- 學位論文
固聚酯粒存貨之最佳化控制-以A公司為例
The Study of Optimal Inventory Level for SSP PET Resin - A Case Study of A-Company
摘要
影響企業獲利的兩大因素為營收的變化與成本的變化，營業獲利就來自兩 者間的差距。因此如何使成本最低、或增加營收是公司使獲利增加最主要的方法。本研究構建主要模式，為「生產–成品存貨–客戶需求」模式，探討的重心是在存貨。藉由降低存貨水準來降低成本達成增加獲利的目標，並採用營收管理的觀念，藉由控制不同產量，控制成品庫存量，以不缺貨為原則，使獲利增加。 本研究以連續式固相聚合酯粒之生產、存貨、與客戶需求做為個案研究之主題。在第四章應用A公司個案，構建的產能大於需求的「生產–成品存貨–客戶需求」模式於探討，採用simulation with arena。先針對個案公司之各項存貨成本等數據做研究分析，求得各項存貨成本數據後，再結合電腦模擬軟體，分別建立了連續式(Continuous Simulation)以及離散式(Discrete Simulation)存貨管理之模擬模型，最後再利用模擬軟體內建之功能，自動求出最佳解。文中建議將每日的最低存貨量設定為816噸，最大存貨量1069噸， ，在此設定下求得之最佳解較與由代入實際值算得之營業獲利增加10.5 %，存貨則下降75.9%。 本研究因採用電腦模擬軟體，因此能大幅減低繁瑣之數學計算工作。求解過程中，我們發現電腦模擬軟體確實能如預期提供一較簡單之方式，求出現況存貨管理系統中成品庫存量最佳管制上下限。此外，模型建立完成後，只需調整所要變更的參數值，即可快速觀察相對應之各項輸出變化以做為決策之參考之優點，此點非常適合庫存管理在實務面上之應用。
並列摘要
The enterprise making a profit two big factors are cost down and increasing new revenues. In this research, the major developed models is a demand deterministic “production - inventory - customer demand” model. The objection function is to maximize the profit, which is the difference between revenues and costs. Production, selling, and inventory amount are the control variables. In this model setup and inventory costs are considered. The inventory level can be set at different number. The production plan is arranged to make the setup and inventory cost down. In this research, we select a bottle resin maker in Taoyuan, Taiwan as the case study company. Firstly, we study and calculate the inventory cost, then we use the simulation software with arena to build up a continuous and discrete simulation model of the inventory system. Finally, use the built-in function of the simulation software to get the optimal solution. The condition of production capacity is higher than the customer’s demand in case model. By simulating all the variables and observing their dynamic behavior, the result ( ) shows the best solution increasing 10.5 % profit and the inventory is down 75.9% with the real production data. During the problem-solving procedure, we find the simulation software really is easier to get the optimal solution. Furthermore, we also find that we can easily observe the change of output by just adjust the corresponding parameter, it helps us in decision-making process and also has good practical applications in the real inventory management works.