Suchergebnisse

ABSTRACTUnder a continuous improvement framework, the policy of abating inventory via reductions in manufacturing randomness is considered. To explore this policy, a model of a real‐world production‐inventory system is developed, tested, and studied. The results suggest that manufacturing randomness reductions, even substantial ones, may not necessarily lead to inventory abatement, and paradoxically may lead sometimes to an inventory increase. In these cases, however, manufacturing randomness reductions will translate into higher customer service levels.

Research and development (R & D) supply chains are often designed without the process discipline and rigor that typically characterize the development of products emerging from R & D programs. This book should help everyday supply chain practitioners involved in research and new product development, who are migrating their products to full commercialization. The book should also aid decision makers looking to improve the overall effectiveness and efficiency of their supply chain. When new products are developed, a significant divide typically emerges in trying to commercialize the product while at.

AbstractConsider a single‐product, make‐to‐stock, risk‐averse firm with stochastic demand and manufacturing capacity. Temporarily unfilled demands are back‐ordered. Total cost is equal to the sum of inventory‐holding and back‐ordering costs over a continuous‐time, finite planning horizon. In this article, we study the problem of finding the base‐stock level that minimizes total cost conditional value‐at‐risk (CVaR), or total cost CVaR for short. We demonstrate that total cost CVaR is both convex in the base‐stock level and increasing in risk aversion. We derive a closed‐form approximation of total cost which is asymptotically exact in the planning horizon length. The approximation leads to a relatively simple determination of optimal base‐stock levels which are reasonably accurate for practical applications. We make observations and identify findings regarding the impact on optimal base‐stock levels of changes in risk aversion, manufacturing capacity, inventory‐holding and back‐ordering costs, and planning horizon length. We provide a detailed description of how our research results were applied in a real‐world, supply‐chain design project.