The product platform concept represents a powerful approach for manufacturers to compete cost-effectively in a global market that requires diverse product range, quick time to market, and rapid responses to supply sources. A key challenge is how to strike a balance between platform commonality and modularity. When a manufacturer outsources its raw materials or module options, the supplier capabilities and production costs should be considered. This paper discusses optimizing decision variables for simultaneously configuring not only platform-based product variants but also their supply chain. We develop a mixed-integer programming model that integrates both platform product design and material purchase decisions based on cost drivers sensitive to commonality and modularity. Theoretical analysis of the model yields two properties, allowing us to further simplify the model and thus help in developing an effective solution algorithm. A numerical example is presented to illustrate how manufacturers strive to dynamically adjust their product design strategies in response to changes in the market demands and/or supply base.
|Number of pages||26|
|Journal||International Journal of Production Research|
|Publication status||Published - Nov 2008|
- Mass customization
- Platform product
- Supply chain configuration