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Optimized process planning by generative simulated annealing

Published online by Cambridge University Press:  27 February 2009

K.N. Brown  and
J. Cagan
K.N. Brown
Affiliation:
Department of Computing Science, University of Aberdeen, Aberdeen AB24 3UE, U.K.
J. Cagan
Affiliation:
Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, U.S.A.
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Abstract

Manufacturing process planning is a difficult problem with a prohibitively large search space. It is normally tackled by decomposing goal objects into features, and then sequencing features to obtain a plan. This paper investigates an alternative approach. The capabilities of a manufacturing process are represented by a formal language of shape, in which sentences correspond to manufacturable objects. The language is interpreted to describe process plans corresponding to the shape generation, complete with cost estimates. A macro layer that describes single operations of the machine is implemented on top of the formal language. The space it describes is searched by the generative simulated annealing algorithm, a stochastic search technique based on simulated annealing. Plans that are close to the optimum are generated in reasonable time.

Keywords

Process PlanningSimulated AnnealingShape GrammarSemanticsOptimization

Information

Type
Articles
Information
AI EDAM , Volume 11 , Issue 3 , June 1997 , pp. 219 - 235
Copyright
Copyright © Cambridge University Press 1997

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References

REFERENCES

Brown, K.N., & Cagan, J. (1996). Modified shape annealing for optimally-directed generation: Initial results. In Advances in Formal Design Methods for CAD, (Gero, J.S., Ed.), pp. 59–73. IFIP and Chapman and Hall, London.CrossRefGoogle Scholar
Brown, K.N., McMahon, C.A., & Sims Williams, J.H. (1994 a). A formal language for the design of manufacturable objects. In Formal Design Methods for CAD (B-18), (Gero, J.S. and Tyugu, E., Eds.), pp.135–155. North Holland, Amsterdam.Google Scholar
Brown, K.N., McMahon, C.A., & Sims Williams, J.H. (1994 b). Constraint unification grammars: Specifying languages of parametric designs. In Artificial Intelligence in Design '94, (Gero, J.S. and Sudweeks, F., Eds.), pp. 239–256. Kluwer, Dordrecht.Google Scholar
Brown, K.N., McMahon, C.A., & Sims Williams, J.H. (1995).Features, aka the semantics of a formal language of manufacturing. Res. Eng. Design 7, 151–172.CrossRefGoogle Scholar
Brown, K.N., McMahon, C.A., & Sims Williams, J.H. (1996). Describing process plans as the formal semantics of a language of shape. Artif. Intel. Eng. 10, 153–169.CrossRefGoogle Scholar
Brown, K.N., Sims Williams, J.H., & McMahon, C.A. (1992). Grammars of features in design, In Artificial Intelligence in Design '92, (Gero, J.S., Ed.), pp.287–306. Kluwer Academic Publishers, The Netherlands.Google Scholar
Cagan, J., & Kotovsky, K. (1997). “Simulated annealing and the generation of the objective function: A model of learning during problem solving. Computational Intell. (accepted).CrossRefGoogle Scholar
Cagan, J., & Mitchell, W.J. (1993). Optimally directed shape generation by shape annealing. Environ. Plann. B 20, 5–12.CrossRefGoogle Scholar
Chang, T.C., & Wysk, R.A. (1985). An introduction to automated process planning. Prentice-Hall, Englewood Cliffs, New Jersey.Google Scholar
Chuang, S.-H., & Henderson, M.R. (1991). Compound feature recognition by web grammar parsing. Res. Eng. Design 2(3),147–158.CrossRefGoogle Scholar
Finger, S., & Rinderle, J.R. (1990). Transforming behavioural and physical representations of mechanical designs. Proc. First Int. Workshop Formal Methods in Eng. Design, Manufact. Assembly, pp.133–151. Department of Mechanical Engineering, Colorado State University, Fort Collins, Colorado.Google Scholar
Finger, S., & Safier, S.A. (1990). Representing and recognizing features in mechanical designs. Second Int. Conf. Design Theor. Methodol. DTM '90.CrossRefGoogle Scholar
Fitzhorn, P.A. (1990). Formal graph languages of shape. AIEDAM 4(3), 151–164.CrossRefGoogle Scholar
