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A common skeletal framework for knowledge-based solutions to a representative set of manufacturing problems

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Handbook of Expert Systems Applications in Manufacturing Structures and rules

Part of the book series: Intelligent Manufacturing Series ((IMS))

Abstract

Intelligent systems have been increasingly studied and used in the fields of flexible design and manufacture. Some recent applications include know-ledge-based systems for process planning, scheduling, facilities layout and intelligent design environments (Kumara et al, 1986; Kusiak and Chen, 1988; Steffan, 1986). The evolution of intelligent systems can be thought of as having passed through several phases. While logic and knowledge representation were the themes during the 1970s, the early 1980s were when expert systems gained popularity and the late 1980s acknowledged the development of many knowledge-based application programs as well as software tools. For the knowledge-based methods to advance, we need a deeper investigation of the fundamentals behind successful knowledge-based applications. In order to demonstrate that knowledge-based methods are not ad hoc, we need to study the common underlying themes, generalize particular solutions into problem solving methodologies, study the properties of the underlying solving structures and investigate the impact of representation. Such an investigation provides us with a framework and a deeper generic understanding of the solution methodology. This framework and understanding can be used in the new generation of intelligent systems to:

  • Evaluate the capabilities of certain classes of systems.

  • Enhance and improve the capabilities of existing and new systems through incorporation of those elements of the framework which are lacking in these systems.

  • Design new problem solving systems by applying the framework to particular problem domains and instantiating its key elements.

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References

  • Banerjee, P. (1990) An automated reasoning architecture for a representative set of human designer tasks in manufacturing systems layout organization by designing default knowledge combining linear objective optimization and non-linear qualitative analysis, PhD Dissertation ,Industrial Engineering, Purdue University.

    Google Scholar 

  • Banerjee, P., Montreuil, B., Moodie, C.L. and Kashyap, R.L. (1990a) A qualitative reasoning-based interactive optimization methodology for layout design. HE Conference Proceedings ,230–5.

    Google Scholar 

  • Chang, T.-C. and Wysk, R.A. (1985) An Introduction to Automated Process Planning Systems ,Prentice-Hall, Englewood Cliffs, NJ.

    Google Scholar 

  • Choi, B.K., Barash, M.M. and Anderson, D.C. (1984) Automatic recognition of machined surfaces from a 3D solid modelor. Computer-Aided Design 16(2), 81–6.

    Article  Google Scholar 

  • Davies, B.J. and Darbyshire, I.L. (1984) The use of expert systems in process planning. Annals of the CIRP ,33(1), 303–6.

    Article  Google Scholar 

  • Denardo, E.V. (1986) Dynamic Programming Theory and Applications ,Prentice-Hall, Englewood Cliffs, NJ.

    Google Scholar 

  • Descotte, Y. and Latombe, J.C. (1981) GARI: A Problem Solver that Plans how to Machine Mechanical Parts. IJCAI-7, pp. 766–72.

    Google Scholar 

  • Fisher, E.L. (1986) An Al-based methodology for factory design. AI Magazine ,7(4), 72–85.

    Google Scholar 

  • Flemming, U., Coyne, R., Glavin, T. and Rychener, M. (1988) A generative expert system for the design of building layouts-version 2, in Artificial Intelligence in Engineering: Design ,(ed. J.S. Gero), Elsevier, Amsterdam, pp. 445–64.

    Google Scholar 

  • Forbus, K.D. (1990) Qualitative physics: past, present, and future, in Qualitative Reasoning about Physical Systems (eds D.S. Weld and J. de Kleer), Morgan Kaufmann, San Francisco.

    Google Scholar 

  • Foulds, L.R., Gibbons, P.B. and Gifrin, J.W. (1985) Facilities layout adjacency determination: an experimental comparison of three graph theoretic heuristics. Operations Research ,33(5), 1091–106.

    Article  MATH  Google Scholar 

  • Golany, B. and Rosenblatt, M.J. (1989) A heuristic algorithm for the quadratic assignment formulation to the plant layout problem. International Journal of Production Research ,27(2), 293–308.

    Article  MATH  Google Scholar 

  • Gossard, D.C., Zuffante, R.P. and Hiroshi, S. (1988) Representing dimensions, tolerances, and features in MCAE systems. IEEE Computer Graphics and Applications ,pp. 51–9.

