Paper
13 October 2000 How much domestic quick response manufacturing can a business afford?
Roger D. H. Warburton, Steven B. Warner
Author Affiliations +
Proceedings Volume 4192, Intelligent Systems in Design and Manufacturing III; (2000) https://doi.org/10.1117/12.403641
Event: Intelligent Systems and Smart Manufacturing, 2000, Boston, MA, United States
Abstract
Employment in the U.S. apparel industry has declined dramatically since the 1960s. Will it fall inexorably to zero, or is there some base level that can endure? If so, what strategic characteristics are required to survive? There is considerable interest in Quick Response Manufacturing (QRM), not only as a reason to support domestic manufacturing, but also as part of the larger goal of reducing supply chain costs. However, since Domestic Manufacturing is more expensive, why should anyone bother considering it? This paper presents an analytical model of a team approach that includes both domestic and offshore manufacturing. Despite the additional costs associated with U.S. manufacturing, our model predicts that including a domestic contractor is legitimate and cost effective. However, the alliance must be genuinely cooperative. A partnership has to be established early in the retailer's planning cycle, and the manufacturer should participate in the planning. Also, sharing data and making timely decisions imposes a strategic business approach, and the model allows us to describe the characteristic roles and capabilities required. Using this model for guidance, we anticipate that retailers will have the stock to satisfy more customers with fewer markdowns, while manufacturers will see increased margins and lower inventories.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Roger D. H. Warburton and Steven B. Warner "How much domestic quick response manufacturing can a business afford?", Proc. SPIE 4192, Intelligent Systems in Design and Manufacturing III, (13 October 2000); https://doi.org/10.1117/12.403641
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Cited by 2 scholarly publications.
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KEYWORDS
Manufacturing

Data modeling

Performance modeling

Design for manufacturability

Intelligence systems

Calibration

Data analysis

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