The study highlighted the significance of data quality, particularly, when leveraging historical data and presented a use case for design augmentation and comprehensive analysis of interdependencies in lithium-ion electrode manufacturing. The enhanced dataset was combined with explainable machine learning methods to predict the mechanical and electrochemical properties of the electrodes produced on a pilot production line.

中文翻译：

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电极制造中的相互依赖性：基于设计增强和可解释机器学习的综合研究

该研究强调了数据质量的重要性，特别是在利用历史数据时，并提出了锂离子电极制造中设计增强和相互依赖性综合分析的用例。增强的数据集与可解释的机器学习方法相结合，以预测中试生产线上生产的电极的机械和电化学特性。