1 |
Kathawala Y. & Motwani J. (1994), 'Implementing quality function deployment: a systems approach', The TQM Magazine, vol. 6, No. 6, pp. 31-37
DOI
ScienceOn
|
2 |
Kim J.K., Han C.H., and Choi S.H., et al., (1998) 'A knowledge based approach to the quality function deployment', Computers Ind. Engineering, Vol. 35 No. 1-2, pp. 233-2368
DOI
ScienceOn
|
3 |
Kumar A. (2001), Applying Quality Function Deployment Techniques to Obtain Target Values for the Design of a Novel Hip Projector, Management Project of Manchester School of Management, UMIST, Manchester, UK
|
4 |
Lu M.H., Madu C.N., and Kuei C.H., et al., 'Integrating QFD, AHP and Benchmarking in Strategic Marketing', Journal of Business & Industrial Marketing, Vol. 9 No. 1, 1994, pp.41-50
DOI
ScienceOn
|
5 |
Meziane F., Vadera S., and Kobbacy K., et al, (2000) 'Intelligent systems in manufacturing: current developments and future prospects', Integrated Manufacturing System, 11/4, pp. 218-238
DOI
ScienceOn
|
6 |
Moskowitz H. and Kim K.J. (1997), 'QFD optimizer: a novice friendly quality function deployment decision support system for optimizing product designs', Computers Ind. Engineering, Vol. 32, No. 3, pp. 641-655
DOI
ScienceOn
|
7 |
Park M.K., Lee I. & Shon K.M. 1998, 'Using Case Based Reasoning for Problem Solving in a Complex Production Process', Expert System With Applcations, Vol. 15, pp. 69-75
DOI
ScienceOn
|
8 |
Stalk G. and Webber A.M., (July-Aug, 1993), 'Japan's dark side of time', Harvard Business Review
|
9 |
Surma J. & Braunschweig B. 1996, 'Case-Base Retrieval in Process Engineering: Supporting Design by Reusing Flowsheets', Engng Applic.Artif. Intell, Vol. 9, No. 4, pp. 385-391
DOI
ScienceOn
|
10 |
Tanaka H., Haysashi I. & Watada J., (1989), 'Possibilistic linear regression analysis for fuzzy data', European Journal of Operational Research, vol. 40, pp. 389-396
DOI
ScienceOn
|
11 |
Yoder, B. and Mason, D. (1995),Evaluating QFD relationships through the use of regression analysis, in Proceedings of the Seventh Symposium on Quatity Function Deployment, ASI & GOAL/ QPC, American Supplier Institute, Livonia, MI. pp. 35-39
|
12 |
Ganesan K., Khoshgoftaar T.M., and Allen E.B., (2000), ' 'Case based software quality prediction', International Journal of Software Engineering and Knowledse Engineering, Vol. 10, No. 2, pp. 139-152
DOI
ScienceOn
|
13 |
Dimancescu S. and Dwenger K. (1996), 'World-Class New Product Development: Benchmarking best practices of agile manufacturers', American Management Association (AMACOM) 1996
|
14 |
Su C.T. and Chang H.H. (2000), 'Optimization of parameter design: an intelligent approach using neural network and simulated annealing', International Journal of System Science, Vol. 31, No. 12, pp. 1543-1549
DOI
ScienceOn
|
15 |
Rao S.S., Nahm A., and Shi Z., et al., (1999) 'Artificial intelligence ad expert systems applications in new product development a survey', Journal of Intelligent Manufacturing, 10, pp. 231-244
DOI
ScienceOn
|
16 |
Schmidt R. (1997), The Implementation of Simultaneous Engineering in the Stage of Product Concept development: A process oriented improvement of Quality Function Deployment, European Journal of Operation Research, 100, pp. 293-314
DOI
ScienceOn
|
17 |
Young A.R., and Allen N. (1996), Concurrent Engineering and Product Specification, Journal of Material processing Technology 61, 181-186
DOI
ScienceOn
|
18 |
Bouchereau V. & Rowlands H. (2000), 'Methods and techniques to help quality function deployment (QFD)', Benchmarking: An International Journal, vol. 7, No. 1, pp. 8-19
DOI
ScienceOn
|
19 |
