Ubiquitous Operations Research in Production Systems

  • Leon F. McGinnisEmail author
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 200)


Fifty years ago, young operations research (OR) professionals, like Dr. Salah Elmaghraby, were exploring the opportunities for using OR to better understand how to make critical decisions about the design and operation of complex production systems. Elmaghaby’s seminal text, The Design of Production Systems, is an inimitable example of that exploration, combining deep knowledge of both the mathematical tools of OR and the application domain. Today, deployment of OR in production systems, by and large, continues to follow a pattern established by those early pioneers of the discipline—an OR expert (or team) studies the problem of interest and crafts a model to answer a specific question. The tools used, of course, have matured tremendously in the past 50 years, and contemporary computational capabilities allow the analysis of very large and complex systems. Yet the essential application process remains that of an artisan (“one who produces something (such as cheese or wine) in limited quantities often using traditional methods” (anonymous 2011a)). This chapter argues that it is time for the OR community to augment the artisanal approach by using technologies emerging in computer science to “industrialize” those OR applications in production systems that are well understood, creating a reusable platform for innovation that enables broader and deeper penetration of OR methods and tools in the support of production systems decision making.


Operation Research Modeling Language Unify Modeling Language Model Transformation Domain Expert 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



While I alone am responsible for what I write, the ideas expressed in this chapter have been strongly influenced by my involvement with PDES, Inc. as a Board Member representing Georgia Tech’s Manufacturing Research Center, by my collaborations with Dr. Chris Paredis and Dr. Russell Peak in the Model-Based Systems Engineering Center at Georgia Tech, and by my work on MBSE with a number of for user and current graduate students at Georgia Tech, including Dr. Edward Huang, Dr. Ky Sang Kwon, and Mr. George Thiers, as well as by working with two excellent postdoctoral fellows, Dr. Volkan Ustun and Dr. Ola Batarseh. This work has been supported by a variety of sponsors, including the Gwaltney Professorship, Lockheed Martin, Rockwell Collins, General Electric Energy Systems, Boeing, and DARPA.


  1. Anonymous. (2011a). Artisan. Accessed 26 Dec 2011.
  2. Anonymous. (2012a). Software factory. Accessed 4 Jan 2012.Google Scholar
  3. Batarseh, O., McGinnis, L., & Lorenz, J. (2012). MBSE supports manufacturing system design, The 22nd Annual INCOSE International Symposium Proceedings, Rome, Italy.Google Scholar
  4. Bloom, E. D., et al. (1969). High-energy inelastic e-p scattering at 6° and 10°. Physical Review Letters, 23(16), 930–934.Google Scholar
  5. Box, G. E. P., & Deaper, N. R. (1987). Empirical model-building and response surfaces (p. 424). Wiley.Google Scholar
  6. Chungoora, N., Cutting-Decelle, A.-F., Young, R. I. M., Gunendran, G., Usman, Z., Harding, J. A., & Case, K. (2011). Towards the ontology-based consolidation of production-centric standards, International Journal of Production Research, 51(2), 327–345.Google Scholar
  7. Dieng, R. (2000). Knowledge management and the internet. Intelligent Systems and their Applications, IEEE, 15(3), 14-17 (May/Jun 2000).Google Scholar
  8. Ehm, H., Heilmayer, S., Ponsignon, T., & Russland, T. (2011). A discussion of object-oriented process modeling approaches for discrete manufacturing on the example of the semiconductor industry. In Proceedings of the 2011 Winter Simulation Conference, S. Jain, R. R. Creasey, J. Himmelspach, K. P. White, and M. Fu, eds.Google Scholar
  9. Estefan, Jeff A. (2007). Survey of model-based systems engineering (MBSE) Methodologies.
  10. Huan, S., Sheoran, S., & Wang, G. (2004). A review and analysis of supply chain operations reference (SCOR) model. Supply Chain Management, 9(1), 23–29.Google Scholar
  11. Huang, E., Ky S. K., & McGinnis, L. F. (2008). Toward on-demand wafer fab simulation using formal structure and behavior models. Proceedings of the 2008 Winter Simulation Conference, S. J. Mason, R. R. Hill, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds.Google Scholar
  12. Huang, E., Ramamurthy, R., & McGinnis, L. F. (2008). System and simulation modeling using SysML. Proceedings of the 2007 Winter Simulation Conference, S. J. Mason, R. R. Hill, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds.Google Scholar
  13. Jiang, Y., Peng, G., & Liu, W. (2010). Research on ontology-based integration of product knowledge for collaborative manufacturing. The International Journal of Advanced Manufacturing Technology, 49(9), 1209–1221.Google Scholar
  14. Kiron, D., Schockly, R., et al. (2011). Analytics: The widening divide. MITSloan Management Review, 53(2):3–20.Google Scholar
  15. Lavrischeva, K. M. (2011). Theory and practice of software factories. Cybernetics and Systems Analysis, 47(6), 961–972.Google Scholar
  16. Libert, S., & ten Hompel, M. (2011). Ontology-based communication for the decentralized material flow control of a conveyor facility. Logistics Research, 3(1), 29–36.Google Scholar
  17. Meyers, B., & Hans, V. (2011, 1 December). A framework for evolution of modelling languages. Science of Computer Programming, 76(12), 12.Google Scholar
  18. Peak, R., Paredis, C., McGinnis, L., Friedenthal, S., & Burkhart, R. (2009). Integrating system design with simulation and analysis using SysML. INCOSE Insight Special Edition on MBSE, 12(4), 40–43.Google Scholar
  19. Prout, W. (1815). On the relation between the specific gravities of bodies in their gaseous state and the weights of their atoms. Annals of Philosophy, 6, 321–330.Google Scholar
  20. Ramos, A. L. F., Vasconcelos, J., & Barcelo, J. (2011). Model-Based Systems Engineering: An Emerging Approach for Modern Systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 42(1), 101–111.Google Scholar
  21. Rutherford, E. (1919). Collision of alpha particles with light atoms; an anomalous effect in nitrogen. The Philosophical Magazine, 37(222), 537–587. London: Taylor and Francis.Google Scholar
  22. White, S. A. (2006). Introduction to BPMN. Accessed 28 Dec 2011.

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.H. Milton Stewart School of Industrial and Systems EngineeringThe Georgia Institute of TechnologyAtlantaUSA

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