摘要
从影响军用飞机生产制造工时的众多因素中提取出24个飞机总工时影响因素,采用统计学方法结合理论分析对此24个因素进行科学筛选,筛选出飞机最大起飞重量、最大速度、爬升率、最大过载、钛铝合金比例、复合材料与铝合金比例这6个关键影响因素。考虑偏最小二乘回归(PLS)法在处理小样本多元数据方面的优势,采用PLS法对飞机总工时进行预测,预测结果表明PLS预测模型平均检验误差约为10%。该模型在实际使用过程中,只需获得飞机性能指标和材料构成等少数设计参数即可在飞机产品生产制造前对飞机生产制造总工时进行宏观预测,具有参数少、物理意义明晰、操作简单、便于使用、准确率高等特点,可为缺乏详细设计信息和生产信息的飞机研制早期方案优选、设计优化或对其进行费用分析和成本控制、固定资产投资、安排生产计划等工作提供相对准确的飞机产品工时。
Out of a selection of 24 parameters from numerous factors which correlate to plane manhours in manufacture, six key parameters, including maximum takeoff weight, maximum speed, climbing rate, maximum overload, ratio of titanium/ aluminum alloy and ratio of composite/aluminum alloy, are chosen via statistical and theoretical analysis based on existing plane samples. In view of the advantages of partial least-squares regression （PLS） method in analyzing multivariate data with small samples, it is utilized to build an estimation model of plane manhours in manufacture. The results show that the av- erage error is about 10%. With this model, very little information, such as performance index, material composition, etc., is needed for the estimation of plane manufacturing manhours before the start of manufacturing activities. The PLS estimation model exhibits many advantages such as less parameters requirement, perspicuous physical meaning, and simple operation. It can be used to predict the manhours for plan optimization, design optimization, cost analysis and control, capital asset in- vestment and production arrangement in the preliminary development stage of a plane with the absence of detailed design and manufacture information.
出处
《航空学报》
EI
CAS
CSCD
北大核心
2012年第8期1448-1454,共7页
Acta Aeronautica et Astronautica Sinica
基金
航空科学基金(2010ZG17001)~~
关键词
飞机总工时
特征参数
预测模型
偏最小二乘回归法
小样本多元数据
plane manhour
characteristic parameter
estimation model
partial least-squares regression method
multiva-riate data with small samples
