电商采购模式下煤炭企业物资库存优化方法研究

    Research on inventory optimization methods for coal enterprises under E-commerce procurement model

    • 摘要: 随着云计算、大数据及移动互联等技术的迅猛发展,电商采购模式逐渐应用于煤矿行业,在降低煤炭企业物资库存管理成本、提升采购效率的同时,也带来了新的挑战。本文分析了电商采购模式下煤炭企业物资库存管理存在的三个主要问题:需求预测难度加大;库存结构失衡;库存周转率与资金占用之间的矛盾。在此基础上,引入多模型预测方法构建煤矿企业物资需求预测模型,实现需求量的实时更新,从而更科学地规划库存持有量,避免过多积压,降低库存管理成本,并提升客户服务水平。依托ABC-VED分类方法,对不同类型库存实施差异化管控策略,采取不同的订货方式,以优化库存结构,提高周转率。同时分析了优化方案实施保障措施。应用结果表明,优化后的库存管理模式使总成本下降7.89%,库存积压物资减少11.41%,有效提升了库存物资周转率,减少了资金占用,实现了库存总成本的优化,验证了该方案的实际可行性。

       

      Abstract: With the rapid development of technologies such as cloud computing, big data, and mobile internet, the E-commerce procurement model is gradually being applied in the coal mining industry. While it reduces inventory management costs and improves procurement efficiency for coal enterprises, it also brings new challenges. This paper analyzes three main issues in inventory management of coal enterprises under the E-commerce procurement model: increased difficulty in demand forecasting; imbalance in inventory structure; conflict between inventory turnover rate and capital occupancy. Based on this analysis, a multi-model forecasting method is introduced to construct a material demand forecasting model for coal enterprises, achieving real-time updates of demand quantities. This enables more scientific planning of inventory holding levels, avoiding excessive accumulation, reducing inventory management costs, and improving customer service levels. Utilizing the ABC-VED classification method, differentiated control strategies are implemented for different types of inventory, adopting various ordering methods to optimize the inventory structure and improve turnover rates. The paper also analyzes the implementation guarantee measures for the optimization plan. The application results show that the optimization inventory management model reduces total costs by 7.89%, decreases excess inventory by 11.41%, effectively enhances inventory turnover rates, and reduces capital occupancy, achieving optimization of total inventory costs and verifying the practical feasibility of the plan.

       

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