Data-driven process control considering both geometric and loaded contact performance evaluations has been an increasingly important stage in field of spiral bevel and hypoid gears. A new data-driven manufacturing process control strategy is proposed for a high performance spiral bevel and hypoid gears. Here, to distinguish with the conventional simulated loaded tooth contact analysis (SLTCA) using economical finite element software package, the numerical loaded tooth contact analysis (NLTCA) is of more flexibility and practicality. In light of the advantages of the improved design for six sigma (DFSS), it is integrated with NLTCA for establishing a novel data-driven process control of gear manufacturing. Firstly, in improved DFSS framework, quality function deployment (QFD) is used to determine four sub-objective high-performance evaluation items. Then, their data-driven relationships between machine settings are respectively determined by using NLTCA. In particular, the manufacturing process control is further converted into multi-objective optimization (MOO) modification of the hypoid generator settings. Finally, an interactive preference point approach is applied for data-driven control of its iterative step and it can obtain a robust solution from Pareto optimal front. A case study is provided to verify the proposed methodology.

中文翻译：

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通过使用考虑数值加载齿接触分析 (NLTCA) 的六西格玛 (DFSS) 设计，用于制造螺旋锥齿轮和准双曲面齿轮的数据驱动过程控制

考虑几何和负载接触性能评估的数据驱动过程控制已成为螺旋锥齿轮和准双曲面齿轮领域日益重要的阶段。针对高性能螺旋锥齿轮和准双曲面齿轮，提出了一种新的数据驱动制造过程控制策略。这里，与传统的使用经济型有限元软件包的模拟加载齿接触分析（SLTCA）不同，数值加载齿接触分析（NLTCA）更具灵活性和实用性。鉴于六西格玛改进设计（DFSS）的优点，它与NLTCA集成，建立了一种新颖的数据驱动的齿轮制造过程控制。首先，在改进的DFSS框架中，利用质量功能展开（QFD）确定四个子目标高性能评价项。然后，使用 NLTCA 分别确定机器设置之间的数据驱动关系。特别是，制造过程控制进一步转换为准双曲线发生器设置的多目标优化（MOO）修改。最后，应用交互式偏好点方法对其迭代步骤进行数据驱动控制，并且可以从帕累托最优前沿获得鲁棒解决方案。提供了一个案例研究来验证所提出的方法。