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Predicting downtime costs of tracked hydraulic excavators operating in the UK opencast mining industry

机译:预测英国露天采矿业中的履带液压挖掘机的停机成本

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This paper describes the development of a model to predict the hourly cost of downtime (using regression equations) for tracked hydraulic excavators operating in the UK opencast mining industry. A three-stage process was utilized for the model's development. The first stage predicted machine cycle times, the second predicted hire costs per hour and the third used the outputs of the first two to forecast the cost of breakdown. Both cycle time and hire cost models were revealed to be good predictors, as exhibited by the 'high' R~2 values of 0.86 and 0.95, respectively. A plant expert employed within the Defence Logistics Organisation, UK Ministry of Defence, validated these regression models and the process by which downtime costs were predicted. Future research work will aim to enhance the predictive ability of the models developed, expand the research to cover other machine types, and reproduce the findings in graphical and tabular format to improve the interpretation of information generated.
机译:本文描述了模型的开发,该模型可预测在英国露天采矿行业中使用的履带液压挖掘机的停机小时成本(使用回归方程式)。模型的开发采用了三个阶段的过程。第一阶段预计的机器周期时间,第二阶段预计的每小时租金,第三阶段使用前两个阶段的输出来预测故障成本。周期时间模型和租用成本模型都被证明是很好的预测指标,R'2的“高”值分别为0.86和0.95。英国国防部国防后勤组织的一名工厂专家验证了这些回归模型以及预测停机成本的过程。未来的研究工作将旨在增强所开发模型的预测能力,将研究范围扩大到其他机器类型,并以图形和表格格式重现研究结果,以改善对所生成信息的解释。

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