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Big data and machine learning: A roadmap towards smart plants
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作者 Bogdan DORNEANU Sushen ZHANG +4 位作者 Hang RUAN mohamed heshmat Ruijuan CHEN Vassilios SVASSILIADIS Harvey ARELLANO-GARCIA 《Frontiers of Engineering Management》 2022年第4期623-639,共17页
Industry 4.0 aims to transform chemical and biochemical processes into intelligent systems via the integration of digital components with the actual physical units involved.This process can be thought of as addition o... Industry 4.0 aims to transform chemical and biochemical processes into intelligent systems via the integration of digital components with the actual physical units involved.This process can be thought of as addition of a central nervous system with a sensing and control monitoring of components and regulating the performance of the individual physical assets(processes,units,etc.)involved.Established technologies central to the digital integrating components are smart sensing,mobile communication,Internet of Things,modelling and simulation,advanced data processing,storage and analysis,advanced process control,artificial intelligence and machine learning,cloud computing,and virtual and augmented reality.An essential element to this transformation is the exploitation of large amounts of historical process data and large volumes of data generated in real-time by smart sensors widely used in industry.Exploitation of the information contained in these data requires the use of advanced machine learning and artificial intelligence technologies integrated with more traditional modelling techniques.The purpose of this paper is twofold:a)to present the state-of-the-art of the aforementioned technologies,and b)to present a strategic plan for their integration toward the goal of an autonomous smart plant capable of self-adaption and self-regulation for short-and long-term production management. 展开更多
关键词 big data machine learning artificial intelligence smart sensor cyber–physical system Industry 4.0 intelligent system DIGITALIZATION
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