Selecting new product designs and processing technologies under uncertainty: Two-stage stochastic model and application to a food supply chain

Abstract

New product introduction frequently requires new processing technologies, and the development of new processing technologies also allows for the introduction of new products. An assessment of these new products and technologies must account for changes in the whole supply chain. This paper presents a two-stage stochastic mixed integer linear programming model that integrates the selection of new product designs and processing technologies in a supply chain context. Special attention is given to the demand uncertainties with regard to product specifications and volumes. The first stage of the model selects the processing technologies that determine the set of feasible product designs, leaving the detailed product designs and the production volumes as recourse actions to the second stage. We apply the developed approach to product designs and processing technologies in the dairy sector. Here, the substitution of milk powders through milk concentrates is currently being considered, which may lead to extensive energy savings in production. In an interdisciplinary effort, we first derive the design space encompassing the feasible dairy technologies and product designs for concentrates. Through numerical investigation we then show that flexible technologies are selected that can be used to produce different product designs. We also show that the selection of technologies is highly dependent on the uncertain demand characteristics of the new concentrate products.