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Research on data mining technology for the connotation and measurement of uncertainty for reassembly dimensions

机译:数据挖掘技术在装配尺寸不确定性的内涵和度量中的研究

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摘要

The uncertainty of remanufactured parts is a key factor in the stability of remanufacturing systems. Therefore, the purpose of this paper is to identify these uncertainties and measure them to improve the optimisation management level of remanufacturing production process. Contrasting the ideal dimensional accuracy, manufactured dimensional accuracy and remanufactured dimensional accuracy, we analyse the connotation of uncertainty for reassembly dimensions. We construct the uncertainty measurement model for reassembly dimensions to realise quantitative measurement by entropy. So the coupling mechanism of uncertainty for reassembly dimensions is studied and the corollary is in conformity with the reality. It can use data mining technology to optimise remanufacturing process management. Finally, the feasibility and effectiveness of the model are verified in grading selection of remanufacturing enterprise parts. This research provides support for the uncertain optimisation decision for lean remanufacturing from both theoretical and practical aspects by uncertain data mining techniques.
机译:再制造零件的不确定性是再制造系统稳定性的关键因素。因此,本文的目的是找出这些不确定性并进行测量,以提高再制造生产过程的优化管理水平。通过比较理想的尺寸精度,制造的尺寸精度和再制造的尺寸精度,我们分析了重新装配尺寸的不确定性的内涵。我们构建了用于装配尺寸的不确定性测量模型,以实现熵的定量测量。因此,研究了不确定性的重组尺寸耦合机理,其推论与现实相符。它可以使用数据挖掘技术来优化再制造过程管理。最后,验证了该模型在再制造企业零件分级选择中的可行性和有效性。这项研究通过不确定的数据挖掘技术从理论和实践两个方面为精益再制造的不确定性优化决策提供了支持。

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