An effective tool for supply chain decision support during new product development process

Abstract

The global marketplace has transformed supply chain design into a discipline which requires business sense supported by mathematical expertise. Several methods have been introduced to support supply chain design, most notably mixed integer programming. The current methods are tailor-made for situations where a product's bill-of-material is fixed. However, this assumption does not hold during product development where several competing product designs exist. Therefore this research investigates the question of what is an effective way to support supply chain decisions during new product development. The study is divided into four research questions, corresponding to the articles from which the dissertation is compiled: (1) Does a product structure-driven method exist for modeling and analyzing supply chains? (2) If such a method is discovered, what is its mathematical formulation? (3) Is there evidence to support the theoretical and practical usability of such a method? (4) How can strategic supply chain decisions be validated? Regarding question (1) the research finds that there is a shortage of methods that fulfill supply chain modeling and analysis requirements imposed by new product development process. During the research a Petri-net based method was constructed which satisfies these requirements. For question (2), the formal definitions of the constructed Petri net class are provided. Regarding question (3), the research finds that the created method and associated tool are useful aids when solving the question of the effect of demand variation and the number of product variants on the optimal supply chain. Furthermore, interviews with end users of the tool implementation provide evidence of the Petri net method's practical usefulness. Regarding question (4), the research finds that the validation of strategic supply chain decisions from companies' reporting systems is important, but it has not become a common practice due to the challenges in integrating various IT systems