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IMPReSS: An Automated Production-Planning and Delivery-Quotation System at Harris Corporation—Semiconductor Sector

Author

Listed:
  • Robert C. Leachman

    (Engineering Systems Research Center, University of California at Berkeley, Berkeley, California 94720)

  • Robert F. Benson

    (Engineering Systems Research Center, University of California at Berkeley, Berkeley, California 94720)

  • Chihwei Liu

    (Tyecin Systems, Inc., Four Main Street, Los Altos, California 94022)

  • Dale J. Raar

    (Aeon Decision Engineering, Inc., 1290 Oak Hampton Road, Holland, Michigan 49425)

Abstract

IMPReSS, an optimization-based production planning system at Harris Corporation's semiconductor sector, generates capacity-feasible production schedules for a worldwide manufacturing network and quotes product delivery dates in response to customer inquiries. The planning engine of IMPReSS is the Berkeley Planning System (BPS), which models the problem in a form that permits linear programming optimization. BPS embeds formulation techniques for planning the requirements of binning and substitutable products, for representing dynamic capacity consumption by reentrant process flows, and for developing multiple optimization calculations that reflect marketing priorities. It uses a heuristic decomposition strategy to break the overall problem into several manageable calculations. Its implementation raised on-time deliveries of line items from 75 to 95 percent without increasing inventories, enabled the sector to expand its markets and its market share, and helped move the sector from a loss of $75 million to profit of over $40 million annually.

Suggested Citation

  • Robert C. Leachman & Robert F. Benson & Chihwei Liu & Dale J. Raar, 1996. "IMPReSS: An Automated Production-Planning and Delivery-Quotation System at Harris Corporation—Semiconductor Sector," Interfaces, INFORMS, vol. 26(1), pages 6-37, February.
    • Handle: RePEc:inm:orinte:v:26:y:1996:i:1:p:6-37
    DOI: 10.1287/inte.26.1.6
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    Citations

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    Cited by:

    1. Ying-Ju Chen & Brian Tomlin & Yimin Wang, 2017. "Dual Coproduct Technologies: Implications for Process Development and Adoption," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 692-712, October.
    2. Raphael Herding & Lars Mönch, 2024. "A rolling horizon planning approach for short-term demand supply matching," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 32(3), pages 865-896, September.
    3. Lin, James T. & Chen, Tzu-Li & Lin, Yen-Ting, 2009. "Critical material planning for TFT-LCD production industry," International Journal of Production Economics, Elsevier, vol. 122(2), pages 639-655, December.
    4. Peter C. Bell & Chris K. Anderson, 2002. "In Search of Strategic Operations Research/Management Science," Interfaces, INFORMS, vol. 32(2), pages 28-40, April.
    5. Alfred Degbotse & Brian T. Denton & Kenneth Fordyce & R. John Milne & Robert Orzell & Chi-Tai Wang, 2013. "IBM Blends Heuristics and Optimization to Plan Its Semiconductor Supply Chain," Interfaces, INFORMS, vol. 43(2), pages 130-141, April.
    6. Peter C. Bell & Chris K. Anderson & Stephen P. Kaiser, 2003. "Strategic Operations Research and the Edelman Prize Finalist Applications 1989--1998," Operations Research, INFORMS, vol. 51(1), pages 17-31, February.
    7. Sawik, Tadeusz, 2007. "A lexicographic approach to bi-objective scheduling of single-period orders in make-to-order manufacturing," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1060-1075, August.
    8. S Eom & E Kim, 2006. "A survey of decision support system applications (1995–2001)," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(11), pages 1264-1278, November.

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