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A knowledge-based Digital Shadow for machining industry in a Digital Twin perspective
یک سایه دیجیتال مبتنی بر دانش برای صنعت ماشینکاری در یک چشم انداز دیجیتال دوتایی-2021 This paper addresses the problems of data management and analytics for decision-aid by proposing a new vision
of Digital Shadow (DS) which would be considered as the core component of a future Digital Twin. Knowledge
generated by experts and artificial intelligence, is transformed into formal business rules and integrated into the
DS to enable the characterization of the real behavior of the physical system throughout its operation stage. This
behavior model is continuously enriched by direct or derived learning, in order to improve the digital twin. The
proposed DS relies on data analytics (based on unsupervised learning) and on a knowledge inference engine. It
enables the incidents to be detected and it is also able to decipher its operational context. An example of this
application in the aeronautic machining industry is provided to stress both the feasibility of the proposition and
its potential impact on shop floor performance. keywords: سایه دیجیتال | دوقلو | داده ها و مدیریت دانش | ماشینکاری | Digital shadow | Digital twin | Data and knowledge management | Machining |
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