Flemming, U. (1987). More than the sum of their parts: The grammar of Queen Anne Houses. Environ. Plann. B 14, 323–350.CrossRefGoogle Scholar
Fu, Z., & de Pennington, A. (1991). Geometric reasoning based on graph-grammar parsing. 1991 ASME Design Automation Conf.CrossRefGoogle Scholar
Gaschnig, J. (1979). Performance measurement and analysis of certain search algorithms. Report No. CMU–CS–79–124.Google Scholar
Green, R.E. (Ed.). (1992). Machinery's handbook. Industrial Press, New York.Google Scholar
Harvey, W.D. (1995). Non-systematic backtracking search. PhD Dissertation. Department of Computer Science, University of Stanford, Stanford, California.Google Scholar
Hayes, C.C., & Wright, P.K. (1989). Automating process planning: Using feature interactions to guide search. J. Manufact. Syst. 8(1), 1–15.CrossRefGoogle Scholar
Huang, M.D., Romeo, R., & Sangiovanni-Vincentelli, A. (1986). An efficient general cooling schedule for simulated annealing algorithm. Proc. 1986 IEEE Int. Conf. CAD, 381–384.Google Scholar
Husbands, P., & Mill, F. (1991). Simulated co-evolution as the mechanism for emergent planning and scheduling. Proc. Fourth Int. Conf. Genet. Algorithms, pp.264–270. Morgan Kaufmann, Los Altos, California.Google Scholar
Joshi, S., & Chang, T.C. (1988). Graph-based heuristics for recognition of machined features from a 3D solid model. CAD 20(2), 58–66.Google Scholar
Kirkpatrick, S., Gelatt, C.D. Jr, & Vecchi, M.P. (1983). Optimization by simulated annealing. Science 220(4598), 671–679.CrossRefGoogle ScholarPubMed
Knuth, D. (1968). Semantics of context-free languages. Math. Syst. Theory 2, 127–145.CrossRefGoogle Scholar
Marefat, M., & Britanik, J. (1996). Automated reuse of solutions in manufacturing process planning through a case-based approach. Proc. 1996 ASME Design Eng. Tech. Conf. Comput. Eng.CrossRefGoogle Scholar
Nau, D.S., Gupta, S.K., & Regli, W.C. (1995). AI planning versus manufacturing-operation planning: A case study. IJCAI-95, pp. 1670–1676.Google Scholar
Opitz, H. (1970). Classification system to describe workpieces. Pergamon Press, Oxford.Google Scholar
Penjam, J. (1990). Computational and attribute models of formal languages. Theor. Comput. Sci. 71, 241–264.CrossRefGoogle Scholar
Reddy, G., & Cagan, J. (1995). An improved shape annealing algorithm for truss topology generation. ASME J. Mechanical Design 117(2A), 315–321.CrossRefGoogle Scholar
Rinderle, J.R. (1991). Grammatical approaches to engineering design, part II: Melding configuration and parametric design using attribute grammars. Res. Eng. Design 2(3), 137–146.CrossRefGoogle Scholar
Schmidt, L.C., & Cagan, J. (1995). Recursive annealing: A computational model for machine design. Res. Eng. Design 7, 102–125.CrossRefGoogle Scholar
Selman, B., Levesque, H., & Mitchell, D. (1992). A new method for solving hard satisfiability problems. Proc. Tenth Nat. Conf. Artif. Intell. (AAAI-92), pp. 440–446.Google Scholar
Shah, J.J. (1991). Conceptual development of form features and feature modelers. Res. Eng. Design 2, 93–108.CrossRefGoogle Scholar
Shah, J.J., & Bhatnagar, A.S. (1989). Group technology classification from feature-based geometric models. Manufact. Rev. 2(3), 204–213.Google Scholar
Srikantappa, A.B., & Crawford, R.H. (1992). Intermediate geometric and interfeature relationships for automatic group technology part coding. Proc. ASME Comput. Eng. Conf., pp. 245–251.CrossRefGoogle Scholar
Stiny, G. (1980). Introduction to shape and shape grammars. Environ. Plann B. 7,343–351.CrossRefGoogle Scholar
Stiny, G. (1981). A note on the description of designs. Environ. Plann. B 8, 257–267.CrossRefGoogle Scholar
Stiny, G. (1991). The algebras of design. Res. Eng. Design 2(3), 171–181.CrossRefGoogle Scholar
Stiny, G., & Mitchell, W.J. (1978). The palladian grammar. Environ. Plann. B 5, 5–18.CrossRefGoogle Scholar
Szykman, S., & Cagan, J. (1993). Automated generation of optimally directed three dimensional component layouts. DE–Vol 65–1, Adv. Design Automation, pp. 527–537.CrossRefGoogle Scholar
Szykman, S., & Cagan, J. (1995). A simulated annealing approach to three dimensional component packing. ASME J. Mech. Design 117(2A), 308–314.CrossRefGoogle Scholar