Haque B.U., Belecheanu R.A., & Barson R.J., et al. (2000), 'Towards the Application of Case Based Reasoning to Decision-Marking in Concurrent Product Development (Concurrent Engineering)', Knowledge-Based System, Vol. 13, pp. 101-112
DOI
ScienceOn
|
20 |
Tsai Y.C. J., Chin K.S. & Yang J.B., (2002), 'Development of Hybrid Quality Function Deployment Framework', Change Management, Proceedings of the International Conference on ISO 9000 and TQM, pp. 89-90, Melbourne, Australia
|
21 |
Huang Y. and Miles R. (1996), 'Using case-based techniques to enhance constraint satisfaction problem solving', Applied Artificial Intelligence, 10: 307-328
DOI
ScienceOn
|
22 |
Zimmermann H., (1978), 'Fuzzy Programming and Linear Programming with Several Objective Functions', Fuzzy Sets and Systems, 1, pp. 45-55
DOI
ScienceOn
|
23 |
Zimmermann H., (1976), 'Description and Optimization of Fuzzy Systems', International Journal of General Systems, 2 (4), pp. 209-215
DOI
ScienceOn
|
24 |
Fung R.Y.K., Popplewell K., and Xie J. (1998), 'An intelligent hybrid system for customer requirements analysis and product attribute targets determination', International Journal of Production Research, Vol. 36 No. 1, pp. 13-34
DOI
ScienceOn
|
25 |
Kolodner J. (1993), Case Based Reasoning, Morgan Kaufmann publishers, Inc
|
26 |
Smyth B. & Keane M.T. 1998, 'Adaptation-Guided Retrieval: Questioning the similarity Assumption in Reasoning', Artificial Intelligence, Vo1.102, pp. 249-293
|
27 |
Askin R.G. and Dowson D.W., (2000),'Maximizing customer satisfaction by optimal specification of engineering characteristics', IEE transactions, Vol. 32, pp. 9-20
|
28 |
Vanegas L.V. and Labib A.W. (2001), 'A Fuzzy Quality Function Deployment (FQFD) Model for Deriving Optimum Targets', Int. J. Production Research,Vol. 39, No. 1, pp. 99-120
DOI
ScienceOn
|
29 |
Curtis C.C. and Ellis L.W., (Sept/Oct, 1998), 'Satisfy customers while speeding R&D and staying profitable', Res. Technology Management, Vol. 41, pp. 23-24
DOI
|
30 |
Tanaka, H., Watada, J., (1988), 'Possibilistic linear systems and their applications to the linear regression model', Fuzzy Sets and Systems, Vol 27, pp. 275-289
DOI
ScienceOn
|
31 |
Akao Y. (1990), Quality function deploy merit: integrating customer requirements into product design, Cambridge, Mass.: Productivity Press
|
32 |
Irgens C.S. (1995), 'Design support based projection of information across the product development life cycle by means of case based reasoning'. IEE Pro.Sci Meas. Techno., Vol. 142 No.5
|
33 |
Wang J. (1999), 'Fuzzy outranking approach to prioritize design requirement s in quality function deployment', International Journal of Production Research. Vol. 37 No. 4, pp. 899-916
DOI
ScienceOn
|
34 |
Yagar R.R. (1977), 'Multiple Objective Decision-making using Fuzzy Sets', International Journal of Man-machine Studies, Vol. 9, pp. 375-382
DOI
ScienceOn
|
35 |
Temponi C., Yen J. and Tiao W. A. (1999), 'House of quality: a fuzzy logic based requirement analysis', European Journal of Operation Research, 117, pp. 340-354
DOI
ScienceOn
|
36 |
Chuang P.T. (2001), 'Combining the Analytic Hierarchy Process and Quality Function Deployment for a Location Decision for a Requirement perspective', Int. J. Adv. Manuf. Technol., vol. 18, pp. 842-849
DOI
ScienceOn
|
37 |
Kim K.J., Moskowitz H., & Dhingra A.,et al. (2000), 'Fuzzy Multicriteria Models for Quality Function Deploy ment', European Journal of Operational Reasoning, vol. 121, pp. 504-518
DOI
ScienceOn
|
38 |
Zaheh L.A. (1975), 'The Concept of a Linguistic Variable and its Applications to Approximate Reasoning-I', Inf. Science, 8, pp. 199-249
DOI
ScienceOn
|