Abstract
This work discusses important aspects in the computational representation of models, focusing on the treatment of the heterogeneity and the integration of models. The relevance of this topic lies in the necessity of achieving an efficient workflow when handling heterogeneous information structures and of giving proper answer to the involvement of new types of models driven by the increasing demand for enhanced information handling capabilities in the planning and the control of production systems.
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7. References
Arata WM, Miyagi PE. Uniform computational treatment of heterogeneous discrete-event dynamic system models. Proceedings of 9th IEEE International Conference on Emerging Technologies and Factory Automation, Lisbon, Portugal, 2003; p.47–53.
Arata WM. Miyagi PE. Formal comprehensiveness and uniformity and semantic intra and intermodel consistency in the representation of Discrete Event Dynamic System models. Proceedings of the 18th International Congress of Mechanical Engineering, COBEM 2005, Ouro Preto, Brazil, 2005.
Bolch G: Greiner S. Meer H, Trivedi KS. Queuing Networks and Markov Chains: modeling and performance evaluation with computer science applications. New York: Wiley-Interscience, 1998.
Cassandras CG. Discrete Event Systems: Modeling and Performance Analysis. Burr Ridge: Richard D. Irwin Inc, 1993
Deransart P, Cervoni L, Ed-Dbali A. Prolog: the standard: reference manual. London: Springer-Verlag, 1996.
Hasegawa K. Takahashi K. Miyagi PE. Application of the Mark Flow Graph to represent discrete event production systems and system control. Transactions of the Society of Instrument and Control Engineers 1988: 1, 69–75.
Kulkarni VG. Modeling and Analysis of Stochastic Systems. London: Chapman & Hall, 1995.
Marsan MA. Conte G, Balbo G. A class of generalized Stochastic Petri Nets for the performance evaluation of multiprocessor systems. ACM Transactions on Computer Systems 1984: 2, 93–122.
Molloy MK. Performance analysis using Stochastic Petri Kets. IEEE Transactions on Computers 1980: 9, 913–917.
Murata T. Petri Nets: Properties, Analysis and Applications. Proceedings of IEEE 1989: 4; 541–580.
Sanders WH, Courtney T, Deavours D, Daly D, Derisavi S; Lam. Multi-formalism and Multisolution-method Modeling Frameworks: The Mobius Approach. Proceedings of the Symposium on Performance Evalilation-Stories and Perspectives. Vienna, Austria, 2003: 241–256.
Trivedi KS. SHARPE 2002: Symbolic Hierarchical Automated Reliability and Performance Evaluator, Proceedings of 2002 International Conference on Dependable Systems and Networks (DSN 2002), http://csdl.computer.org/comp/proceedings/dsn/2002/1597/00/15970544.pdf.
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© 2006 International Federation for Information Processing
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Arata, W.M., Miyagi, P.E. (2006). Computational Representation, Heterogeneity and Integration of Production System Models. In: Information Technology For Balanced Manufacturing Systems. BASYS 2006. IFIP International Federation for Information Processing, vol 220. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-36594-7_43
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DOI: https://doi.org/10.1007/978-0-387-36594-7_43
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-36590-9
Online ISBN: 978-0-387-36594-7
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