| Summary: | 博士 === 國立清華大學 === 工業工程與工程管理學系 === 98 === Available-to-promise (ATP) calculating from master production schedule (MPS) exhibit availability of manufacturing resources that can be used to support customer order promising. This traditional order promising mechanism is adapted in MTS (make-to-stock) production model and all orders are treated the same on first-come-first-served (FCFS) policy. However, increasingly mass customization results in production model gradually transfers from MTS to ATO (assembly-to-order) or MTO (make-to-order) in order to fulfill the requests from customers such as customer’s preference materials/plants or specifications for the ordered products. Moreover, mass customization also drives the trend of customer demand to segmentation and prioritization according to differential product profit, sales growth potential, contracts or the relationships with customers.
Many manufacturers employ advanced planning and scheduling (APS) solutions with new planning and scheduling techniques to support supply chain planning. In which, the solution module of order promising & ATP is to match customer orders against available manufacturing resources and then to reply promised quantities and due dates. In ATO or MTO model, the manufacturing resource such as materials and capacity after order penetration point should be checked and allocated for customer orders considering customer’s preference constraints. An upstream CODP (customer order decoupling point) such as ATO or MTO involves rather long order lead-time but customers at least want to get a reliable promise that they can receive the products in the promised quantities at the promised dates. Therefore, order promising process is very important within such competitive supply chain environment to build core-competence through reliable order promises in order to retain customers and increase market share.
First, this research proposes one order promising mechanism that applies mixed integer linear programming (MILP) model to prioritize allocating manufacturing resource for high profit products or important customers and to consider material and capacity constraints after order penetration point. Furthermore, this order promising mechanism takes thin film transistor liquid crystal display (TFT-LCD) manufacturing as illustration for these material and capacity constraints after order penetration point.
Second, to reserve manufacturing resources for high-margin products or high-priority customers, this dissertation proposes two-phase order promising process. In phase 1, ATP are reserved (called Allocated ATP; AATP) first for the demand with higher profit or higher priority. And then in phase 2, customer orders are promised according to time-phase supply calendar of manufacturing resource and restricted by the AATP in phase 1 and requests from customers such as customer’s preference material/plant constraint. In which, mixed integer linear programming (MILP) is applied to prioritize allocating manufacturing resource for high profit products or important customers and to consider customer’s preference material/plant constraints after CODP.
One TFT-LCD manufacturing is taken as illustration for demonstrating the validity of the proposed two-phase order promising process. The results of numerical comparison show that the proposed two-phase order promising process can assist company to reserve manufacturing resources beneficially in advance phase 1 and then to provide more reliable customer order promises in phase 2 with considering available resources and requests from customers such as customer’s preference material/plant constraint.
|
|---|
