钢铁企业原燃料库存控制优化研究
发布时间：2019-05-31 14:52
【摘要】：随着经济全球化的发展,物流业作为一个新兴产业,正在全球范围内迅速兴起,在企业管理控制中,物流管理的地位和作用与日俱增。钢铁企业作为典型的制造类企业,其生产物流成本在企业物流总成本中占有很大的份额,库存成本又是企业生产物流成本的重要组成部分,控制企业库存成本能够有效的降低企业的物流成本。在钢铁企业运营生产过程中,原燃料物流量占企业总物流量的60%以上,因此,对钢铁企业原燃料库存控制的优化研究具有重要的理论和实践意义。 本文针对钢铁企业生产物流的特殊性,分析了钢铁企业原燃料及其库存的特点和存在的问题,针对钢铁企业原燃料库存普遍存在的问题结合适当的库存控制方法,提出钢铁企业原燃料库存控制策略。通过对ABC库存分类方法的研究与改进,分别从价格因素和消耗量因素的角度应用模糊聚类分析方法对钢铁企业原燃料进行分类,重点对价格敏感和消耗量敏感的原燃料提出不同的库存控制策略。根据分类方法中涉及的价格因素和消耗量因素在设置原燃料的安全库存时,从提前期变动和消耗量变动的角度分析其对安全库存的影响,结合钢铁企业生产实际,建立主要原燃料库存优化模型,应用遗传算法对其采购量和库存量进行优化。以XF钢铁厂为例进行了实证研究,运用改进的ABC分类法和模糊聚类分析方法对其主要原燃料进行分类,选取不同类别的主要原燃料计算安全库存并建立库存优化模型,利用遗传算法求解主要原燃料的最佳采购量和最佳库存量,提出了XF钢铁厂原燃料库存控制优化方案。
[Abstract]:With the development of economic globalization, logistics industry, as a new industry, is rising rapidly all over the world. In the enterprise management control, the position and function of logistics management is increasing day by day. As a typical manufacturing enterprise, the production logistics cost of iron and steel enterprises accounts for a large share of the total logistics cost of the enterprise, and the inventory cost is an important part of the production logistics cost of the enterprise. Controlling the inventory cost of the enterprise can effectively reduce the logistics cost of the enterprise. In the operation and production process of iron and steel enterprises, the raw fuel flow accounts for more than 60% of the total material flow of the enterprise. Therefore, it is of great theoretical and practical significance to study the optimization of raw fuel inventory control in iron and steel enterprises. In view of the particularity of production logistics in iron and steel enterprises, this paper analyzes the characteristics and existing problems of raw fuel and its inventory in iron and steel enterprises, and combines the appropriate inventory control methods with the common problems in raw fuel inventory in iron and steel enterprises. The control strategy of raw fuel inventory in iron and steel enterprises is put forward. Through the research and improvement of ABC inventory classification method, the raw fuel of iron and steel enterprises is classified by fuzzy cluster analysis method from the point of view of price factor and consumption factor, respectively. Different inventory control strategies are put forward for price-sensitive and consumption-sensitive raw fuels. According to the price factors and consumption factors involved in the classification method, when setting up the safe inventory of raw fuel, the influence on the safe inventory is analyzed from the point of view of the change of lead time and consumption, and combined with the production practice of iron and steel enterprises, The optimization model of main raw fuel inventory is established, and the purchase volume and inventory are optimized by genetic algorithm. Taking XF iron and steel works as an example, the improved ABC classification method and fuzzy cluster analysis method are used to classify the main raw fuels, and different types of main raw fuels are selected to calculate the safe inventory and establish the inventory optimization model. The genetic algorithm is used to solve the optimal purchase quantity and inventory of the main raw fuel, and the optimization scheme of raw fuel inventory control in XF iron and steel plant is put forward.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F426.31;F274
本文编号：2489794
[Abstract]:With the development of economic globalization, logistics industry, as a new industry, is rising rapidly all over the world. In the enterprise management control, the position and function of logistics management is increasing day by day. As a typical manufacturing enterprise, the production logistics cost of iron and steel enterprises accounts for a large share of the total logistics cost of the enterprise, and the inventory cost is an important part of the production logistics cost of the enterprise. Controlling the inventory cost of the enterprise can effectively reduce the logistics cost of the enterprise. In the operation and production process of iron and steel enterprises, the raw fuel flow accounts for more than 60% of the total material flow of the enterprise. Therefore, it is of great theoretical and practical significance to study the optimization of raw fuel inventory control in iron and steel enterprises. In view of the particularity of production logistics in iron and steel enterprises, this paper analyzes the characteristics and existing problems of raw fuel and its inventory in iron and steel enterprises, and combines the appropriate inventory control methods with the common problems in raw fuel inventory in iron and steel enterprises. The control strategy of raw fuel inventory in iron and steel enterprises is put forward. Through the research and improvement of ABC inventory classification method, the raw fuel of iron and steel enterprises is classified by fuzzy cluster analysis method from the point of view of price factor and consumption factor, respectively. Different inventory control strategies are put forward for price-sensitive and consumption-sensitive raw fuels. According to the price factors and consumption factors involved in the classification method, when setting up the safe inventory of raw fuel, the influence on the safe inventory is analyzed from the point of view of the change of lead time and consumption, and combined with the production practice of iron and steel enterprises, The optimization model of main raw fuel inventory is established, and the purchase volume and inventory are optimized by genetic algorithm. Taking XF iron and steel works as an example, the improved ABC classification method and fuzzy cluster analysis method are used to classify the main raw fuels, and different types of main raw fuels are selected to calculate the safe inventory and establish the inventory optimization model. The genetic algorithm is used to solve the optimal purchase quantity and inventory of the main raw fuel, and the optimization scheme of raw fuel inventory control in XF iron and steel plant is put forward.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F426.31;F274
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