煉鋼廠之氧氣工場最適動態生產規劃之研究

Abstract

鋼鐵工業供氧氣系統在鋼鐵生產過程中主要任務是對高爐煉鐵、轉爐煉鋼提供氧氣。當氧氣供過於求時，通常透過自動或人工操作等方式將多餘氧氣排放至大氣中，稱為氧氣排放，其為鋼鐵企業追求改善的重要指標。本研究針對C公司煉鋼廠之氧氣工場建構數學規劃之模型，利用調節氧氣工場氣體產量與氣體貯槽存貨量推擬氧氣工場之最適動態生產規劃，以滿足下游煉鋼之需求，提高氧氣工場營運之效能，達到減少氧氣排放量、降低營運總成本的目標。並在需求已知的情況下，針對氧氣工場短期與中期規劃分別以線性規劃與基因演算法(GA)為求解架構，求得滿足生產限制與儲存限制的最佳生產與調節規劃，作為氧氣工場規劃人員與現場人員的決策依據。此外，本研究也進行求解結果與C公司歷史數據的比較，其營運總成本改善率達20%以上,顯示本研究所發展之求解演算法為一優良的求解方法。

The mission of an oxygen production plant is to provide oxygen to iron and steel production. While the oxygen supply is over demand, the surplus amount beyond the inventory capacity of oxygen has to be diffused. The oxygen emission rate is a key performance index in iron and steel industry. This study focuses on the optimal dynamic production planning of the oxygen production plant of steel company C. We formulate the production problem as a mathematical model, which is able to fulfil the gas demand, raise the efficiency of gas production, reduce both oxygen emission rate and lower the production cost by adjusting the production rate of gas products and the inventory. This study assists company C in its short-term and middle-term planning of the optimal production planning corresponding to the given demand, production constraints and inventory capacity constraints. By proposing a solution approach that employs Genetic Algorithm (GA), this study provides a basis of decision-making to the operators. Our numerical results show that our approach is able to reduce the production cost for more than 20% from the history data of company C. We conclude that the proposed solution approach serves as a good one for the optimal dynamic production planning of oxygen production plant.