One key characteristic of any process performance is variability; that is, a process rarely performs consistently over time. The bottleneck is one of the main reasons causing the system variability and fluctuation in production. Short-term production analysis and short-term bottleneck identification are imperative to enable manufacturing operations to optimally respond to dynamic changes in system behavior. However, conventional throughput and bottleneck analysis focus on long-term statistic bottleneck identification, which is usually not applicable to a short-term period. An on-line supervisory control method is introduced to search for short-term production constraints with unknown machine reliability distribution and mitigate those constraints to improve system throughput. The control mechanism uses playback simulation of the real production data to identify the bottleneck station, and control parameters of that station to reach a near balanced production line operation by understanding the bottleneck inertia phenomenon. The results ensure the smooth flow of products on the production line and increase the line’s performance.
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e-mail: cindy.chang@gm.com
e-mail: junni@umich.edu
e-mail: pulak.bandyopadhyay@gm.com
e-mail: stephan.biller@gm.com
e-mail: guoxian.xiao@gm.com
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June 2007
Technical Papers
Supervisory Factory Control Based on Real-Time Production Feedback
Qing Chang,
Qing Chang
Manufacturing Systems Research Lab,
e-mail: cindy.chang@gm.com
General Motors Research and Development Center
, 30500 Mound Road, Warren, MI 48090
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Jun Ni,
Jun Ni
Department of Mechanical Engineering,
e-mail: junni@umich.edu
University of Michigan - Ann Arbor
, 1023 H. H. Dow, 2300 Hayward Street, Ann Arbor, MI 48109-2136
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Pulak Bandyopadhyay,
Pulak Bandyopadhyay
Manufacturing Systems Research Lab,
e-mail: pulak.bandyopadhyay@gm.com
General Motors Research and Development Center
, 30500 Mound Road, Warren, MI 48090
Search for other works by this author on:
Stephan Biller,
Stephan Biller
Manufacturing Systems Research Lab,
e-mail: stephan.biller@gm.com
General Motors Research and Development Center
, 30500 Mound Road, Warren, MI 48090
Search for other works by this author on:
Guoxian Xiao
Guoxian Xiao
Manufacturing Systems Research Lab,
e-mail: guoxian.xiao@gm.com
General Motors Research and Development Center
, 30500 Mound Road, Warren, MI 48090
Search for other works by this author on:
Qing Chang
Manufacturing Systems Research Lab,
General Motors Research and Development Center
, 30500 Mound Road, Warren, MI 48090e-mail: cindy.chang@gm.com
Jun Ni
Department of Mechanical Engineering,
University of Michigan - Ann Arbor
, 1023 H. H. Dow, 2300 Hayward Street, Ann Arbor, MI 48109-2136e-mail: junni@umich.edu
Pulak Bandyopadhyay
Manufacturing Systems Research Lab,
General Motors Research and Development Center
, 30500 Mound Road, Warren, MI 48090e-mail: pulak.bandyopadhyay@gm.com
Stephan Biller
Manufacturing Systems Research Lab,
General Motors Research and Development Center
, 30500 Mound Road, Warren, MI 48090e-mail: stephan.biller@gm.com
Guoxian Xiao
Manufacturing Systems Research Lab,
General Motors Research and Development Center
, 30500 Mound Road, Warren, MI 48090e-mail: guoxian.xiao@gm.com
J. Manuf. Sci. Eng. Jun 2007, 129(3): 653-660 (8 pages)
Published Online: October 27, 2006
Article history
Received:
April 25, 2006
Revised:
October 27, 2006
Citation
Chang, Q., Ni, J., Bandyopadhyay, P., Biller, S., and Xiao, G. (October 27, 2006). "Supervisory Factory Control Based on Real-Time Production Feedback." ASME. J. Manuf. Sci. Eng. June 2007; 129(3): 653–660. https://doi.org/10.1115/1.2673666
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