Application of knowledge-based artificial immune system (KBAIS) for computer aided process planning in CIM context

International Journal of Production Research

Volumn 50, Issue 18, 2012, Pages 4937-4954

  Prakash, Anuj ^a   Chan, F T S ^a   Deshmukh, S G ^b  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^b INDIAN INSTITUTE OF TECHNOLOGY DELHI   (India)

Author keywords

Artificial immune system; CAPP; Flexible manufacturing system; KBAIS

Indexed keywords

ARTIFICIAL IMMUNE SYSTEM; BENCH-MARK PROBLEMS; CAPP; COMPLEX PROBLEMS; COMPUTATIONAL EXPERIMENT; DATA SETS; FINISHED PRODUCTS; HYPER MUTATION; KBAIS; KNOWLEDGE BASE; LEAN MANUFACTURING; OPTIMISATIONS; PROCESSING COSTS; QUALITY PRODUCT; RAW MATERIAL COSTS; REDUCED COST; RESEARCH PAPERS; SEARCH ALGORITHMS;

ALGORITHMS; COMPUTER AIDED PROCESS PLANNING; CONCURRENT ENGINEERING; COSTS; FLEXIBLE MANUFACTURING SYSTEMS; IMMUNOLOGY; KNOWLEDGE BASED SYSTEMS; PHILOSOPHICAL ASPECTS; TOTAL QUALITY MANAGEMENT;

PROBLEM SOLVING;

EID: 84867050422     PISSN: 00207543     EISSN: 1366588X     Source Type: Journal    
DOI: 10.1080/00207543.2011.616234     Document Type: Article

References (35)

