评估预测方法以减少电子元件销售的误差范围

Ricardo Daniel López, A. Maldonado, Humberto Jasso, Gerardo Huerta, J. Rodríguez
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引用次数: 1

摘要

电子市场的国际竞争要求组织不仅要利用其资源制造高质量的部件,而且要采用或开发适当的销售预测方法,以适应其需求并保证其经济发展。从工业工程的角度来看,这些组织需要保持平衡的订单和健康的安全库存。这两个指标在他们的经济增长和发展中发挥着重要作用,因为任何破坏都会导致整个制造过程中的高成本。因此,这些组织花费了大量资源来开发信息系统和物流技能,以便实施更可靠和精确的销售预测方法。然而,规划者和预测者不断面临不同的挑战,如突如其来的需求变化,季节性,产品生命周期短,缺乏历史数据,以及世界经济的波动。本研究的目的是确定最方便的需求预测方法,为制造商的电子设备,目标特定市场。分析了27个月的销售数据,并使用统计工具对不同的定量预测方法进行了测试和分析。结果表明,采用组合预测方法预测误差最小,是最合适的预测方法。这项研究的结果可以被其他公司采用,以预测任何项目的未来销售与我们的研究中使用的类似的模式。这对他们的决策过程和盘存计划有重大影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ASSESSMENT OF FORECASTING METHODS TO REDUCE THE MARGIN OF ERROR IN ELECTRONIC COMPONENT SALES
International competition in the electronic market requires that organisations use their resources not only to manufacture high quality components, but also to adopt or develop appropriate sales forecasting methods that could adapt to their needs and guarantee their economic development. From an industrial engineering perspective, keeping balanced orders and healthy safety stocks is required for such organisations. These two metrics play a significant role in their economic growth and development, because any disruption results in high costs throughout their manufacturing processes. Thus significant resources are spent by these organisations to develop information systems and logistics skills in order to implement more reliable and precise sales forecasting methods. Nevertheless, planners and forecasters constantly face different challenges such as sudden demand changes, seasonality, products with a short life cycle, a lack of historical data, and swings in the world economy. The objective of this research is to determine the most convenient demand forecasting method for the manufacturers of electronic devices that target a specific market. Twenty-seven months of sales data were analysed and different quantitative forecasting methods were tested and analysed using statistical tools. From the results obtained, the combined forecasting method appeared to be the most suitable since the least amount of forecasting error is obtained when this method is applied. The results of this research could be adopted by other companies to forecast the future sales of any items with a similar pattern to that used in our study. This has significant implications for their decision-making processes and inventory planning.
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