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Reusability-based selection of parametric finite element analysis models

Published online by Cambridge University Press:  11 February 2009

Nsikan Udoyen
Affiliation:
Systems Realization Laboratory, George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
David W. Rosen
Affiliation:
Systems Realization Laboratory, George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA

Abstract

A selection method to support adaptive reuse of parametric finite element analysis (FEA) models is introduced in this paper. Adaptive reuse of engineering artifacts such as FEA models is common in product design, but difficult to automate because of the need to integrate new information. The proposed method factors reusability into selection by evaluating models based on comparative estimates of effort involved in adapting them for reuse to model a query problem. The method is developed for FEA models of component-based designs. FEA modeling of electronic chip packages is used to illustrate the method's usefulness. We conclude with a discussion on the method's advantages and limitations and highlight important issues for further research.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2009

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References

REFERENCES

Amkor, . (2006). PBGA data sheet. Accessed February 26, 2006, at http://www.amkor.com/products/alldatasheets/PBGA.pdfGoogle Scholar
Arabshahi, S., & Barton, D.C. (1991). Towards integrated design and analysis. Finite Elements in Analysis and Design 9, 271293.CrossRefGoogle Scholar
ASAT. (2006). LPCC application notes. Accessed February 27, 2006, at http://www.asat.com/products/data/appsnotes/lpcc_ apps_04.pdfGoogle Scholar
Azuaje, F., Dubitzky, W., Black, N., & Adamson, K. (2000). Retrieval strategies for case-based reasoning: a categorized bibliography. The Knowledge Engineering Review 15, 371379.CrossRefGoogle Scholar
Basili, V.R., & Rombach, H.D. (1991). Support for comprehensive reuse. Software Engineering Journal 6 (5), 303316.CrossRefGoogle Scholar
Chabanas, M., & Promayon, E. (2004). Physical modeling language: towards a unified representation for continuous and discrete models. Int. Symp. Medical Simulation, pp. 256266.CrossRefGoogle Scholar
Coombs, C.F. (1996). Printed Circuit Handbook. New York: McGraw–Hill.Google Scholar
Deletage, J., Fenech, A., Bechou, L., Ousten, Y., Danto, Y., Salagoity, M., Faure, C., & Rao, S. (1996). Thermomechanical behavior of ceramic ball grid array based on experiments and FEM stimulations. IEEE/CPMT Int. Electronics Manufacturing Symp., pp. 9198.CrossRefGoogle Scholar
Etzkorn, L.H., Hughes, W.E., & Davis, C.G. (2001). Automated reusability quality analysis of OO legacy software. Information and Software Technology 43, 295308.CrossRefGoogle Scholar
Fairchild Semiconductor. (2006). FLMP design guide. Accessed February 27, 2006, at http://www.fairchildsemi.com/ collateral/flmp_designguide.pdfGoogle Scholar
Fenves, S.J., & Turkiyyah, G. (1996). Knowledge-based assistance for finite element modeling. IEEE Expert 11, 2332.Google Scholar
Finn, D.P. (1993). A physical modeling assistant for the preliminary stages of finite element analysis. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 7, 275286.CrossRefGoogle Scholar
Freeman, P., & Prieto-Diaz, R. (1987). Classifying software for reusability. IEEE Software 4 (1), 616.Google Scholar
Fujio, H. (2003). The Feelfem system: a repository system for the finite element method. Int. Parallel and Distributed Processing Symp., p. 254. Nice: IEEE.Google Scholar
Fujitsu. (2006). EBGA. Accessed February 27, 2006, at http://www.fujitsu.com/downloads/MICRO/fma/pdf/enchancedpkg.pdfGoogle Scholar
Grosse, I.R., Milton-Benoit, J.M., & Wileden, J.C. (2005). Ontologies for supporting engineering analysis models. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 19,118.CrossRefGoogle Scholar
Gustafsson, G., Guven, I., Kradinov, V., & Madenci, E. (2000). Finite element modeling of BGA packages for life prediction. IEEE Electronic Components and Technology Conf., pp. 10591063.Google Scholar
Hanna, C., Raghunathan, R., & Sitaraman, S. (2000). Development of virtual reliability methodology for area-array devices used in implantable and automotive applications. IEEE Transactions on Components and Packaging Technologies 23 (3), 452461.Google Scholar
