang J.-S.R., Sun C.-T., and Mizutani E. Neuro-fuzzy and soft computing (1997), Prentice Hall, Upper Saddle River, NJ
21. Kalamdani R., and Khalaf F. Application of design for six sigma to manufacturing process design at Ford PTO. International Journal of Product Development 3 (2006) 369-387
22. Kaufmann A., and Gupta M.M. Introduction to fuzzy arithmetic: Theory and applications (1985), Van Nostrand Reinhold, New York
23. Klefsjö B., Wiklund H., and Edgeman R.L. Six sigma seen as a methodology for total quality management. Measuring Business Excellence 5 (2001) 31-35
24. Liu Y.C., and Chen C.H. A new approach for application of rock mass classification on rock slope stability assessment. Engineering Geology 89 (2007) 129-143
25. Mark D.G. Six Sigma program success factors. Six Sigma Forum Magazine 1 (2001) 36-45
26. Ölcer A.I., and Odabasi A.Y. A new fuzzy multiple attribute group decision making methodology and its application to propulsion/manoeuvring system selection problem. European Journal of Operation Research 166 (2005) 93-114
27. Pande P.S., Robert P.N., and Roland R.C. The Six Sigma way team fieldbook (2002), McGraw-Hill, New York
28. Petroni A., and Rizzi A. Fuzzy logic based methodology to rank shop floor dispatching rules. International Journal Production Economics 76 (2002) 99-108
29. Przekop P. Six Sigma for business excellence (2006), McGraw-Hill, New York
30. Ritter D. A tool for improvement using the Baldrige criteria. National Productivity Review 12 (1993) 167-182
31. Seetharaman A., Sreenivasan S., and Boon L.P. Critical success factors of total quality management. Quality and Quantity 40 (2006) 675-695
32. Snee R.D., and Rodebaugh Jr. W.F. The project selection process. Quality Progress (2002) 78-80
33. Su C.T., Chiang T.L., and Chiao K. Optimizing the IC delamination quality via six-sigma approach. IEEE Transactions on Electronics Packaging Manufacturing 28 (2005) 241-248
34. Wang Y.J. Applying FMCDM to evaluate financial performance of domestic airlines in Taiwan. Expert Systems with Applications 34 (2008) 1837-1845
35. Wang J., and Lin Y. A fuzzy multicriteria group decision making approach to select configuration items for software development. Fuzzy Sets and Systems 134 (2003) 343-363
36. Xu Z.S., and Chen J. An interactive method for fuzzy multiple attribute group decision making. Information Sciences 177 (2007) 248-263
37. Yager R.R. On a general class of fuzzy connectives. Fuzzy Sets and Systems 4 (1980) 235-242
38. Yang T., Chen M.-C., and Hung C.-C. Multiple attribute decision-making methods for the dynamic operator allocation problem. Mathematics and Computers in Simulation 73 (2007) 285-299
39. Yang T., and Chou P. Solving a multiresponse simulation-optimization problem with discrete variables using a multiple-attribute decision-making method. Mathematics and Computers in Simulation 68 (2005) 9-21
40. Yang T., and Hung C.-C. Multiple-attribute decision making methods for plant layout design problem. Robotics and Computer-Integrated Manufacturing 23 (2007) 126-137
41. Yeh D.Y., Cheng C.H., and Chi M.L. A modified two-tuple FLC model for evaluating the performance of SCM: By the Six Sigma DMAIC process. Applied Soft Computing 7 (2007) 1027-1034
42. Zadeh L.A. Fuzzy sets. Information and Control 8 (1965) 338-353
43. Zeng J., An M., and Smith N.J. Application of fuzzy based decision making methodology to construction project risk assessment. International Journal of Project Management 25 (2007) 589-600