王英, 管延萱, 冯佳欣, 魏来, 宋知霖. 考虑无形磨损的拖拉机残值系数预测模型[J]. 农业工程学报, 2019, 35(17): 58-65. DOI: 10.11975/j.issn.1002-6819.2019.17.008
    引用本文: 王英, 管延萱, 冯佳欣, 魏来, 宋知霖. 考虑无形磨损的拖拉机残值系数预测模型[J]. 农业工程学报, 2019, 35(17): 58-65. DOI: 10.11975/j.issn.1002-6819.2019.17.008
    Wang Ying, Guan Yanxuan, Feng Jiaxin, Wei Lai, Song Zhilin. Prediction model of tractor residual value coefficient considering factor of invisible wear[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(17): 58-65. DOI: 10.11975/j.issn.1002-6819.2019.17.008
    Citation: Wang Ying, Guan Yanxuan, Feng Jiaxin, Wei Lai, Song Zhilin. Prediction model of tractor residual value coefficient considering factor of invisible wear[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(17): 58-65. DOI: 10.11975/j.issn.1002-6819.2019.17.008

    考虑无形磨损的拖拉机残值系数预测模型

    Prediction model of tractor residual value coefficient considering factor of invisible wear

    • 摘要: 针对当前随着农机设备更新速度加快,无形磨损对农机折旧影响加重的问题,该文在传统拖拉机残值系数预测模型的基础上引入无形磨损系数,构建了考虑无形磨损的拖拉机残值系数预测模型。以来自于农机服务中心农机及农具拍卖结果的25台拖拉机拍卖数据为研究样本,以机龄、年平均工作时长、无形磨损系数为变量参数,分析其价值变化规律;同时,为了进一步综合对比改进模型与原模型的残值系数预测精度,引入基于几何学的"弗雷歇距离"度量法。结果表明,改进模型与原模型相比,预测偏差较小,预测精度大幅度提高,达到24.9%及以上,能够显著地提高拖拉机残值预测准确度,该研究为折旧成本的计算和农机设备的更新决策提供了科学、准确的决策依据。

       

      Abstract: Abstract: Depreciation takes up a large proportion in the total activity cost of agricultural machinery. As the update speed of agricultural machinery was gradually accelerating, the impact of the invisible wears was strengthened by technological progress on agricultural machinery depreciation. Aiming to this problem, two types of invisible wears, which were caused by increased labor productivity and the emergency of more advanced machines, were analyzed and quantified respectively, and based on which, the comprehensive invisible wear degree was given in this paper. According to the traditional ASABE (American Society of Agricultural and Biological Engineers) residual value coefficient prediction model of tractors, considering the invisible wear factor, an improved prediction model of the residual value coefficient for tractors was established. Based on the auction data of 25 wheeled tractors collected from the agricultural machinery and tools auction results in the agricultural machinery service center, the age, the average annual working hours and the comprehensive degree of the invisible wears were used as the main independent variables to construct the improved model of the tractor residual value coefficient prediction and to analyze the law of the tractor value change. In addition, in order to increase the calculation accuracy, the discount coefficient was introduced to consider the time value of the capital. The results showed when the tractor age was above five years, the prediction value of the improved model was closer to the real residual value coefficient, and compared with the original model, the improved model was with less prediction deviation and higher prediction precision that was improved by more than 27%; but when the tractor age was within four years, the prediction deviation for the improved model was bigger than the original model, and the prediction result of the improved model was not satisfactory. The main reasons causing the results were that the effect of the invisible wears on the tractor was very small due to smaller technological progress in its early working period, but with the increasing of the tractor age and the development of science and technology, on one hand, the reproduction value of the same type of tractor would go down because of the improvement of manufacturing process and the increase of social labor productivity; on the other hand, the new type of machines, which were with more advanced technology, better performance, higher productivity and lower consumptions of raw materials and energy, would occur, so the effect of the invisible wears on the tractor residual value would intensified gradually, which also demonstrated that when predicting the residual value of agricultural machinery used for a relatively long period of time, the influence of the invisible wears must be considered. At the same time, the method of the geometry-based "Fréchet distance" metric was applied to further comprehensively compare and evaluate the prediction accuracies of the original model and the improved model. The results showed that compared with the original model, the improved model was with the higher prediction precision that was improved by 24.9%, and was able to significantly improve the accuracy of residual value prediction of tractors. The research of this paper can provide scientific and accurate decision-making basis for the calculation of depreciation cost and the determination of replacement time of agricultural machinery.

       

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