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217.060 1,计算值最低,2018年、2019年的预测误差仅为0.169 3件与7.385 0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。
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, 217.060 1. The prediction errors in 2018 and 2019 are only 0.169 3 pieces and 7.385 0 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.
作者
曹允春
刘宇展
沈丹阳
CAO Yunchun;LIU Yuzhan;SHEN Danyang(School of Transportation Science and Engineering,Civil Aviation University of China,Tianjin 300300,China;School of Economic and Management,Civil Aviation University of China,Tianjin 300300,China;Institute of Airport Economic,Civil Aviation University of China,Tianjin 300300,China)
出处
《工业工程》
北大核心
2022年第6期101-109,共9页
Industrial Engineering Journal
基金
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)。
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;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。
