Integrating Advance Demand Information into Production Inventory Control Systems

This research investigates how advance demand information (ADI) being shared across the supply chain could be integrated into production inventory control systems (PICS) to gain greater production efficiencies and reduce costs.;First, this research analyzes the integration of ADI in a manufacturing system operating under kanban control and proposes a new hybrid PICS that yields superior performance. Analytical approximations are developed for the optimal policy parameters of this new system. Next, the optimal release policy for a system operating under kanban control with ADI is investigated. By modeling the system as a continuous-time infinite-horizon Markov decision process (MDP), the optimal release policy is shown to have a kanban-controlled state-dependent threshold type structure. Numerical studies show that this relatively simple release policy yields up to 30% cost savings.;Next, the research investigates the impact of quality of ADI and configuration of manufacturing stations, on the benefits of integrating ADI into PICS. Several variations of the system configuration are considered to include various features such as order cancellations, partial sharing of ADI, variability in demand information lead time, the number of manufacturing stations, and their configuration within the manufacturing system. For each setting, revised MDP models are used to determine the optimal release policies using policy iteration algorithms. Numerical studies show that the basic threshold-based structure of the optimal policy continues to hold in most cases. The studies also reveal which aspects of quality of ADI and manufacturing system configuration have significant effect on overall system costs.;The last part of this thesis explores the integration of ADI in supply chain contracts. For a supply chain with a single-manufacturer and single-supplier operating under an options-futures contract, two-stage stochastic dynamic programming is used to determine the optimal ordering decisions for the manufacturer and the optimal production decisions for the supplier. The sensitivity of supply chain performance to the quality of the information exchanged through these contracts is also studied.;The results from this research find important implications for decisions related to investments made to share ADI across supply chains and the benefits to be expected from such collaborations.