一种基于库存绩效的航空消耗备件分类方法

Method for classification of aviation consumable spare parts based on inventory performance

航空消耗备件需求量大、缺货成本难以计算及获取不易等特性导致大量的在库库存,影响航空企业的库存周转率和总成本,不利于保持企业资产结构的流动性,阻碍效益的提高。由于传统定量分类方法无法基于库存绩效对备件进行全方面的分类,文中提出一种同时考虑备件年使用价值和库存信息的航空消耗备件分类方法。首先,基于需求数据及管理要求以(S-1,S)策略参数作为分类指标;其次,采用内生加权模型将其与年使用价值相结合,建立以库存绩效为优化目标的航空消耗备件分类模型;最后,以某航空企业实际备件数据为例对文中方法进行验证。结果表明:该分类方法能够在满足服务水平约束下降低平均库存,显著提高备件周转率和降低总成本,达到优化库存绩效的效果,且订购成本的降低和持有成本占备件价格比例的提高或是服务水平的降低都会增强分类方法的效果。

The aviation consumable spare parts have such characteristics as large demand,difficulty in calculating shortage cost and dfficulty in obtaining,which leads to large amounts of inventory in stock.Thus,it is harmful to the aviation enterprises'inventory turnover rate and total cost;also,it is not conducive to maintaining the liquidity of asset structure,therefore resulting in low profit.Since the traditional quantitative classification method fail to classify the spare parts in a comprehensive manner based on the inventory performance,in this article efforts are made to propose a method for classification of the aviation consumption spare parts,with the spare parts'annual use value and inventory information taken into consideration.Firstly,the(S-1,S)strategy parameter is taken as the classification index according to the data on demand and the management requirements;secondly,the endogenous weighted model is used to combine the parameter with the annual usage value,and the model for classification of the aviation consumable spare parts is set up with inventory performance as the optimization objective;finally,the method is verified according to the actual data on an aviation enterprise's spare parts.The result show that this classification method is helpful to reduce the average inventory,significantly improve the turnover rate of spare parts,reduce the total cost,and optimize the inventory performance,while providing high-quality service.Moreover,the reduced cost in order,the rising proportion of the holding cost to the price of spare parts,or the service on a lowered level will ensure desirable effect of this classification method.