Opportunities and Challenges for Predicting the Service Status of SLM Metal Parts Under Big Data and Artificial Intelligence DOI Open Access
Xiaoling Yan,

Huiwen Fu

Materials, Journal Year: 2024, Volume and Issue: 17(22), P. 5648 - 5648

Published: Nov. 19, 2024

Selective laser melting (SLM) technology is a high-end dual-use that implemented in aerospace and medical equipment, as well the automotive industry other military civilian industries, urgently needed for major equipment manufacturing national defense industries. This paper examines challenges of uncontrollable service states inability to ensure safety SLM metal parts under nonlinear complex operating conditions. An overview prediction status was introduced, an effective approach solving problem provided this paper. In approach, cross-scale coupling mechanism between mesoscopic damage evolution macroscopic state clarified by tracking process based on ultrasonic responses. The failure organically integrated with hidden information from monitoring big data, “chimeric” model accurately evaluate constructed. Combining ultrasound data artificial intelligence construct consummate corresponding methods theories evaluating way reveal mechanisms factor coupling, describe characterize proposed will provide theoretical basis technical guarantee precise management parts’ key fields such aerospace, industry.

Language: Английский

Prognostics for the Sustainability of Industrial Cyber-Physical Systems: From an Artificial Intelligence Perspective DOI
Jiusi Zhang, Jilun Tian, Hao Luo

et al.

IEEE Transactions on Industrial Cyber-Physical Systems, Journal Year: 2024, Volume and Issue: 2, P. 495 - 507

Published: Jan. 1, 2024

Language: Английский

Citations

1

Opportunities and Challenges for Predicting the Service Status of SLM Metal Parts Under Big Data and Artificial Intelligence DOI Open Access
Xiaoling Yan,

Huiwen Fu

Materials, Journal Year: 2024, Volume and Issue: 17(22), P. 5648 - 5648

Published: Nov. 19, 2024

Selective laser melting (SLM) technology is a high-end dual-use that implemented in aerospace and medical equipment, as well the automotive industry other military civilian industries, urgently needed for major equipment manufacturing national defense industries. This paper examines challenges of uncontrollable service states inability to ensure safety SLM metal parts under nonlinear complex operating conditions. An overview prediction status was introduced, an effective approach solving problem provided this paper. In approach, cross-scale coupling mechanism between mesoscopic damage evolution macroscopic state clarified by tracking process based on ultrasonic responses. The failure organically integrated with hidden information from monitoring big data, “chimeric” model accurately evaluate constructed. Combining ultrasound data artificial intelligence construct consummate corresponding methods theories evaluating way reveal mechanisms factor coupling, describe characterize proposed will provide theoretical basis technical guarantee precise management parts’ key fields such aerospace, industry.

Language: Английский

Citations

0