The aerospace industry seeks to achieve net‐zero carbon emissions by 2050 through innovations such as advanced surface solutions, including abradable and thermal barrier coatings. These coatings, deposited primarily via plasma spraying technologies like atmospheric plasma spraying and suspension plasma spraying, enhance engine efficiency and component longevity. However, the complexity and variability of plasma spraying processes pose significant challenges for consistent coating performance. This article gives an overview of the current state of data collection and ontology for aerospace coatings, focusing on the integration of in situ and operando sensors to monitor the plasma torch, plasma jet, and coating subsystems. Key challenges include arc instabilities, particle temperature and velocity control, and real‐time assessment of coating properties. The study highlights the potential of advanced sensing technologies, machine learning, and structured ontologies—such as the European materials and modeling ontology—to improve process control, data interoperability, and digital twin development. By addressing these challenges, the digital transformation of plasma spraying processes can enhance efficiency, sustainability, and coating performance in industrial applications.
Randriamananjara et al. (Sat,) studied this question.