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TECHNICAL PAPERS

Supervisory Factory Control Based on Real-Time Production Feedback

[+] Author and Article Information
Qing Chang

Manufacturing Systems Research Lab, General Motors Research and Development Center, 30500 Mound Road, Warren, MI 48090cindy.chang@gm.com

Jun Ni

Department of Mechanical Engineering, University of Michigan - Ann Arbor, 1023 H. H. Dow, 2300 Hayward Street, Ann Arbor, MI 48109-2136junni@umich.edu

Pulak Bandyopadhyay

Manufacturing Systems Research Lab, General Motors Research and Development Center, 30500 Mound Road, Warren, MI 48090pulak.bandyopadhyay@gm.com

Stephan Biller

Manufacturing Systems Research Lab, General Motors Research and Development Center, 30500 Mound Road, Warren, MI 48090stephan.biller@gm.com

Guoxian Xiao

Manufacturing Systems Research Lab, General Motors Research and Development Center, 30500 Mound Road, Warren, MI 48090guoxian.xiao@gm.com

J. Manuf. Sci. Eng 129(3), 653-660 (Oct 27, 2006) (8 pages) doi:10.1115/1.2673666 History: Received April 25, 2006; Revised October 27, 2006

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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Copyright © 2007 by American Society of Mechanical Engineers
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Figures

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Figure 1

Feedback control to mitigate short-term bottleneck

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Figure 2

A serial manufacturing line with buffers

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Figure 3

Flow chart of on line optimization procedure

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Figure 4

Replay simulation to identify bottleneck

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Figure 5

Adjustment of initial buffer levels around the bottleneck

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Figure 6

A serial line with five stations and four buffers

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Figure 7

Station breakdown records

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Figure 8

M1 repair time reduction versus throughput

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Figure 9

Layout of a production line

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Figure 10

Production increase with control

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