Factory flow design and analysis using internet-enabled simulation-based optimization and automatic model generation

Despite simulation offers tremendous promise for designing and analyzing complex production systems, manufacturing industry has been less successful in using it as a decision support tool, especially in the early conceptual phase of factory flow design. If simulation is used today for system design, it is more of-ten used in later phases when important design decisions have already been made and costs are locked. With an aim to advocate the use of simulation in early phases of factory design and analysis, this paper introduces FACTS Analyzer, a toolset developed based on the concept of integrating model abstraction, automatic model generation and simulation-based optimization under an innovative Internet-based plat-form. Specifically, it addresses a novel model aggregation and generation method, which when combined together with other system components, like optimization engines, can synthetically enable simulation to become much easier to use and speed up the time-consuming model building, experimentation and optimization processes, in order to support optimal decision making.

[1]  Benno Stein,et al.  Realization of Web-based simulation services , 2006, Comput. Ind..

[2]  Philip Heidelberger,et al.  Discrete event simulations and parallel processing: statistical properties , 1988 .

[3]  Jack P. C. Kleijnen,et al.  A Java-based simulation manager for Web-based simulation , 2000, 2000 Winter Simulation Conference Proceedings (Cat. No.00CH37165).

[4]  Cathal Heavey,et al.  A review of Web-based simulation and supporting tools , 2010, Simul. Model. Pract. Theory.

[5]  Hyunbo Cho,et al.  Web Services-Based Parallel Replicated Discrete Event Simulation for Large-Scale Simulation Optimization , 2009, Simul..

[6]  Richard M. Fujimoto,et al.  Parallel and Distribution Simulation Systems , 1999 .

[7]  M. Gyimesi,et al.  Web Services with generic simulation models for discrete event simulation , 2008, Math. Comput. Simul..

[8]  R.M. Fujimoto,et al.  Parallel and distributed simulation systems , 2001, Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304).

[9]  Fred W. Glover,et al.  New advances and applications for marrying simulation and optimization , 2004, Proceedings of the 2004 Winter Simulation Conference, 2004..

[10]  Fred W. Glover,et al.  Integrating optimization and simulation: research and practice , 2000, 2000 Winter Simulation Conference Proceedings (Cat. No.00CH37165).

[11]  Soundar R. T. Kumara,et al.  Simulation anywhere any time: Web-based simulation implementation for evaluating order-to-delivery systems and processes , 2002, Proceedings of the Winter Simulation Conference.

[12]  Joshua D. Knowles A summary-attainment-surface plotting method for visualizing the performance of stochastic multiobjective optimizers , 2005, 5th International Conference on Intelligent Systems Design and Applications (ISDA'05).

[13]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[14]  William E. Biles,et al.  Web based evaluation of material handling alternatives for automated manufacturing: a parallel replications approach , 2004, Proceedings of the 2004 Winter Simulation Conference, 2004..

[15]  Kaizhi Tang,et al.  Simulation applications in the automotive industry: simulation anywhere any time: web-based simulation implementation for evaluating order-to-delivery systems and processes , 2002 .

[16]  Jack P. C. Kleijnen,et al.  International collaborations in Web-based simulation: a focus on experimental design and optimization , 2005, Proceedings of the Winter Simulation Conference, 2005..

[17]  Hyunbo Cho,et al.  Determination of efficient simulation model fidelity for flexible manufacturing systems , 2005, Int. J. Comput. Integr. Manuf..

[18]  Boleslaw K. Szymanski,et al.  Research and commercial opportunities in Web-Based Simulation , 2001, Simul. Pract. Theory.

[19]  William E. Biles,et al.  Statistical considerations in simulation on a network of microcomputers , 1985, WSC '85.

[20]  Dave Stainforth,et al.  Climateprediction.net: Design Principles for Publicresource Modeling Research , 2002, IASTED PDCS.

[21]  Fred Glover,et al.  Future of simulation optimization , 2001, Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304).

[22]  Pau Klein,et al.  San Francisco, California , 2007 .