Inoue, K., Yokomori, R., Yamamoto, T., Matsushita, M., & Kusumoto, S. (2005). Ranking significance of software components based on use (relations. IEEE Transactions on Software Engineering 31 (3), 213225.CrossRefGoogle Scholar
Kashyap, V., & Sheth, A. (2000). Information Brokering Across Heterogenous Digital Data: A Metadata-Based Approach. Boston: Kluwer Academic.CrossRefGoogle Scholar
Lee, W.W., Nguyen, L.T., & Selvaduray, G.S. (2000). Solder joint fatigue models: review and applicability to chip scale packages. Microelectronics Reliability 40, 231244.CrossRefGoogle Scholar
LSI Logic. (2006). Flip chip ball grid array 4-layer (FPBGA-4L) package family. Accessed May 10, 2006, at http://www.lsilogic.com/files/docs/marketing_docs/asic/FPBGA-4Lps.pdfGoogle Scholar
Mackie, R.I. (1999). Object-oriented finite element programming—the importance of data modeling. Advances in Engineering Software 30, 775782.CrossRefGoogle Scholar
McMahon, C.A., Pitt, D.J., Yang, Y., & Sims Williams, J.H. (1995). An information management system for informal design data. Engineering with Computers 11, 123135.CrossRefGoogle Scholar
Menken, M. jCLIPS. Accessed November 22, 2005, at http://www.cs.vu.nl/~mrmenken/jclips/Google Scholar
Nagasawa, S., Nomura, M., Miyata, Y., & Sakuta, H. (1995). Development of a retrieval system for case data of finite element modeling. Int. Computers in Engineering Conf. Database Management Symp., pp. 245253. Boston: ASME.Google Scholar
Nelson, P.R., Poltrock, S.E., & Schuler, D. (1996). Industrial strength hypermedia: managing engineering information with hypermedia. SIGOIS Bulletin 17 (2), 1833.CrossRefGoogle Scholar
Pang, J.H.L., & Chong, D.Y.R. (2001). Flip chip on board solder joint reliability analysis using 2-D and 3-D FEA models. IEEE Transactions on Advanced Packaging 24 (4), 499506.CrossRefGoogle Scholar
Pang, J.H.L., Wang, Z.P., & Seetoh, C.W. (2000). CBGA solder joint reliability evaluation based on elastic-plastic-creep analysis. Journal of Electronic Packaging 122, 255261.CrossRefGoogle Scholar
Peak, R.S. (1993). Product model-based analysis models: a new representation of engineering analysis models. PhD Thesis. Georgia Institute of Technology.Google Scholar
Peak, R.S., Scholand, A., Tamburini, D., & Fulton, R.E. (1999). Towards the routinization of engineering analysis to support product design. International Journal of Computer Applications in Technology 12 (1), 115.CrossRefGoogle Scholar
Pearson, S. (1996). Economical management of engineering information. ISA Transactions 35 (1), 38.CrossRefGoogle Scholar
Peng, J., Liu, D., & Law, K.H. (2003). An engineering data access system for a finite element program. Advances in Engineering Software 34, 163181.CrossRefGoogle Scholar
Plate, T.O. (2000). Analogy retrieval and processing with distributed vector representations. Expert Systems 17, 2940.CrossRefGoogle Scholar
Qu, Y., & Yao, Q. (1999). Three-dimensional versus two-dimensional finite element modeling of flip-chip packages. Journal of Electronic Packaging 121, 196201.Google Scholar
Riley, G. (2005). CLIPS. Accessed November 22, 2005, at http://www.ghg.net/clips/CLIPS.htmlGoogle Scholar
Shephard, M.S., & Wentorf, R. (1994). Toward the implementation of automated analysis idealization control. Applied Numerical Mathematics 14, 105124.CrossRefGoogle Scholar
Shklar, L., Sheth, A., Kashyap, V., & Shah, K. (1995). InfoHarness: use of automatically generated metadata for search and retrieval of heterogenous information. Proc. 7th Int. Conf. CAiSE'95 on Advanced Information Systems Engineering (Iivari, J., Lyytinen, K., & Rossi, M., Eds.), Vol. 932, pp. 217230. Jyväskylä, Finland: Springer–Verlag. Accessed at citeseer.ist.psu.edu/article/shklar95infoharness.htmlCrossRefGoogle Scholar
Udoyen, N. (2006). Information modeling for intent-based retrieval of finite element analysis models. PhD Thesis. Georgia Institute of Technology.Google Scholar
Udoyen, N., & Rosen, D.W. (2006). Description logic representation of finite element analysis models for automated retrieval. ASME Int. Design Engineering Technical Conf., Computers and Information in Engineering Conf., pp. 603616, Paper No. DETC2006-99451. Philadelphia, PA: ASME.Google Scholar
Yong, L., Irving, S., Tumulak, M., & Cabahug, A.E. (2002). Assembly process induced stress analysis for new FLMP package by 3D FEA. IEEE Electronic Components and Technology Conf., pp. 604610.CrossRefGoogle Scholar