This paper describes the first phase of the authors’ Design for Supply Chain research that seeks to address supply chain excellence the product design process. In a global economy, companies must address supply chain issues beyond the traditional viewpoint of logistics, trucking, warehousing and include other considerations that affects design and manufacturing decisions. To include supply chain perspectives in the design of products and manufacturing processes, supply chain performance data play a critical role. This paper examines the source of data pertinent to design for supply chain using methods such as Customer Value Chain Analysis and Quality Function Deployment. A multi-industry benchmarking study also highlights the different approaches to Design for Supply Chain and emerging challenges of Social and Environmentally Responsible Supply Chains. The study revealed that lead time, quality and social/environmental metrics are the most important metrics for design for supply chain. Future research will address the refinement of metrics, the definition of the relevant data for product design, and effective approaches to incorporate the information into the product definition process.
Product design over the past few decades has moved towards shorter life cycles, shorter design cycles while simultaneously having to satisfy multiple market segments. Global companies have responded to this challenge by designing products based on architectures, to meet these new market requirements. However, designing products based on architecture levies a significant tradeoff penalty on the derivative variants when compared to custom requirement-specific design. All derivative variants sharing the common architecture will have to carry the engineering weight of the variant with the most stringent performance requirements. This makes architecture definition a crucial step in achieving market success. The architecture definition process has three primary steps: architecture bandwidth definition, determining the number of variants and definition of the bandwidth of each variant. A study of the current architecture definition process in a large automobile manufacturer determined that the bandwidth and variant decision making process was entirely manual and dependant on the skill & experience of the personnel involved. This paper defines a math-based framework to define, determine and visualize the entire solution space of product variants in an individual architecture. A case study was built around a midsize vehicle architecture; with elemental physics and dynamics determining the performance attributes of each variant solution. A commercial simulation solution provided the marketshare simulation, for all the potential virtual vehicles in the solution space, providing a connection for engineering requirements to market performance. This paper begins with a brief overview of the architecture design space, walks through an analytical framework to define product architecture, and finally, future steps for this line of research.
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