University of Maryland
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Computer Integrated Manufacturing Laboratory

The Computer Integrated Manufacturing Laboratory is a constituent laboratory of the Institute for Systems Research at the University of Maryland.

Adaptable Simulation Models for Manufacturing

Principal Investigators:

Project Team:

Background

This project was funded as part of a collaboration entitled Enhancing Collaborative Research in Industrial and Systems Engineering. The following organizations participated in the collaboration, which was sponsored by the National Science Foundation.

Arena Production Control Simulation Model

We have created a template for use with the Arena simulation modeling software. We have shown that the use of this template increases the adaptability of manufacturing system simulation models with respect to changes in production control policy by parameterizing complex behavior.

Comprehensive instructions for the use of the template are forthcoming. In the meantime, an example of its use is provided in the following Arena model: Flow_Shop_Example.doe. The model is a realization of the example in our WSC 2001 paper (Gahagan and Herrmann, 2001, listed below). It may be modified, as in the paper, to exhibit a variety of push pull production control policies.

To use the template, download Production_Control.tpo and place it in the Arena templates directory on your local drive, C:\Program Files\Rockwell Software\Arena\Template (or something like that). You may now attach it to any Arena model.

If you have access to the Professional Edition of Arena, you may download the source code file Production_Control.tpl.

Learning Historian for Discrete Event Simulation

Please see the learning historian page for more information about this tool that facilitates learning about system behavior by making it easier to run trials and visualize the results.

Publications

  1. Herrmann, J.W., E. Lin, B. Ram, and S. Sarin, Adaptable simulation models for manufacturing, Proceedings of the 10th International Conference on Flexible Automation and Intelligent Manufacturing, Volume 2, pp. 989-995, College Park, Maryland, June 26-28, 2000.
  2. Gahagan, Sean M., and Jeffrey W. Herrmann, Improving simulation model adaptability with a production control framework, Proceedings of the 2001 Winter Simulation Conference, B.A. Peters, J.S. Smith, D.J. Medeiros, and M.W. Rohrer, eds., Arlington, Virginia, December, 2001.
  3. Chipman, Gene, Catherine Plaisant, Sean Gahagan, Jeffrey W. Herrmann, Sara Hewitt, Lakeisha Reaves, Understanding Manufacturing Systems with a Learning Historian for User-Directed Experimentation. CS-TR-4243, UMIACS-TR-2001-29, University of Maryland, College Park, 2001.
  4. Sara T. Hewitt and Jeffrey W. Herrmann, Interfaces to enhance user-directed experimentation with simulation models of discrete-event systems, to appear in Proceedings of the SCS International Conference on Simulation and Multimedia in Engineering Education, Western Multiconference on Computer Simulation, Orlando, Florida, January 19-23, 2003.
  5. Sara T. Hewitt, Comparing Analytical and Discrete-Event Simulation Models of Manufacturing Systems, M.S. Thesis, University of Maryland, 2002.
  6. Gahagan, Sean M., and Jeffrey W. Herrmann, Finding the optimal production control policy using the production control framework Proceedings of the 2005 Winter Simulation Conference, Orlando, Florida, December 4-7, 2005.
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Computer Integrated Manufacturing Laboratory

Last updated on July 15, 2005, by Jeffrey W. Herrmann.