Knowledge acquisition techniques for feature recognition in CAD models

Journal of Intelligent Manufacturing

Volumn 19, Issue 1, 2008, Pages 21-32

  Brousseau, Emmanuel ^a   Dimov, Stefan ^a   Setchi, Rossitza ^a  

^a CARDIFF UNIVERSITY   (United Kingdom)

Author keywords

CAD CAM integration; Feature recognition; Inductive learning; Knowledge acquisition; Rule formation

Indexed keywords

BENCHMARKING; COMPUTER AIDED DESIGN; LEARNING ALGORITHMS; LOGIC PROGRAMMING; PATTERN RECOGNITION; PRODUCT DEVELOPMENT;

AUTOMATIC FEATURE RECOGNITION (AFR); INDUCTIVE LEARNING; RULE FORMATION;

KNOWLEDGE ACQUISITION;

EID: 39449113342     PISSN: 09565515     EISSN: 15728145     Source Type: Journal    
DOI: 10.1007/s10845-007-0043-7     Document Type: Article

References (39)

1. Ames, A. L. (1991). Production ready feature recognition basedc automatic group technology part coding. In Proceedings of the first ACM symposium on solid modelling foundations and CAD/CAM applications, Austin, Texas, USA (pp. 161-169). ACM Press, New York, USA.
2. Chan A.K.W., Case K. (1994). Process planning by recognizing and learning machining features. International Journal of Computer Integrated Manufacturing, 7(2): 77-99
3. Chen Y.H., Lee H.M. (1998). A neural network system for two-dimensional feature recognition. International Journal of Computer Integrated Manufacturing, 11(2): 111-117
4. Dimov S.S., Brousseau E.B., Setchi R.M. (2007). A hybrid method for feature recognition in CAD models. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 221(B1): 79-96
5. Donaldson I.A., Corney J.R. (1993). Rule-based feature recognition for 2.5D machined components. International Journal of Computer Integrated Manufacturing, 6(1&2): 51-64
6. Dong J., Vijayan S. (1997). Feature extraction with the consideration of manufacturing processes. International Journal of Production Research, 35(8): 2135-2155
7. Gao S., Shah J.J. (1998). Automatic recognition of interacting machining features based on minimal condition subgraph. Computer-Aided Design, 30(9): 727-739
8. Gindy N.N.Z. (1989). A hierarchical structure for form features. International Journal of Production Research, 27(12): 2089- 2103
9. Gupta S.K., Kramer T.R., Nau D.S., Regli W.C., Zhang G. (1994). Building MRSEV models for CAM applications. Advances in Engineering Software, 20(2-3): 121-139
10. Han, J. (1996). 3D geometric reasoning algorithms for feature recognition. Ph.D. Thesis, University of Southern California, USA.
11. Han J., Pratt M., Regli W.C. (2000). Manufacturing feature recognition from solid models: A status report. IEEE Transactions on Robotics and Automation, 16(6): 782-796
12. Henderson M.R., Anderson D.C. (1984). Computer recognition and extraction of form features: A CAD/CAM link. Computers in Industry, 5(4): 329-339
13. Henderson, M. R., Srinath, G., Stage, R., Walker, K., & Regli, W. (1994). Boundary representation-based feature identification. In J. J. Shah, M. Mantyla, & D. S. Nau (Eds.), Advances in feature based manufacturing (pp. 15-38). Elsevier Science Publishers.
14. Hummel, K. E. (1989). Coupling rule-based and object-oriented programming for the classification of machined features. In Proceedings of the ASME international computers in engineering conference (pp. 409-418). Anheim, CA, USA.
15. Hwang J.-L., Henderson M.R. (1992). Applying the perceptron to three-dimensional feature recognition. Journal of Design and Manufacturing, 2(4): 187-198
16. TM. Available from https://javacc.dev. java.net (accessed 23rd November 2005).
17. Ji Q., Marefat M.M. (1995). Bayesian approach for extracting and identifying features. Computer-Aided Design, 27(6): 435-454
18. Ji Q., Marefat M.M. (1997). Machine interpretation of CAD data for manufacturing applications. ACM Computing Survey, 24(3): 264-311
19. Lankalapalli K., Chatterjee S., Chang T.C. (1997). Feature recognition using ART2: A self-organising neural network. Journal of Intelligent Manufacturing, 8(3): 203-214
20. Li W.D., Ong S.K., Nee A.Y.C. (2000). Recognition of overlapping machining features based on hybrid artificial intelligent techniques. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 214(B8): 739-744
21. Li W.D., Ong S.K., Nee A.Y.C. (2003). A hybrid method for recognizing interacting machining features. International Journal of Production Research, 41(9): 1887-1908
22. Lockett H.L., Guenov M.D. (2005). Graph-based feature recognition for injection moulding based on a mid-surface approach. Computer-Aided Design, 37(2): 251-262
23. Marefat M., Kashyap R.L. (1990). Geometric reasoning for recognition of three-dimensional object features. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(10): 949-965
24. Marquez M., White A., Gill R. (2001). A hybrid neural network - feature-based manufacturability analysis of mould reinforced plastic parts. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 215(B8): 1065-1079
25. National Design Repository. Available from www.designrepository.org (accessed 23rd November 2005).
26. Nezis K., Vosniakos G. (1997). Recognising 2 1 2D shape features using a neural network and heuristics. Computer-Aided Design, 29(7): 523-539
27. Peters T.J. (1992). Encoding mechanical design features for recognition via neural nets. Research in Engineering Design, 4(1): 67-74
28. Pham D.T., Bigot S., Dimov S.S. (2003). Rules-5: A rule induction algorithm for classification problems involving continuous attributes. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 217(C12): 1273-1286
29. Pham D.T., Dimov S.S. (1997). An efficient algorithm for automatic knowledge acquisition. Pattern Recognition, 30(7): 1137-1143
30. Pham D.T., Dimov S.S. (1998). An approach to concurrent engineering. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 212(B1): 13-27
31. Prabhakar S., Henderson M.R. (1992). Automatic form-feature recognition using neural-network-based techniques on boundary representations of solid models. Computer-Aided Design, 24(7): 381-393
32. Regli W.C. (1995). Geometric algorithms for recognition of features from solid models. Ph.D. Thesis, University of Maryland, USA
33. Sakurai H., Gossard D.C. (1990). Recognizing shape features in solid models. IEEE Computer Graphics and Applications, 10(5): 22-32
34. STEP Part 21 - Clear text encoding parser to be used with JavaCC. Available from http://www.cobase.cs.ucla.edu/pub/javacc/#Ssection (accessed 23rd November 2005).
35. Trika S.N., Kashyap R.L. (1994). Geometric reasoning for extraction of manufacturing features in iso-oriented polyhedrons. IEEE Transactions on Pattern Analysis and Machine Intelligence, 16(11): 1087-1110
36. Vandenbrande J.H., Requicha A.A.G. (1993). Spatial reasoning for the automatic recognition of machinable features in solid models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(12): 1269-1285
37. Vosniakos G.C., Davies B.J. (1993). A shape feature recognition framework and its application to holes in prismatic parts. International Journal of Advanced Manufacturing Technology, 8(5): 345-351
38. Weiss, S. M., & Indurkhya, N. (1991). Reduced complexity rule induction. In Proceedings of the 12th international joint conference on artificial intelligence (IJCAI-91), Sydney, Australia. (pp. 678-684). Morgan Kaufmann, San Mateo, California USA.
39. Zulkifli A.H., Meeran S. (1999). Decomposition of interacting features using a Kohonen self-organizing feature map neural network. Engineering Applications of Artificial Intelligence, 12(1): 59-78