库存管理对于企业的高效运营至关重要。通过合理的库存管理，企业可以避免因库存过多而产生的库存积压和过期损失，同时也可以避免因库存不足而导致的生产停滞和加急采购等问题。科学、合理地进行库存管理，有助于企业降低运营风险，提高响应速度，降低企业的库存成本，提高企业竞争力。 N公司作为一家提供全球安检产品和解决方案的公司，随着安检行业市场容量每年市场容量的稳步上升，市场需求不断扩大，现有的物料供给节奏已经无法应对快速变化的市场需求。为了满足市场需求，N公司采取了一系列的供给措施。但是，满足客户需求势必带来高库存、高成本运营的风险。当面临研发换型，客户偏好变更等情况时，很容易产生呆滞物料或库存不足的情况，从而造成库存成本增加或客户服务水平降低。本论旨在研究库存优化管理的问题，探讨如何通过有效的库存管理方法来降低库存成本、提高效率和响应速度。 通过对国内外库存管理文献的研究，分析了库存管理现状及发展趋势，探究相关理论知识和优秀企业库存管理案例，结合N公司自身实际情况，将库存优化管理运用企业实践中。 随着业务的不断能扩大，N公司在生产管理过程中，面临着一系列的问题与挑战。通过分析N公司的库存管理现状，揭示了造成问题的根本原因，包括库存水平的判断、物料备货策略及库存风险的应对等方面。运用ABC分类法，以最小存货单位占比及物料价值比重进行标的，对N公司上百种物料进行分类识别，根据不同的物料属性，分类管理，最终达到库存管理有的放矢，精益化生产的目的。 根据N公司物料分类的不同，采取合适的库存盘点策略，计算补货点及最优补货量。本文筛选出4种具有代表性的物料，利用需求量的概率密度，测算出满足一定服务水平的前提下，物料的补货点及最优补货量，进而设置库存优化模型，并对库存水平及库存成本的计算结果与改善前的数据进行比对，以此验证数据模型优化的合理性。 本文以N公司库存管理优化设置为例，帮助生产制造企业，摆脱以往凭借经验管理的局面，运用科学合理的方法来应对瞬息万变的市场需求，减少企业沉重的库存成本负担，使优化库存机制的研究具有现实管理意义。

Inventory management is crucial for the efficient operation of enterprises. Through reasonable inventory management, enterprises can avoid inventory backlog and overdue losses caused by excessive inventory, as well as production stagnation and urgent procurement problems caused by insufficient inventory. Scientific and reasonable inventory management can help enterprises reduce operational risks, improve response speed, reduce inventory costs, and enhance competitiveness. As a company that provides global security products and solutions, N Company has been unable to cope with the rapidly changing market demand due to the steady increase in market capacity of the security industry every year and the continuous expansion of market demand. In order to meet market demand, N Company has taken a series of supply measures. However, meeting customer needs inevitably brings risks of high inventory and high cost operations. When faced with research and development changes, customer preferences changes, and other situations, it is easy to generate stagnant materials or insufficient inventory, resulting in increased inventory costs or reduced customer service levels. This paper aims to study the issue of inventory optimization management and explore how to reduce inventory costs, improve efficiency, and respond quickly through effective inventory management methods. Through research on domestic and foreign inventory management literature, this paper analyzes the current situation and development trends of inventory management, explores relevant theoretical knowledge and excellent enterprise inventory management cases, and combines the actual situation of N Company to apply inventory optimization management to enterprise practice. This article analyzes the production management characteristics and current status of plan management of Company N, deeply analyzes the problems and challenges in inventory management, and reveals the root causes of the problems, including inventory level judgment, material stocking strategy, and response to inventory risks. ABC analysis is used to classify and identify hundreds of materials of Company N based on the proportion of stock keeping unit and the proportion of material value. According to different material properties, classified management is carried out to achieve the goal of targeted inventory management and lean production. Based on the different material classifications of Company N, adopt appropriate inventory counting strategies, calculate replenishment points and optimal replenishment quantities. This article selects four representative materials and uses the probability density of demand to calculate the replenishment point and optimal replenishment quantity of materials that meet a certain service level. Then, an inventory optimization model is set up, and the calculation results of inventory level and inventory cost are compared with the data before improvement to verify the rationality of the data model optimization. This article takes N Company’s inventory management optimization setting as an example to help manufacturing enterprises break away from the situation of relying on experience management in the past, use scientific and reasonable methods to respond to rapidly changing market demand, reduce the heavy inventory cost burden of enterprises, and make the research on optimizing inventory mechanisms have practical management significance.