Research Papers

Transient Analysis of Downtimes and Bottleneck Dynamics in Serial Manufacturing Systems

[+] Author and Article Information
Qing Chang

Department of Mechanical Engineering, New York Institute of Technology, Harry Schure Hall, Old Westbury, NY 11568qchang@nyit.edu

Stephan Biller

Manufacturing Systems Research Laboratory, General Motors Research and Development Center, 30500 Mound Road, Warren, MI 48090-9055stephan.biller@gm.com

Guoxian Xiao

Manufacturing Systems Research Laboratory, General Motors Research and Development Center, 30500 Mound Road, Warren, MI 48090-9055guoxian.xiao@gm.com

J. Manuf. Sci. Eng 132(5), 051015 (Oct 05, 2010) (9 pages) doi:10.1115/1.4002562 History: Received January 11, 2010; Revised September 01, 2010; Published October 05, 2010; Online October 05, 2010

In manufacturing industry, downtimes have been considered as major impact factors of production performance. However, the real impacts of downtime events and relationships between downtimes and system performance and bottlenecks are not as trivial as it appears. To improve the system performance in real-time and to properly allocate limited resources/efforts to different stations, it is necessary to quantify the impact of each station downtime event on the production throughput of the whole transfer line. A complete characterization of the impact requires a careful investigation of the transients of the line dynamics disturbed by the downtime event. We study in this paper the impact of downtime events on the performance of inhomogeneous serial transfer lines. Our mathematical analysis suggests that the impact of any isolated downtime event is only apparent in the relatively long run when the duration exceeds a certain threshold called opportunity window. We also study the bottleneck phenomenon and its relationship with downtimes and opportunity window. The results are applicable to real-time production control, opportunistic maintenance scheduling, personnel staffing, and downtime cost estimation.

Copyright © 2010 by American Society of Mechanical Engineers
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Figure 3

The line segment between the station m and the slowest station M∗ when m<M∗

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Figure 4

Impact of downtime event (m,Td,d) to a transfer line

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Figure 5

Trend of blockage and starvation times in a production line

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Figure 1

A serial production line with M stations and M−1 buffers

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Figure 2

The production count trajectories when 1/T1<1/T2. (a) Production count trajectories with and without inserted downtime event e2,1=(2,Td,d1) and (b) production count trajectories with and without inserted downtime event e2,2=(2,Td,d2).



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