Inventory control during peak periods using basestock backlog policy: a case study of Pinkaura Plastic Company

Inventory optimization is very significant in supply chain and business activities. It also seeks to balance meeting customer demand at specified service levels while minimizing cost. Due to the variability of demand in the market, this uncertainty can result in overstocking or understocking and could lead to shortages and inefficiencies. Consequently, to efficiently optimize inventory costs, this study will use the recent three years’ Q4 demand (A.D. 2020-2022) of Pinkaura plastic company to be a Case study. The objective of this study is to enhance inventory management practices and elevate the service quality provided by Pinkaura plastic company. After gathering and analyzing the data, it was revealed that the company’s policy of ‘made-to-order’ resulted in lost sales opportunities and profit, particularly during the Q4, which encompasses extended long weekends and significant festivals. The make-to-order policy implies it takes 30-45 days to fulfill an order. In addition, some customers may not know about the pre-ordering rule, which results in unexpected orders and company might not have enough inventory to satisfy these orders. This paper will use the Grid search and Golden section search method to automate the simulation using Macro in Excel to find the optimal Order up to level of each product to minimize Total cost and fulfill customer demand.

库存优化在供应链与商业活动中具有至关重要的意义，其核心目标在于平衡特定服务水平下的客户需求满足率与成本最小化。由于市场需求存在波动性，这种不确定性可能引发库存过剩或缺货问题，进而导致资源短缺与运营低效。因此，为高效优化库存成本，本研究将以品克拉塑料公司（Pinkaura Plastic Company）近三年（公元2020-2022年）的第四季度需求数据作为案例研究对象。本研究的目标在于优化品克拉塑料公司的库存管理实践，提升其服务质量。在收集并分析数据后，研究发现该公司的按单生产（made-to-order）政策导致了销售机会与利润的流失，尤其在包含多个延长假期与重要节庆的第四季度期间。按单生产模式意味着订单履约周期为30至45天。此外，部分客户并不了解该公司的预购规则，由此产生的临时订单可能导致公司库存不足以满足需求。本文将采用网格搜索（Grid Search）与黄金分割搜索（Golden Section Search）方法，借助Excel中的宏（Macro）实现仿真自动化，以确定各产品的最优补货上限（Order-up-to Level），从而实现总成本最小化并满足客户需求。