Research on material demand analysis of manufacturing industry based on time series model—ARIMA

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Abstract

In order to solve the problem of mismatch between material production plan and actual demand, this paper analyzes and forecasts the material demand of manufacturing industry. Firstly, the material demand frequency at different time points in the historical production data of a manufacturing industry is calculated by statistical method. Secondly, it quantitatively analyzes the change trend of the total sales volume of each material at different time points to the unit price of the material. Thirdly, with the quantity, frequency, total sales and unit price of materials as characteristic factors, through relevant statistical analysis, six kinds of materials are synthesized. Finally, according to the demand data of these six materials, the time characteristics are transformed into weekly characteristics, and the time series model ARIMA is applied to construct the weekly prediction model of material demand, and the performance of the prediction model is evaluated. The results show that the comparison between the forecast results and the actual values of the weekly forecast model passes the test and has a good application prospect.
基于时间序列模型arima的制造业材料需求分析研究
为了解决材料生产计划与实际需求不匹配的问题,本文对制造业的材料需求进行了分析和预测。首先,采用统计方法计算某制造业历史生产数据中不同时间点的物料需求频率;其次,定量分析各物料在不同时间点的总销售量对物料单价的变化趋势。再次,以材料的数量、频次、销售总额和单价为特征因素,通过相关统计分析,综合出六种材料。最后,根据这六种材料的需求数据,将时间特征转化为周特征,应用时间序列模型ARIMA构建材料需求周预测模型,并对预测模型的性能进行评价。结果表明,周预报模型的预报结果与实际值的对比通过了检验,具有良好的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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