Simulation Modeling with Hierarchical Planning: Application to a Metal Manufacturing System
There has been an increasing volume of research that combines artificial intelligence (AI) and simulation in the last decade to solve the problems of various kinds, some of which are related to manufacturing systems. In modern manufacturing industries, automatic systems composed of computers are common, and these systems are continuing to enhance the efficiency of the manufacturing process by analyzing the overall production process – from design to manufacturing. This paper deals with the problem regarding how to improve the productivity of a metal grating manufacturing system. To solve this problem, we proposed and applied Hierarchical RG-DEVS formalism, which is a modeling methodology for incorporating the hierarchical regression planning of AI and simulation, for constructing an environment for sound modeling. This research presents not only an improvement of the metal production design environment that can predict efficiency in the manufacturing process, but also a cooperation technique for AI planning and simulation.
KeywordsTarget System Modeling Methodology State Transition Diagram Welding Type Hierarchical Planning
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- 1.Zeigler, B.P., Cho, T.H., Rozenblit, J.W.: A Knowledge-Based Simulation Environment for Hierarchical Flexible Manufacturing. IEEE Transactions on Systems, Man and Cybernetics 26(1) (1996)Google Scholar
- 2.Cho, T.H., Zeigler, B.P.: Simulation of Intelligent Hierarchical Flexible Manufacturing: Batch Job Routing in Operation Overlapping. IEEE Transactions in Systems, Man, and Cybernetics 27(1) (1997)Google Scholar
- 4.Allen, J.F.: Towards General Theory of Action and Time. Artificial Intelligence 23 (1984)Google Scholar
- 5.Kwon, Y., Park, H., Jung, S., Kim, T.: Fuzzy-DEVS Formalism: Concepts, Realization and Applications. AI, Simulation and Planning in High Autonomy Systems, EPD, University of Arizona, San Diego (1996)Google Scholar
- 6.Lee, K.: Principles of CAD/CAM/CAE Systems. Addison Wesley Longman, Amsterdam (1999)Google Scholar
- 7.Cho, Y.S.: Construction of efficient CAD environment (2000)Google Scholar
- 8.Hetem, V.: Communication: Computer Aided Engineering in the Next Millennium. Computer-Aided Design 32(5-6) (2000)Google Scholar
- 9.Kalyan-Seshu, U.S., Bras, B.: Towards Computer Aided Design for the Life Cycle. In: IEEE International Symposium on Electronics and the Environment, Oak Brook, Illinois, USA (1998)Google Scholar
- 10.Szykman, S., Fenves, S.J., Keirouz, W., Shooter, S.B.: A Foundation for Interoperability in Next-generation Product Development Systems. Computer-Aided Design 33(7) (2001)Google Scholar
- 11.Zeigler, B.P., Praehofer, H., Kim, T.G.: Theory of Modeling and Simulation: Integrating Discrete Event and Continuous Complex Dynamic Systems, San Diego, California (2000)Google Scholar
- 12.Cho, T.H.: Embedding Intelligent Planning Capability to DEVS Models by Goal Regression Method. Simulation Transactions of The Society for Modeling and Simulation International 78(12) (December 2002)Google Scholar