Inventory control model based on Big Data, EOQ, ABC and forecast to increase productivity in a hardware SME

J. Quiroz-Flores, Darien Caceres-Paitan, Rocio Avila-Nolasco
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Abstract

Within the commercial sector, SMEs represent more than 90% of all companies; they are responsible for 50% of GDP and generate between 60% and 70% of employment worldwide, which is why they are critical in the Peruvian economy. However, through an exhaustive review of the literature and sectoral analysis, we concluded they have a high risk of failure in the short term due to various problems, such as poor inventory management. In Peru, the provisions for carrying out inventories usually have a ratio of between 1% and 1.4% of the total inventory stock; thus, SMEs belonging to the hardware sector more frequently present this problem that affects the profitability of their companies. For this reason, the need arises to design an inventory control model that increases the productivity of hardware SMEs. After the pilot implementation of the first component, an increase in distribution efficiency of 11% is achieved, and its effectiveness is supported by simulating the entire model, obtaining the same results.
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基于大数据、EOQ、ABC和预测的库存控制模型,提高硬件中小企业的生产效率
在商业领域,中小企业占所有公司的90%以上;他们贡献了50%的国内生产总值,创造了全球60%至70%的就业机会,这就是为什么他们对秘鲁经济至关重要。然而,通过对文献和部门分析的详尽审查,我们得出结论,由于各种问题,例如库存管理不善,它们在短期内具有很高的失败风险。在秘鲁,用于进行库存的准备金通常占总库存的1%至1.4%;因此,属于硬件部门的中小企业更频繁地出现影响其公司盈利能力的问题。出于这个原因,需要设计一个库存控制模型,以提高硬件中小企业的生产力。第一个组件试点实施后,配送效率提高了11%,通过对整个模型的仿真验证了其有效性,得到了相同的结果。
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