Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30174
Abstraction Hierarchies for Engineering Design

Authors: Esra E. Aleisa, Li Lin

Abstract:

Complex engineering design problems consist of numerous factors of varying criticalities. Considering fundamental features of design and inferior details alike will result in an extensive waste of time and effort. Design parameters should be introduced gradually as appropriate based on their significance relevant to the problem context. This motivates the representation of design parameters at multiple levels of an abstraction hierarchy. However, developing abstraction hierarchies is an area that is not well understood. Our research proposes a novel hierarchical abstraction methodology to plan effective engineering designs and processes. It provides a theoretically sound foundation to represent, abstract and stratify engineering design parameters and tasks according to causality and criticality. The methodology creates abstraction hierarchies in a recursive and bottom-up approach that guarantees no backtracking across any of the abstraction levels. The methodology consists of three main phases, representation, abstraction, and layering to multiple hierarchical levels. The effectiveness of the developed methodology is demonstrated by a design problem.

Keywords: Hierarchies, Abstraction, Loop-free, Engineering Design

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1330561

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1107

References:


[1] Lam, K.P., "Hierarchical Method for Large-Scale Two-Dimensional Layout". Journal of Mechanical Design, 1983. 105(2): p. 242-248.
[2] Sebastia, L., E. Onaindia, and E. Marzal, Decomposition of planning problems". Ai Communications, 2006. 19(1): p. 49-81.
[3] Holte, R.C. and B.Y. Choueiry, "Abstraction and reformulation in artificial intelligence". Philosophical Transactions of the Royal Society of London Series B-Biological Sciences, 2003. 358(1435): p. 1197-1204.
[4] Goldin, S.E. and P. Klahr. Learning and Abstraction in Simulation. in International Joint Conference on Artificial Intelligence. 1981: American Assoc for Artificial Intelligence.
[5] Sacerdoti, E., "Planning in a Hierarchy of Abstraction Spaces". Artificial Intelligence, 1974. 5(2): p. 115-135.
[6] Taylor, L.E. and M.R. Henderson. Roles of features and abstraction in mechanical design. in 6th International Conference on Design Theory and Methodology American Society of Mechanical Engineers, Design Engineering Division (Publication) DE. 1994. New York, NY: ASME.
[7] Reddy, S.Y., "Learning abstract models for system design". Ai Edam- Artificial Intelligence for Engineering Design Analysis and Manufacturing, 1996. 10(2): p. 167-169.
[8] Hoover, S.P. and J.R. Rinderle. Abstractions, design views and focusing. in 6th International Conference on Design Theory and Methodology American Society of Mechanical Engineers, Design Engineering Division (Publication) DE. 1994: ASME, New York, NY.
[9] Sarjoughian, H.S., B.P. Zeigler, and F.E. Cellier. Evaluating model abstractions: A quantitative approach. in Proceedings of SPIE Enabling Technology for Simulation Science II. 1998. Orlando, FL, United States.
[10] Kiran, A.S., T. Cetinkaya, and J. Cabrera, "Hierarchical modeling of a shipyard integrated with an external scheduling application". Winter Simulation Conference Proceedings, 2001. 2: p. 877-881 (IEEE cat n 01CH37304).
[11] McGraw, R.M. and R.A. MacDonald, "Abstract modeling for engineering and engagement level simulations". Winter Simulation Conference Proceedings, 2000. 1: p. 326-334.
[12] Zeigler, B.P., "Hierarchical, Modular Discrete-Event Modelling in an Object-Oriented Envirionment". Simulation, 1987. 49(5): p. 219-230.
[13] Lin, J.T., K.C. Yeh, and L.C. Sheu, "A context-based object-oriented application framework for discrete event simulation". Computers & Industrial Engineering, 1996. 30(4): p. 579-597.
[14] Praehofer, H., "Object oriented, modular hierarchical simulation modeling: towards reuse of simulation code". Simulation Practice & Theory, 1996. 4(4): p. 4.
[15] Pidd, M. and R.B. Castro. Hierarchical modular modelling in discrete simulation. in Winter Simulation Conference. 1998: IEEE, Piscataway, NJ.
