A note on ‘impacts of random scrap rate on production system in supply chain environment with a specific shipping policy’

This paper employs an alternative approach to reexamine the impacts of random scrap rate on production system in supply chain environment with a specific shipping policy. A straightforward approach in terms of a two-phase algebraic derivation is proposed in this study to replace the conventional method with the need of applying first-order and second-order differentiations to the system cost function for proof of convexity before derivation of the optimal production-shipment policy. The research result of this study is confirmed that is identical to what was obtained by Cheng et al. [1] where they used the conventional method to solve the same problem. The proposed approach is helpful for practitioners, who may not have sufficient knowledge of differential calculus to understand such an integrated production-shipment system in supply chain environment

Multiple Item Capacitated Random Yield Systems

Two main contributors to the uncertainty of production systems are capacity and random yield; therefore, strategies are needed that incorporate both random yield and the increased effect due to capacity restrictions. This paper utilizes dynamic programming and linear programming transformation to provides a method to specify an optimal decision for a given inventory state. In doing so, it can be empirically shown that the structure of the optimal policy is not an order-up-to policy. Using this method, one only needs to solve a small subproblem, which using LP transformation can be done using commercially available LP solvers without concern for solution time. These results may improve the decision-making capabilities of real-time complex environments since the emphasis is on developing policy rules that are easy to implement in manufacturing applications, as well as service industries such as airlines, healthcare and education. Additionally, the results may be used as a means of evaluating (bounding) existing approximation methods