Abstract Ultra-precision machining (UPM) technology is extensively applied to manufacture top quality products with high precision level and complicated geometry. As complicated machining factors affect the surface quality of machined components in UPM, large numbers of experiments for understanding the influences from particular machining factors are needed, leading overestimate or underestimate of significance of machining factors at certain machining conditions and raising of experimental cost. For these reasons, a crucial approach is urged to adapt for providing a fast track to an optimal machining condition. In this study, social network analysis (SNA) is introduced firstly to develop UPM network, which the network shows the relationship between dominant machining factors in UPM. A complicated UPM network containing interdependencies between each machining factor is generated by SNA. The determinations of network metrics in the UPM network support the selection of optimal machining factors under various machining conditions. Furthermore, the constructed UPM network using SNA provides the complete framework of dependencies in UPM for well predicting the machining outcomes when particular machining factors are adjusted in practical situations. The study contributes to offering a detail guideline for constructing machining strategies or experimental plans to efficiently achieve desired machining outcomes.

中文翻译：

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超精密制造中最佳加工条件的社会网络分析

摘要 超精密加工（UPM）技术被广泛应用于制造具有高精度水平和复杂几何形状的优质产品。由于复杂的加工因素影响UPM加工零件的表面质量，需要进行大量实验以了解特定加工因素的影响，导致在某些加工条件下高估或低估加工因素的重要性，增加实验成本。出于这些原因，迫切需要一种关键方法来适应提供快速通道以达到最佳加工条件。本研究首先引入社会网络分析（SNA）来开发UPM网络，该网络显示了UPM中主要加工因素之间的关系。SNA 生成了一个复杂的 UPM 网络，其中包含每个加工因素之间的相互依赖性。UPM 网络中网络度量的确定支持在各种加工条件下选择最佳加工因素。此外，使用 SNA 构建的 UPM 网络在 UPM 中提供了完整的依赖关系框架，以便在实际情况下调整特定加工因素时很好地预测加工结果。该研究有助于为构建加工策略或实验计划提供详细指南，以有效实现所需的加工结果。使用 SNA 构建的 UPM 网络提供了 UPM 中完整的依赖关系框架，用于在实际情况下调整特定加工因素时很好地预测加工结果。该研究有助于为构建加工策略或实验计划提供详细指南，以有效实现所需的加工结果。使用 SNA 构建的 UPM 网络提供了 UPM 中完整的依赖关系框架，用于在实际情况下调整特定加工因素时很好地预测加工结果。该研究有助于为构建加工策略或实验计划提供详细指南，以有效实现所需的加工结果。