[16] Chen, S.-J., "Project task coordination and team organization in concurrent engineering", in Department of Industrial Engineering. 1999, State University of New York at Buffalo: Buffalo, NY.
[17] Knoblock, C., "Automatically generating abstractions for planning". Artificial Intelligence, 1994. 68(2 Aug): p. 243-302.
[18] Giunchiglia, F. and T. Walsh, "A Theory of Abstraction". Artificial Intelligence, 1992. 57(2-3): p. 323-389.
[19] Armano, G., G. Cherchi, and E. Vargiu, "Planning by abstraction using HW
[], in Book" in Planning by abstraction using HW
[]. 2003. p. 349-361.
[20] Fishwick, P.A., "Role of Process Abstraction in Simulation". IEEE Transactions on Systems, Man & Cybernetics, 1988. 18(1): p. 18-39.
[21] Fishwick, P.A., Simulation model design and execution : building digital worlds. Prentice-Hall international series in industrial and systems engineering. 1995, Englewood Cliffs, N.J.: Prentice Hall. xvi, 448 p.
[22] Holte, R.C., et al., "Speeding up problem solving by abstraction: a graph oriented approach". Artificial Intelligence, 1996. 85(1-2 Aug): p. 321-361. World Academy of Science, Engineering and Technology 21 2008
[23] Caughlin, D. and A.F. Sisti. A summary of model abstraction techniques. in Proceedings of SPIE - The International Society for Optical Engineering. 1997: SPIE.
[24] Sisti, A.F. and S.D. Farr. Model abstraction techniques: an intuitive overview. in National Aerospace and Electronics Conference, Proceedings of the IEEE 1998. 1998: IEEE, Piscataway, NJ.
[25] Giunchiglia, F., "Using Abstrips abstractions - Where do we stand?". Artificial Intelligence Review, 1999. 13(3): p. 201-213.
[26] Minton, S., "Learning Effective Search Control Knowledge: An Explanation-Based Approach". 1988, Carnegie-Mellon University. p.231.
[27] Yang, Q. and J. Tenenberg. Abtweak: Abstracting a Nonlinear, Least Commitment Planner. in Proceedings of the 8th National Conference on Artificial Intelligence. 1990. Boston, MA.
[28] Christensen, J., "Automatic Abstraction in Planning", in Department of Computer Science. 1991, Stanford University: Stanford, Ca. p. 153.
[29] Bacchus, F. and Q. Yang. Expected value of hierarchical problemsolving. in AAAI-92. 1992.
[30] Friske, L.M. and C.H.C. Ribeiro, "Planning under uncertainty with abstraction hierarchies, in Book" in Planning under uncertainty with abstraction hierarchies. 2006. p. 1057-1066.
[31] Marie, d., R. Priyang, and G. Lise, "Learning structured Bayesian networks: combining abstraction hierarchies and tree-structured conditional probability tables". Computational Intelligence, 2008. 24(1):p. 1.
[32] Knoblock, C. Search reduction in hierarchical problem solving. in AAAI. 1991. Anaheim, CA.
[33] Bacchus, F. and Q. Yang, "Downward refinement and the efficiency of hierarchical problem solving". Artificial Intelligence, 1994. 71(1 Nov): p. 43-100.
[34] Helmert, M., "The Fast Downward planning system". Journal of Artificial Intelligence Research, 2006. 26: p. 191-246.
[35] Gimenez, O. and A. Jonsson, "The complexity of planning problems with simple causal graphs". Journal of Artificial Intelligence Research, 2008. 31: p. 319-351.
[36] Bylander, T., "Computational complexity of propositional STRIPS planning". Artificial Intelligence, 1994. 69(1-2): p. 165-204.
[37] Kemke, C. and E. Walker, "Planning with action abstraction and Plan Decomposition Hierarchies". 2006 Ieee/Wic/Acm International Conference on Intelligent Agent Technology, Proceedings, 2006: p. 447- 451.
[38] Kemeny, J.G. and J.L. Snell, Finite markov chains. 1960, Princeton, N.J.,: Van Nostrand. 210 p.
[39] Dartmouth College Writing Group and E. Cogan, Modern mathematical methods and models; a book of experimental text materials. Vol. 2. 1958, Ann Arbor, MI.
[40] Gaver, D.P. and G.L. Thompson, Programming and probability models in operations research. 1973, Monterey, Ca: Brooks/Cole Pub. Co. xiii,683 p.
[41] Russell, S.J. and P. Norvig, Artificial intelligence : a modern approach. Prentice Hall series in artificial intelligence. 1995, Englewood Cliffs, N.J.: Prentice Hall. xxviii, 932 p.
[42] Chen, S.J. and L. Lin, "A project task coordination model for team organization in concurrent engineering". Concurrent Engineering- Research and Applications, 2002. 10(3): p. 187-202.