Machine learning and AI-driven digital twins in manufacturing of advanced metal alloys and compounds: A review

The advancements in manufacturing have been now revolutionized by implementation of machine learning (ML) and Artificial Intelligence (AI) approaches along with the Digital Twins (DTs). Manufacturing of alloys and compounds have been developed by applying ML and AI-driven DTs in order to provide intelligent monitoring, predictive maintenance and data processing systems during alloy manufacturing. As a result, information regarding microstructural analysis, structure-processing-property relation and effective approaches for optimal defect reduction can be obtained using the ML and AI-driven DTs during alloy manufacturing. Moreover, predictive modeling approaches for material properties, big data analysis, real-time process monitoring, online control approaches, optimized alloy production can be achieved by implementation of the ML and AI-driven DTs during alloy manufacturing. This review study analyzed novel advancements of ML and AI-based DTs applications in manufacturing of advanced metal alloys and compounds by considering and discussing recent achievement from research works. So, the applications and challenges of ML and AI-driven DTs during alloy manufacturing are discussed in the study in order to reduce processing costs, increase quality of produced alloys, optimize alloy production and enhance performance of produced alloys during working conditions. In order to provide guidelines for the future research works, novel ideas such as explainable AI models, combined AI and ML models in alloy manufacturing are also presented and discussed in the study. Furthermore, by presenting guidelines in the study to reduce waste materials and minimize power consumption during alloy production, a substantial development of alloy manufacturing can be achieved. Thus, the discussion of ML and AI-driven DTs during alloy manufacturing can provide guidelines for researchers in order to increase sustainability and productivity during manufacturing process of alloys and compounds.