人工智能
大数据
计算机科学
数据科学
工程类
纳米技术
认知科学
材料科学
心理学
数据挖掘
标识
DOI:10.1016/j.ifacol.2022.09.234
摘要
Digitalization is a key enabling factor of the dramatic transformation of metal industry since the 90-ies. Important applications were implemented since then, exploiting multi-physical modelling, complex real time process control and Machine Learning. This trend was further enhanced and accelerated by Industry 4.0. Digitalization implies harvesting impressive volumes of heterogeneous data, which need to be stored, processed and, mostly, interpreted to extract relevant information and “knowledge”. Knowledge means capability of interpreting data, of explaining and representing material transformation and product evolution during the different process stages considering complex interactions among process and product variables, including aspects still not perfectly understood. Artificial Intelligence supports knowledge extraction by enabling optimal process management and control, higher flexibility and product quality, stronger resource and energy efficiency, namely sustainability. Challenges and opportunities of enhancing metallurgical science and technology through Artificial intelligence are considered in this review.
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