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How Would You Forecast the Manpower Needs of Ya Kun

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How Would You Forecast the Manpower Needs of Ya Kun
The International Journal of Flexible Manufacturing Systems, 16, 11–44, 2004 c 2004 Kluwer Academic Publishers. Manufactured in The Netherlands.

Time-Based Competition in Multistage Manufacturing: Stream-of-Variation Analysis (SOVA) Methodology—Review
D. CEGLAREK darek@engr.wisc.edu W. HUANG huang@cae.wisc.edu S. ZHOU szhou@engr.wisc.edu Department of Industrial Engineering, University of Wisconsin-Madison, Madison, WI 53706-1572, USA Y. DING YuDing@iemail.tamu.edu Department of Industrial Engineering, Texas A&M University, College Station, TX 77843, USA R. KUMAR Y. ZHOU Dimensional Control Systems, Inc., Troy, MI 48084, USA kumarr@3dcs.com yzhou@3dcs.com

Abstract. Frequency of model change and the vast amounts of time and cost required to make a changeover, also called time-based competition, has become a characteristic feature of modern manufacturing and new product development in automotive, aerospace, and other industries. This paper discusses the concept of time-based competition in manufacturing and design based on a review of on-going research related to stream-of-variation (SOVA or SoV) methodology. The SOVA methodology focuses on the development of modeling, analysis, and control of dimensional variation in complex multistage assembly processes (MAP) such as the automotive, aerospace, appliance, and electronics industries. The presented methodology can help in eliminating costly trial-and-error fine-tuning of new-product assembly processes attributable to unforeseen dimensional errors throughout the assembly process from design through ramp-up and production. Implemented during the product design phase, the method will produce math-based predictions of potential downstream assembly problems, based on evaluations of the design and a large array of process variables. By integrating product and process design in a pre-production simulation, SOVA can head off individual assembly errors that contribute to an accumulating set of dimensional variations,



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