工业工程

工业工程 ›› 2022, Vol. 25 ›› Issue (6): 101-109.doi: 10.3969/j.issn.1007-7375.2022.06.012

• 专题论述 • 上一篇    下一篇

航空公司航线可更换件需求预测模型比较分析

曹允春1,3, 刘宇展2,3, 沈丹阳1,3   

  1. 1. 中国民航大学 交通科学与工程学院，天津 300300;
    2. 中国民航大学 经济与管理学院，天津 300300;
    3. 中国民航大学 临空经济研究中心，天津 300300
  • 收稿日期:2022-01-25 发布日期:2022-12-23
  • 通讯作者: 沈丹阳 (1983—) ，女，锡伯族，辽宁省人，副教授，博士，主要研究方向为航材管理、航空物流。E-mail: dyshen@cauc.edu.cn E-mail:dyshen@cauc.edu.cn
  • 作者简介:曹允春(1970—)，男，陕西省人，教授，博士，主要研究方向为航空物流、临空经济
  • 基金资助:
    天津市教委科研计划项目人文社科一般资助项目(2020SK046)；天津市研究生科研创新资助项目(2021YJSS105)

Demand Forecast Model Comparison of Airline LRU Parts

CAO Yunchun1,3, LIU Yuzhan2,3, SHEN Danyang1,3   

  1. 1. School of Transportation Science and Engineering, Civil Aviation University of China, Tianjin 300300, China;
    2. School of Economic and Management, Civil Aviation University of China, Tianjin 300300, China;
    3. Institute of Airport Economic, Civil Aviation University of China, Tianjin 300300, China
  • Received:2022-01-25 Published:2022-12-23

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摘要： 高价、可修航线可更换件的精准需求预测是航空公司航材采购的重要依据，是其降低成本的重要途径。为了比较并选择有效的预测方法，以发动机驱动泵为例，利用传统预测模型以及航空备件需求预测常用的计量预测模型进行需求预测；结合有效性准则对比得出最佳模型；将预测结果与真实值进行对比，验证最佳模型，并根据预测结果分析模型的适用性。结果表明，6种计量预测模型中，负二项回归模型优势明显，其AIC为217.0601，计算值最低，2018年、2019年的预测误差仅为0.1693件与7.3850件，且均满足航班保障率不低于95%的实践要求。在仅统计故障次数的情况下，计量预测模型相对于传统预测模型更有优势。比较结果可为航空公司维修中采购航线可更换件的决策提供参考。

关键词: 需求预测, 比较分析, 回归分析, 民用航空, 航线可更换单元 (LRU)

Abstract: Accurate demand forecasting of the high-priced and repairable line replaceable unit (LRU) parts is an important basis for airline procurement and an important way to reduce costs. Taking the Engine Driven Pump as an example, traditional forecasting models and the common measurement forecasting models for aviation spare parts were selected to forecast demand; then combined with the comparison of evaluating indexes, the best model was obtained; finally, the forecast demand of the models were discussed and compared with the practices to verify the conclusion. The results show that the negative binomial regression model has obvious advantages among the six models for the demand forecast of LRU parts. It has the lowest AIC, 217.0601. The prediction errors in 2018 and 2019 are only 0.1693 pieces and 7.3850 pieces, and it can meet the realistic requirements of airline flight guarantee rates exceeding 95%. In the case of only the number of failures is available, the measurement forecasting models are more advantageous. The comparison results of the forecasting models can provide reference for the airline's decision to purchase LRU parts.

Key words: demand forecasting, comparative analysis, regression analysis, civil aviation, line replaceable unit (LRU)

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