Research Papers

The Costs of Downtime Incidents in Serial Multistage Manufacturing Systems

[+] Author and Article Information
Jianbo Liu

Department of Electrical and Computer Engineering,  Michigan State University, 2120 Engineering Building, East Lansing, MI 48824-1226jliu@egr.msu.edu

Qing Chang

Department of Mechanical Engineering,  Stony Brook University, 163 Light Engineering, Stony Brook, NY 11794qing.chang@stonybrook.edu

Guoxian Xiao

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

Stephan Biller

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

J. Manuf. Sci. Eng 134(2), 021016 (Apr 04, 2012) (10 pages) doi:10.1115/1.4005789 History: Received October 18, 2009; Revised December 17, 2011; Published April 03, 2012; Online April 04, 2012

Downtime is arguably the single most significant contributor to system inefficiency in a multistage manufacturing system. Achieving near-zero downtime has been the ultimate goal of production operation management at the plant floor. Accurate estimation of the impact of each downtime incident is of great importance for deciding where to allocate limited resources among various manufacturing stages. In this paper, we focus on quantitative analysis of the impact of each individual downtime event in terms of permanent production loss and financial cost. We start from the transient analysis of a single downtime event and later extend to more generic scenarios where downtime incidents occur concurrently at different stages. Apart from the analytical study, a practical computation procedure using real-time production records can be readily derived and implemented at the plant floor. Case studies are conducted to demonstrate its potential in facilitating the decision making at plant floor on project identification, prioritization, and budget allocation in a multistage manufacturing system.

Copyright © 2012 by American Society of Mechanical Engineers
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Figure 1

A serial production line with M stations and M buffers

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Figure 2

Concurrent downtime events in a two-station-one-buffer line

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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

Layout of the machining line. It consists of total 17 production stations (squares). All buffers (circles) are marked by their respective capacity

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Figure 5

Allocated production time loss at the station level due to random downtime events (a) and scheduled downtime events (b). The allocated production time loss was aggregated daily at each station.

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Figure 6

The differences among the allocated production time loss, accumulated downtime, and the accumulated blockage and starvation time. The MCBF for OP060 is set to 80. MCBF for OP090 is set to 64 (a), 40 (b), and 20 (c), respectively. All other parameters of the line are kept unchanged. Upper panel, allocated production time loss; middle panel, accumulated downtime; lower panel, accumulated blockage and starvation time.

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Figure 7

The line segment of consideration in an assembly plant



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