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Article summary:
1. This article presents a twin data and knowledge-driven intelligent process planning framework of aviation parts.
2. The research was supported by the National Key Research and Development Program of China, National Natural Science Foundation of China, and China National Postdoctoral Program for Innovative Talents.
3. The authors are Jingjing Li, Guanghui Zhou, and Chao Zhang from the School of Mechanical Engineering at Xi’an Jiaotong University in China.
Article analysis:
The article is generally trustworthy and reliable as it is based on research conducted by three authors from the School of Mechanical Engineering at Xi’an Jiaotong University in China who have been supported by various grants from the Chinese government. The article does not appear to be biased or one-sided as it provides an overview of the research conducted without making any unsupported claims or omitting any points of consideration. Furthermore, the article does not contain any promotional content or partiality towards any particular viewpoint or opinion. Additionally, possible risks associated with the research are noted in the acknowledgements section. In conclusion, this article appears to be trustworthy and reliable as it is based on sound research that has been adequately funded and presented in an unbiased manner.