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Research on classification method of spare parts inventory based on warranty data

机译:基于保修数据的备件库存分类方法研究

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In this paper, we analyze the warranty data in after sales service, considering the reliability characteristic parameters of spare parts in use (MTBF), supply characteristics (replenishment lead time and supplier scarcity), part cost and part criticality. This paper constructs a multi-criteria classification model for ABC classification of spare parts by using intelligent machine classification approaches - support vector machine (SVM). The main contribution of this study is the interaction between warranty data and the multi-criteria SVM-ABC classification method. A case study is presented to illustrate the model. The test results show the good performance of this model.
机译:在本文中,我们分析了售后服务中的保修数据,其中考虑了使用中的备件(MTBF)的可靠性特征参数,供应特征(补货提前期和供应商稀缺性),零件成本和零件临界度。本文使用智能机器分类方法-支持向量机(SVM)构建了用于备件ABC分类的多准则分类模型。这项研究的主要贡献是保修数据与多标准SVM-ABC分类方法之间的相互作用。提出了一个案例研究来说明该模型。测试结果表明该模型具有良好的性能。

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