ARTIFICIAL INTELLIGENCE APPLIED TO THE ELECTROPLATING PROCESS FOR LOW CARBON STEELS: A LITERATURE REVIEW

Luciano M. L. OLIVEIRA; Juliano C. TONIOLO

Luciano M. L. OLIVEIRA Federal Institute of Education, Science and Technology of Rio Grande do Sul (IFRS), 95043-700, Caxias do Sul - RS, Brazil
Juliano C. TONIOLO Federal Institute of Education, Science and Technology of Rio Grande do Sul (IFRS), 95043-700, Caxias do Sul - RS, Brazil

Palavras-chave: Artificial intelligence, Electrodeposited zinc coating, Electroplating, XGBoost, Electrodeposition, Thickness prediction

Resumo

Technological advances in computing, specifically in the area of artificial intelligence (AI), have made it possible to apply methods that seek to reduce the response times of analyses in order to reduce costs and improve the quality and safety of operations. This work aims to carry out a literature review, on three axes and their interactions: electroplating, AI and low carbon steels seeking to identify what has been developed in relation to ML methods applied to the electroplating of carbon steels, optimising industrial processes and improving the final quality of galvanised products. The search was carried out on the Web of Science - Main Collection (Clarivate Analytics) database. This review found that studies in these areas are incipient and we therefore conclude that there is space for further research into the application of AI in the development of models for determining corrosion resistance in low carbon steel subjected to electroplating.