一种基于灰色理论和弱缓冲算子的装备备件预测方法

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Title:

A prediction method for equipment spare parts based on grey theory and weak buffering operator

作者:

齐小刚, 姚兆冬

西安电子科技大学 数学与统计学院, 陕西 西安 710126

Author(s):

QI Xiaogang, YAO Zhaodong

School of mathematics and statistics, Xidian University, Xi’an 710126, China

关键词:

备件预测; 灰色模型; 光滑度; 模型改进; 缓冲算子; 维修保障; 资源预测; 预测精度

Keywords:

spare part prediction; gray model; smoothness; model improvement; buffer operator; maintenance assurance; resource prediction; prediction accuracy

分类号:

TP20; N941.5

DOI:

10.11992/tis.202402014

摘要:

备件不足或者冗余是维修保障中的经典问题，严重影响维修效率。如何进行准确、有效的备件预测已成为维修保障的关键问题，由于备件预测的短期性和无规律性，灰色预测成为了常用的方法，但目前的灰色预测还存在精度不足的问题。为提升精度，从光滑化原始序列和模型改进2个方面对灰色预测进行改进，选取了4种不同的模型和3种光滑函数，并进一步构建新的弱缓冲算子来减少因累计计算产生的误差。实验结果表明在不同模型和光滑函数下，构建的算子对精度的提升是可行的，改进效果明显，同模型改进和光滑化结合可以获得更为准确的结果。

Abstract:

Spare parts shortage or redundancy is a common issue in maintenance assurance tasks, which seriously affects efficiency. How to make accurate and effective spare parts prediction has become crucial in maintenance support. Due to the short-term and irregular nature of spare part prediction, gray prediction has become a commonly used method, but the current gray prediction still has the problem of insufficient accuracy. To enhance the accuracy, gray models and methods are improved by smoothing the original sequence and refining the model, four different models and three smoothing functions are selected, and a new weak buffer operator is further constructed to reduce the error due to the cumulative calculation. The experiments show that under different models and smoothing functions, the constructed operators are feasible to improve the accuracy, and the improvement effect is obvious, and more accurate results can be obtained by combining with model improvement and smoothing.