A Framework of Set-based Concept Selection for Risk Control of Product Development

Author(s)

CAI Yan-ling1, ZHAI Yun-kai2

Author affiliation

1Zhengzhou University, 2Henan Engineering Research Center for Digital Medicine

Abstract

This paper attempts to examine the product innovation by R&D subsidies policies in a supply chain by supplier. This study derives a model for a supplier’s product innovation R&D subsidies policy. The product innovation of supplier can contribute to the long-term competitiveness for the supply chain. For many supply chains, product innovation is a major factor, and it should be considered in the development of strategies for a supplier. In this paper, we study whether there is scope for using R&D subsidies to smooth out obstacles to R&D performance for product innovation and expand the share of R&D to suppliers. To this end we consider a dynamic model with sunken entry costs in which supplier optimal participation strategy is defined in terms of two subsidy thresholds that characterise entry and continuation. A survey result in India is studied whether there is scope for using R&D subsidies to smooth out obstacles to R&D performance for product innovation and expand the share of R&D to suppliers. We are able to compute the subsidy thresholds from the estimates of a dynamic panel data type-2 to bit model for an unbalanced panel of about 3,000 Indian suppliers. The results suggest that extensive R&D subsidies (i.e., subsidies on the extensive margin) are a feasible and efficient tool for expanding the share of R&D for product innovation by suppliers.Product development (PD) projects are generally very risky because there are tremendous uncertain factors to handle. On the other hand, point-based product concept selection is always taken as the mainstream in PD practice to reduce resources consumption or expected lead time, which will inevitably introduce extra uncertainty into the PD process. This paper proposes a new framework of set-based concept selection in PD to improve the probability of project success. It suggests enhancing the decision robustness of product concept selection by allowing parallel evolvement of multiple alternatives, and the size of alternatives group will be re-determined at the next stage by assessing the overall quality of acquired product information at the current stage. The proposed method could provide PD team or manufacturers an optimal solution by balancing resources consumption and robustness of PD project success.

Keywords

Concept Selection, Set-Based Concurrent Engineering, Robust Decision, Risk Control, Product Development