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Serial Agile Production Systems with Automation

Author

Listed:
  • Wallace J. Hopp

    (Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208)

  • Seyed M. R. Iravani

    (Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208)

  • Biying Shou

    (Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208)

Abstract

To gain insights into the design and control of manufacturing cells with automation, we study simple models of serial production systems where one flexible worker attends a set of automated stations. We (a) characterize the operational benefits of automation, (b) determine the most desirable placement of automation within a line, and (c) investigate how best to allocate labor dynamically in a line with manual and automatic equipment. We do this by first considering two-station Markov decision process models and then studying three-station simulations. Our results show that the capacity of production lines with automatic machines can be significantly lower than the rate of the bottleneck. We also show that automating a manual machine can have a dramatic effect on the average work-in-process (WIP) level, provided that labor is the system bottleneck. Once a machine becomes the bottleneck, the benefits from further automation are dramatically reduced. In general, we find that automation is more effective when placed toward the end of the line rather than toward the front. Finally, we show that automation level increases the priority workers should give to a station when selecting a work location.

Suggested Citation

  • Wallace J. Hopp & Seyed M. R. Iravani & Biying Shou, 2005. "Serial Agile Production Systems with Automation," Operations Research, INFORMS, vol. 53(5), pages 852-866, October.
  • Handle: RePEc:inm:oropre:v:53:y:2005:i:5:p:852-866
    DOI: 10.1287/opre.1050.0226
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Jingui Xie & Yiming Fan & Mabel C. Chou, 2017. "Flexibility design in loss and queueing systems: efficiency of k-chain configuration," Flexible Services and Manufacturing Journal, Springer, vol. 29(2), pages 286-308, June.
    2. Sina Ansari & Seyed M. R. Iravani & Qifeng Shao, 2019. "Optimal control policies in service systems with limited information on the downstream stage," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(5), pages 367-392, August.
    3. Rezapour, Shabnam & Naderi, Nazanin & Morshedlou, Nazanin & Rezapourbehnagh, Shaghayegh, 2018. "Optimal deployment of emergency resources in sudden onset disasters," International Journal of Production Economics, Elsevier, vol. 204(C), pages 365-382.
    4. Wallace J. Hopp & Seyed M.R. Iravani & Biying Shou & Robert Lien, 2009. "Design and control of agile automated CONWIP production lines," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(1), pages 42-56, February.
    5. 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.
    6. Soroush Saghafian & Wallace J. Hopp & Mark P. Van Oyen & Jeffrey S. Desmond & Steven L. Kronick, 2012. "Patient Streaming as a Mechanism for Improving Responsiveness in Emergency Departments," Operations Research, INFORMS, vol. 60(5), pages 1080-1097, October.

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