    Google Scholar 

  • Hassan, M.M.D. and Hogg, G.L. (1989) On converting a dual graph into a block layout. International Journal of Production Research ,27(7), 1149–60.

    Article  Google Scholar 

  • Heragu, S. and Kusiak, A. (1988) Knowledge based system for machine layout (KBML). HE Conference Proceedings ,pp. 159–64.

    Google Scholar 

  • Hummel, K.E. (1989) Coupling rule-based and object-oriented programming for the classification of Mach. Computers in Engineering ,1, 409–18.

    Google Scholar 

  • Ikeuchi, K. and Takeo, K. (1988) Automatic generation of object recognition programs. Proceedings of the IEEE ,76(8), 1016–35.

    Article  Google Scholar 

  • Jakiela, M.J. (1989) Design and implementation of a prototype ‘intelligent’ CAD system. Journal of Mechanics, Transfer and Automation in Design ,3, 252–8.

    Article  Google Scholar 

  • Karinthi, R.R. and Nau, D.S. (1989) Geometric Reasoning as a Guide to Process Planning. Proceedings of the ASME International Computers in Engineering Conference, July 30-August 3, pp. 609–16.

    Google Scholar 

  • Knoll, T.F. and Jain, R.C. (1986) Recognizing partially visible objects using feature indexed hypotheses. IEEE Journal of Robotics and Automation ,RA-2(1), 3–13.

    Google Scholar 

  • Korf, R.E. (1987) Planning as search: a quantitative approach. Artificial Intelligence, 33, 65–88.

    Article  Google Scholar 

  • Kumara, S.R.T., Joshi, S., Kashyap, R.L. et al. (1986) Expert systems in industrial engineering. International Journal Production Research ,24(5), 1107–25.

    Article  Google Scholar 

  • Kumara, S.R.T., Kashyap, R.L. and Moodie, C.L. (1988) Application of expert systems and pattern recognition methodologies to facilities layout planning. International Journal of Production Research ,26(5), 905-30. Kusiak, A. and Chen, M. (1988) Expert systems for planning and scheduling manufacturing systems. European Journal Operations Research ,34, 113–30.

    Google Scholar 

  • Liu, C.R. and Srinivasan, R. (1984) Generative process planning using syntactic pattern recognition. Computers in Mechanical Engineering ,63–6.

    Google Scholar 

  • Luby, S.C., Dixon, J.R. and Simmons, M.K. (1986) Design with features: creating and using a feature data base for evaluation of manufacturability of castings. Computers in Mechanical Engineering ,5(3), 25–33.

    Google Scholar 

  • Malakooti, B. and Tsurushima, A. (1989) An expert system using priorities for solving multiple-criteria facility layout problems. International Journal of Pro-duction Research ,27(5), 793–808.

    Article  Google Scholar 

  • Marefat, M. and Kashyap, R.L. (1990) Geometric reasoning for recognition of three dimensional object features. IEEE Transactions on Pattern Analysis and Ma-chine Intelligence TPAMI-12(10)

    Google Scholar 

  • Marefat, ML, Feghhi, S.J. and Kashyap, R.L. (1990) IDP: Automating the CAD/CAM Link by Reasoning about Shape. The Sixth Conference on Artificial Intelligence Applications, Santa Barbara, California.

    Google Scholar 

  • Marefat, M., Timke, M. and Kashyap, R.L. (1990) A Framework for Image Interpre-tation in manufacturing applications. Proceedings of IEEE International Con-ference on Systems, Man, and Cybernetics (SMC), Los Angeles, California.

    Google Scholar 

  • Minsky, M. (1963) Steps toward artificial intelligence, in Computer and Thought ,(ed. Feigenbaum and Feldman), McGraw-Hill, New York, pp. 441–3.

    Google Scholar 

  • Montreuil, B. and Ratliff, H.D. (1989) Utilizing cut trees as design skeletons for facility layout. HE Transactions ,21(2), 136–143.

    Google Scholar 

  • Montreuil, B., Venkatadri, U. and Ratliff, H.D. (1989) Generating a layout from a design skeleton. Document 89-01 ,Department of Operations &Decision Systems, Laval University, Quebec, Canada (to appear in Management Science).

