Towards Intelligent Surface Modification: The Role and Relevance of AI

Surface modifications are critical for several high-value applications, including aerospace, automotive, biomedical, and electronics, where they provide essential properties such as corrosion resistance, wear protection, and biocompatibility. However, traditional modification approaches often involve time-consuming characterisation and optimisation processes. The integration of smart manufacturing technologies, including AI, machine learning, and big data analytics, enables the development of predictive models that can optimise surface modification processes, monitor them in real time, and accurately predict the properties of the resulting surfaces. This integration not only reduces costs and time but also enhances the overall quality and efficiency of operations. While this is a rapidly evolving field, it still faces numerous challenges and bottlenecks, including issues with data quality and quantity, model complexity, and the need for domain expertise. Addressing these challenges is crucial for further advances and the automation of surface modification technologies. This chapter critically analyses the role, relevance, and impact of AI in advancing surface modifications, discusses its main challenges, and shares our views on its future research scope and directions.