1. Beckman, T., 1997. A methodology for knowledge management. In: M.H. Harmza, ed. Proceedings of the IASTED international conference on artificial intelligence and soft computing, ASC '97, 27 July-1 August 1997, Banff, Canada: IASTED ACT Press, 29-32.
2. Ben-Arieh, D. and Chopra, M., 1997. Case based NC code generating system for prismatic parts. International Journal of Production Research, 35 (7), 1925-1943.
3. Ben-Arieh, D., et al., 2003. Process planning for rotational parts using the generalised traveling salesman problem. International Journal of Production Research, 41 (11), 2581-2596.
4. Ciurana, J., Ferrer, I., and Gao, J.X., 2006. Activity model and computer aided system for defining sheet metal process planning. Journal of Materials Processing Technology, 173 (2), 213-222.
5. Cutello, V. and Nicosia, G., 2002. An immunological approach to combinatorial optimisation problems. Lecture notes in Computer Science, 2527, 361-370.
6. Cutello, V., Nicosia, G. and Pavone, M., 2003. A hybrid immune algorithm with information gain for the graph coloring problem. Genetic evolutionary computation conference (GECCO 2003), 12-16 July 2003, Chicago, Illinois, USA, 171-182.
7. Davenport, T.H., Delong, D.W., and Beers, M.C., 1998. Successful knowledge management projects. Sloan Management Review, 39 (2), 43-57.
8. Davenport, T. and Prusak, L., 1998. Working knowledge: How organizations manage what they know. Boston, MA: Harvard Business School Press.
9. Decastro, L.N. and Vonzuben, F.J., 2001. aiNet: An artificial immune network for data analysis. In: A. Hussein, A. Abbass, Ruhul A. Sarker and Charles S. Newton, eds. Data mining: A heuristic approach. USA: Idea Group Publishing.
10. Decastro, L.N. and Vonzuben, F.J., 2002. Learning and optimisation using clonal selection principle. IEEE Transactions on Evolutionary Computation, 6 (3), 239-251.
11. Decastro, L.N. and Timmis, J., 2002. Artificial immune system: a novel paradigm for pattern recognition. In: L. Alonso, J. Corchado and C. Fyfe, eds. Artificial neural networks in pattern recognition. University of Paisley, 67-84.
12. Handfield, R.B. and Nichols, E.Z., 1998. Introduction to SCM. New York: Prentice Hall.
13. Husbands, P. and Mill, F., 1991. Simulated co-evolution as the mechanism for emergent planning and scheduling. In: R.K. Belew and I.B. Booker, eds. Proceedings of the 4th international conference on genetic algorithms, July 1991, San Diego, CA. San Mateo, California: Morgan Kaufmann Publishers, 264-269.
14. Kusiak, A. and Finke, G., 1998. Selection of process plans in an automated manufacturing system. IEEE Journal of Robotics and Automation, 4 (4), 397-402.
15. Li, L., et al., 2005. Application of genetic algorithm to computer aided process planning in distributed manufacturing environment. Robotics and Computer Integrated Manufacturing, 21 (6), 568-578.
16. Ma, G.H., Zhang, Y.F., and Nee, A.Y.C., 2000. A simulated annealing based optimisation algorithm for process planning. International Journal of Production Research, 38 (12), 2371-2387.
17. Ming, X.G. and Mak, K.L., 2000a. Intelligent set up planning by neural network based approach. Journal of Intelligent Manufacturing, 11 (3), 311-331.
18. Ming, X.G. and Mak, K.L., 2000b. A hybrid Hopfield network - Genetic approach to optimal process plan selection. International Journal of Production Research, 38 (8), 1823-1838.
19. Morad, N. and Zalzala, A.M.S., 1999. Genetic algorithms in integrated process planning and scheduling. Journal of Intelligent Manufacturing, 10 (2), 169-179.
20. Nassehi, A., Newman, S.T., and Allen, R.D., 2006. The application of multi-agent systems for STEP-NC computer aided process planning of prismatic components. International Journal of Machine Tools and Manufacture, 46 (5), 559-574.
21. Niebel, B.W., 1965. Mechanised process selection for planning new designs. ASME papers, 737.
22. Nietok, M., 2003. From R&D management to knowledge management: An overview of studies of innovation management. Technological Forecasting & Social Change, 70 (2), 135-161.
23. Nonaka, I., 1994. A dynamic theory of organisational knowledge creation. Organisation Science, 5 (1), 14-37.
24. Nonaka, I. and Takeuchi, H., 1995. The knowledge-creating company: How Japanese companies create the dynamics of innovation. New York, NY: Oxford University Press.
25. O'Dell, C. and Grayson, J., 1997. If we only knew what we know: Identification and transfer of internal best practices. Houston, TX: American Productivity and Quality Center.
26. Palmer, G.J., 1996. A simulated annealing approach to integrated production scheduling. Journal of Intelligent Manufacturing, 7 (3), 163-176.
27. Rai, R., Kameshwaran, S., and Tiwari, M.K., 2002. Machine tool selection and operation allocation in FMS: solving a fuzzy goal programming model using a genetic algorithm. International Journal of Production Research, 40 (3), 641-665.
28. Roh, M. and Lee, K.-Y., 2006. An initial hull structural modeling system for computer-aided process planning in shipbuilding. Advances in Engineering Software, 37 (7), 457-476.
29. Salehi, M. and Moghaddam, R.T., 2009. Application of genetic algorithm to computer-aided process planning in preliminary and detailed planning. Engineering Applications of Artificial Intelligence, 22 (8), 1179-1187.
30. Tiwana, A., 2000. The knowledge management toolkit. New Jersey: Prentice Hall.
31. Tiwana, A. and Balasubramaniam, R., 2001. A design knowledge management system to support collaborative information product evolution. Decision Support Systems, 31 (2), 241-262.
32. Tiwari, M.K. and Vidyarthi, N.K., 1998. An integrated approach to solving the process plan selection problem in an automated manufacturing system. International Journal of Production Research, 36 (8), 2167-2184.
33. Wadhwas, S. and Saxena, A., 2006. Supply chain flexibility and knowledge management: A decision knowledge sharing focus. Studies in Informatics and Control, 15 (1), 15-32.
34. Xu, H. and Li, D., 2009. Modeling of process parameter selection with mathematical logic for process planning. Robotics and Computer-Integrated Manufacturing, 25 (3), 529-535.
35. Zhang, F., Zhang, Y.F., and Nee, A.Y.C., 1997. Using genetic algorithm in process planning for job shop machining. IEEE Transaction on Evolutionary Computation, 1 (4), 278-289.