    Google Scholar 

  • Mortenson, M.E. (1985) Geometric Modeling ,John Wiley &Sons, New York.

    Google Scholar 

  • Newell, A. and Simon, H.A. (1972) Human Problem Solving ,Prentice-Hall, Engle-wood Cliffs, NJ.

    Google Scholar 

  • Picone, C.J. and Wilhelm, W.E. (1984) A perturbation scheme to improve Hillier’s solution to the facilities layout problem. Management Science ,30(10), 1238–49.

    Article  MATH  Google Scholar 

  • Pinilla, J.M., Finger, S. and Prinz, F.B. (1989) Shape feature description and recognition using an augmented topology graph grammar. NSF Engineering Design Reserach Conference, June 11-14, Amherst.

    Google Scholar 

  • Requicha, A.A.G. (1980) Representations for rigid solids: theory, methods, and systems. IEEE Computer Graphics and Applications ,12(4), 45–60.

    Google Scholar 

  • Requicha, A.A.G. and Chan, S. (1986) Representation of geometric features, toleran-ces, and attributes in solid modelers based on constructive geometry. IEEE Journal of Robotics and Automation ,RA-2(3), 156–66.

    Article  Google Scholar 

  • Sacerdoti, E.D. (1974) Planning in a hierarchy of abstraction spaces. Artificial Intelligence ,5, 115–35.

    Article  MATH  Google Scholar 

  • Schank, R.C. (1982) Dynamic Memory: A Theory of Reminding and Learning in Computers and People ,Cambridge University Press, Cambridge.

    Google Scholar 

  • Scriabin, M. and Vergin, R.C. (1985) A cluster-analytic approach to facility layout. Management Science ,31(1), 33–49.

    Article  MATH  Google Scholar 

  • Shafer, G.A. (1976) A Mathematical Theory of Evidence ,Princeton University Press, Princeton, NJ.

    MATH  Google Scholar 

  • Shah, J.J. and Rogers, M.T. (1988) Expert form feature modelling shell. Computer-Aided Design ,20(9), 515–24.

    Article  Google Scholar 

  • Steffan, M.S. (1986) A survey of artificial intelligence-based scheduling systems. IIE Conference Proceedings ,395–405.

    Google Scholar 

  • Stefik, M. (1981) Planning with constraints (MOLGEN: Part 1). Artificial Intelli-gence ,16, 111–40.

    Article  Google Scholar 

  • Tsatsoulis, C. and Kashyap, R.L. (1988a) A case-based system for process planning. International Journal of Robotics and Computer-Integrated Manufacturing ,4, 557–570.

    Article  Google Scholar 

  • Tsatsoulis, C. and Kashyap, R.L. (1988a) A system for knowledge-based process planning. Artificial Intelligence in Engineering ,3(2), 66–75.

    Article  Google Scholar 

  • Wang, H.-P. and Chang, H. (1987) Automated classification and coding based on extracted surface features in a CAD data base. International Journal of Advanced Manufacturing Technology ,2(1), 25–38.

    Article  MathSciNet  Google Scholar 

  • Woo, T.C. (1982) Feature Extraction by Volume Decomposition. Proceedings of the Conference on CAD/CAM Technology in Mechanical Engineering, MIT, Mass-achusetts, pp. 76–94.

    Google Scholar 

  • You, I.C., Chu, C.N. and Kashyap, R.L. (1989) Expert system for castability evaluation using a fixed-features based approach. Robotics and Computer-Integrated Manufacturing ,6(3)

    Google Scholar 

  • Zeigler, B.P. (1990) Object-Oriented Simulation with Hierarchical Modular Models ,Academic Press, New York.

    MATH  Google Scholar 

Download references

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Marefat, M., Banerjee, P. (1994). A common skeletal framework for knowledge-based solutions to a representative set of manufacturing problems. In: Mital, A., Anand, S. (eds) Handbook of Expert Systems Applications in Manufacturing Structures and rules. Intelligent Manufacturing Series. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-0703-7_3

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  • DOI: https://doi.org/10.1007/978-94-011-0703-7_3

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-4302-1

  • Online ISBN: 978-94-011-0703-7

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