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  • https://doi.org/10.1115/detc2010-29095Copy DOI Icon

A Small to Medium-Size Enterprise Oriented Methodology for Optimizing Product and Supply Chain Design Decisions

  • Jan 1, 2010
  • Ming-Chuan Chiu +1 more
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Abstract

Today supply chain management has become one of the crucial factors for gaining and sustaining a competitive advantage. Enterprises that can more effectively manage their supply chain network have a higher likelihood of success in the marketplace. To this end, companies need not only make the “make” or “buy” decisions but also differentiate across potential suppliers in order to improve operational performance, and hence, supplier selection is one of the key decisions aiding effective supply chain management. Many studies have also pointed out that the integration of product and supply chain is a key factor for profitability and efficiency. However, prior studies mostly address supply chain performance after the creation of a new product; and only a few studies discuss when and how to incorporate supply chain decisions during product design. In the studies that cover product design, product family and product platform concepts are presented as enabling vehicles for mass customization, which require a considerable investment, and hence might be out of reach for small to medium size enterprises (SME). Accordingly, there is a need to develop a methodology that can consider manufacturability and supply chain issues at the product design stage. This paper presents a graph theory based optimization methodology to tackle this problem. The supplier selection issue is considered by evaluating its impact on both engineering (e.g., process planning) and operational performance (e.g., cost and time), which are then aggregated as the supply chain performance at the conceptual design stage. A case study in the bicycle industry demonstrates the advantages of this methodology. The synchronized structure of the supply chain and the product design results in simultaneous optimization of both design and supply chain decisions during the early design stages.

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