MTO-MTS Production Systems in Supply Chains

Increasing cost pressures have led supply chain managers to focus on running increasingly lean and efficient supply chains, with minimal inventory. Indeed, more and more firms are relying on pull or make-toorder (MTO) supply chains to minimize cost and waste. At the same time, increasing competitive pressures are leading to an increased emphasis on customer service. An important element of customer service, of course, is having make-to-stock (MTS) items in stock, and delivering make-to-order (MTO) products quickly and by the promised due date. In this project, we consider a variety of models designed to provide insight into the operation of combined MTS-MTO supply chains. We primarily focus on a simple stylized model of a two facility supply chain featuring a manufacturer served by a single supplier. Initially, we model a pure MTO supply, in which customers arrive at the manufacturer and place orders. The manufacturer needs to quote a due date to the customer when the order is placed, and the manufacturer needs to receive a component from the supplier before completing the manufacturing process. We design effective algorithms for production sequencing and due date quotation in both centralized and decentralized versions of this supply chain, characterize the theoretical properties of these algorithms, and compare the performance of the centralized and decentralized versions of the supply chain under various conditions. We also consider combined MTS-MTO versions of this supply chain. In these models, the manufacturer and supplier have to decide which items to produce to order, and which items to produce to stock. Inventory levels must be set for the MTS items, and due dates need to be quoted for the MTO items. In addition, sequencing decisions must be made. We consider several versions of these models, design effective algorithms to find inventory levels, to quote due dates, and to make sequencing decisions in both centralized and decentralized settings, and use these algorithms to assess the value of joint MTSMTO systems, as well as the value of centralization under various conditions. Finally, we consider more complex supply networks, and employ the results from the simple two facility supply chains described above to design effective heuristics for the MTS-MTO decision, inventory levels, sequencing, and due date quotation in these more complex supply chains. We employ these heuristics to answer a variety of questions about the value of centralization, and of using a combined MTS-MTO approach in complex supply chains.