Abstract
Modern engineering design, analysis and manufacturing activities rely heavily on software to handle increasing volumes of data and model complexity. Automated Feature Recognition (AFR) technologies are highly demanded by manufacturing sectors since AFR can efficiently improve the performance of Computer-Aided Design (CAD) processes and reduce costs. Nevertheless, most existing FR applications are confronting various problems of processing CAD models in the manufacturing industry, such as aerospace and automobile industries. The missing link between CAD models and knowledge-based tools is one of the major obstacles. This research project investigates the feasibility and benefits of bridging the gap between knowledge based mechanisms and CAD models, and suggests a knowledge-based AFR approach for tackling AFR problems occurring in the computer-aid manufacturing design process. The AFR system significantly reduces time and costs of analysing CAD models for downstream design processes.
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References
Lockett, H.L.: A Knowledge Based Manufacturing Advisor for CAD. PhD thesis, pp. 23 –40. Cranfield University (2005)
Zhang, H.L., Van der Velden, C., Yu, X., Jones, T., Fieldhouse, I., Bil, C.: Developing A Rule Engine for Automated Feature Recognition from CAD Models. In: Proc. of IEEE IECON, Porto, Portugal, pp. 3925–3930. IEEE Press, Los Alamitos (2009)
Sadaiah, M., Yadav, D.R., Mohanram, P.V., Radhakrishnan, P.: A generative CAPP system for prismatic components. Int. J. of Ad. Manu. Tech. 20, 709–719 (2002)
Bouzakis, H.K.-D., Andreadis, G.: A Feature-based Algorithm for Computer Aided Process Planning for Prismatic Parts. International Journal of Production Engineering and Computers 3(3), 17–22 (2000)
Babic, B., Nesic, N., Miljkovic, Z.: A Review of Automated Feature Recognition With Rule-based Pattern Recognition. Computers in Industry 59, 321–337 (2008)
Joshi, S., Chang, T.C.: Graph-based Heuristics for Recognition of Machined Features from a 3D Solid Model. In: Computer-Aided Design, vol. 20(2), pp. 58–66 (1988)
Dimov, S.S., Brousseau, E.B., Setchi, R.: A Hybrid Method for Feature Recognition in Computer-Aided Design Models. Journal of Engineering Manufacture 221, 79–96 (2007)
Subrahmanyam, S., Wozny, M.: An Overview of Automatic Feature Recognition Techniques for Computer-Aided Process Planning. In: Computers in Industry, vol. 26, pp. 1–21. Elsevier, Amsterdam (1995)
Kailash, S.B., Zhang, Y.F., Fuh, J.Y.H.: A Volume Decomposition Approach to Machining Feature Extraction of Casting and Forging Components. In: Computer-Aided Design, vol. 33(8), pp. 605–617. Elsevier Publication, Amsterdam (2001)
Ding, L., Yue, Y.: Novel ANN-based Feature Recognition Incorporating Design by Features. In: Computers In Industry, vol. 55, pp. 197–222. Elsevier Publication, Amsterdam (2004)
Marquez, M., Gill, R., White, A.: Application of Neural Networks in Feature Recognition of Mould Reinforced Plastic Parts. In: Concurrent Engineering: Research and Applications, vol. 7(2), pp. 115–122. SAGE Publication, Newbury Park (1999)
Chen, Y.-M., Wen, C.-C., Ho, C.T.: Extraction of geometric characteristics for manufacturability assessment. In: Robotics and Computer-Integrated Manufacturing, vol. 19(4), pp. 371–385. Elsevier Publication, Amsterdam (2003)
Yuen, C.F., Wong, S.Y., Venuvinod, P.K.: Development of a Generic Computer-Aided Process Planning Support System. Journal of Materials Processing Technology 139, 394–401 (2003)
Liebowitz, J.: Knowledge Management and its Link to Artificial Intelligence. In: Expert Systems with Applications, vol. 20, pp. 1–6. Elsevier Publication, Amsterdam (2001)
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Zhang, H.L., Van der Velden, C. (2011). Utilizing Knowledge Based Mechanisms in Automated Feature Recognition Processes. In: Hu, B., Liu, J., Chen, L., Zhong, N. (eds) Brain Informatics. BI 2011. Lecture Notes in Computer Science(), vol 6889. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23605-1_32
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