Prediction and analysis of aircraft failure rate based on SARIMA model

2017 2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA) Pub Date : 2017-09-01 DOI:10.1109/CIAPP.2017.8167281

Yanming Yang, Haiyan Zheng, Ruili Zhang

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引用次数: 13

Abstract

A large number of aviation equipment maintenance data exhibit seasonal behavior, such as aircraft failure rate. Consequently, seasonal forecasting problems are of considerable importance in aviation maintenance support. Aircraft failure rate is an important parameter of aviation equipment RMS (Reliability-Maintainability-Supportability). It is indispensable to scientifically predict the aircraft failure rate and to make scientific decisions on aviation maintenance to improve maintenance support capability. This paper proposes a seasonal ARIMA (SARIMA) model to solve the problem of aircraft failure rate forecasting. Then the mathematic model and modeling process of the SARIMA are introduced in detail. The application of SARIMA model in forecasting the aircraft failure rate is analyzed by examples. SARIMA (0, 1, 1) (0, 1, 1)12 model was selected as the most suitable model to forecast of aircraft failure rate. And the forecasting results were analyzed and compared. The results demonstrate that the SARIMA model is feasible and effective for the prediction of aircraft failure rate.

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基于SARIMA模型的飞机故障率预测与分析

大量航空设备维修数据表现出季节性行为，如飞机故障率。因此，季节预报问题在航空维修保障中具有相当重要的意义。飞机故障率是航空装备可靠性-维修性-保障性(RMS)的重要参数。科学地预测飞机故障率，科学地进行航空维修决策，是提高维修保障能力的必要条件。针对飞机故障率的预测问题，提出了一种季节性ARIMA (SARIMA)模型。然后详细介绍了SARIMA的数学模型和建模过程。通过实例分析了SARIMA模型在飞机故障率预测中的应用。选择SARIMA(0,1,1)(0,1,1)12模型作为最适合飞机故障率预测的模型。并对预测结果进行了分析比较。结果表明，SARIMA模型对飞机故障率的预测是可行和有效的。

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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2017 2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA)

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