A framework for industrial systems modeling and simulation

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To successfully compete in a global market, manufacturing production systems are being forced to reduce time to market and to provide improved responsiveness to changes in market conditions. The organizations that comprise the business links in the production system must constantly make tradeoffs between time and cost in order to achieve a competitive but quick response to consumer demand. Due to the inherent uncertainty of consumer demand, these tradeoffs are, by definition, made with incomplete information and can incur significant financial and competitive risk to the organization. Partnerships between organizations are a mechanism for increasing the information in the decision ... continued below

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10 p.

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Macfarlane, J.; Nachnani, S.; Tsai, L.H.; Kaae, P.; Freund, K.; Hoza, M. et al. April 1, 1995.

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Description

To successfully compete in a global market, manufacturing production systems are being forced to reduce time to market and to provide improved responsiveness to changes in market conditions. The organizations that comprise the business links in the production system must constantly make tradeoffs between time and cost in order to achieve a competitive but quick response to consumer demand. Due to the inherent uncertainty of consumer demand, these tradeoffs are, by definition, made with incomplete information and can incur significant financial and competitive risk to the organization. Partnerships between organizations are a mechanism for increasing the information in the decision making process by combining information from the two partners. Partnerships are inherently difficult to implement due to trust issues. A mechanism for investigating and validating the mutual benefit to partnering would be useful in designing and implementing partnerships. This paper describes the development of a software framework for industrial systems modeling and simulation. The framework provides a mechanism for investigating changes to industrial systems in a manner which minimizes the effort and computational power needed to develop focused simulations. The architecture and it`s component parts are described.

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10 p.

Notes

OSTI as DE96002435

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  • 14. international joint conference on artificial intelligence, Montreal (Canada), 20-25 Aug 1995

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  • Other: DE96002435
  • Report No.: LBL--37181
  • Report No.: CONF-950834--2
  • Grant Number: AC03-76SF00098
  • Office of Scientific & Technical Information Report Number: 132714
  • Archival Resource Key: ark:/67531/metadc623269

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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  • April 1, 1995

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  • June 16, 2015, 7:43 a.m.

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  • April 5, 2016, 12:26 p.m.

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Macfarlane, J.; Nachnani, S.; Tsai, L.H.; Kaae, P.; Freund, K.; Hoza, M. et al. A framework for industrial systems modeling and simulation, article, April 1, 1995; California. (digital.library.unt.edu/ark:/67531/metadc623269/: accessed September 23, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.