Abstract
The enterprises usually have many factories in different locations, now. In facing the growth of customer orders, a company usually to face the problem that it cannot accept all the orders because of the lack of capacity. In order to avoid the lost orders and profit, a company requires an assist model to find out the better orders as their first priority. Due to the increasing production scale, a company must adopt a multi-plant manufacturing strategy to increase the capacity to satisfy the ordered demands. Under this consideration, it is important to develop a coordinated capacity planning in the manufacturing model to meet the change in such production environment. The objective of this research is to develop two integrate capacity planning models in two phases. This model is aimed at maximizing the enterprises order’s profit under the maximum capacity volumes and minimizing the total production cost under the consideration of plants and constraints of resources and equipment.The model is analyzed according to the maximum capacity volumes, order allocation by capacity constrain, bottleneck workstation capacity load by machine capacity constrain to find out the dispatching production plan. In this model, we obtain the minimal integrated cost including production cost, manufacturing cost, out-sourcing cost. In phase one, we can obtain the amount of product order requirement of enterprises. In phase two the workstation capacity load and bottleneck workstation of each plant is obtained. The enterprises order evaluation and multi-plant capacity are modeled and solved using the linear programming formulation and technologies. In this way, we can found an optimal order planning solution and an optimal multi-plant capacity planning solution. We can arrange the production planning and schedule planning according to the optimal solution of multi-plant capacity planning. A case study of a semiconducting manufacturer is conducted to verify the feasibility of the proposed methodology. The results show that it can be used to find the optimal order solution and optimal production plan.