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Investigation on industrial dataspace for advanced machining workshops: enabling machining operations control with domain knowledge and application case studies
Journal of Intelligent Manufacturing ( IF 8.3 ) Pub Date : 2020-08-29 , DOI: 10.1007/s10845-020-01646-2
Pulin Li , Kai Cheng , Pingyu Jiang , Kanet Katchasuwanmanee

The machining processes on the advanced machining workshop floor are becoming more sophisticated with the interdependent intrinsic processes, generation of ever-increasing in-process data and machining domain knowledge. To manage and utilize those above effectively, an industrial dataspace for machining workshop (IDMW) is presented with a three-layer framework. The IDMW architecture is Schema CentralizedData Distributed, which relies on Process-Workpiece-Centric knowledge schema description and data storage in decentralized data silos. Subsequently, the pre-processing method for the data silos driven by RFID event graphical deduction model is elaborated to associate decentralized data with knowledge schema. Furthermore, through two industrial case studies, it is found that IDMW is effective in managing heterogeneous data, interconnecting the resource entities, handling domain knowledge, and thereby enabling machining operations control on the machining workshop floor particularly.



中文翻译:

研究高级加工车间的工业数据空间:利用领域知识和应用案例研究实现对加工操作的控制

相互依赖的内在过程,不断增长的过程中数据和加工领域知识的产生,使高级加工车间地板上的加工过程变得越来越复杂。为了有效地管理和利用以上内容,提出了一个具有三层框架的加工车间工业数据空间(IDMW)。IDMW体系结构是架构集中的数据分布式,它依赖于以过程为中心的知识模式描述和分散数据孤岛中的数据存储。随后,阐述了由RFID事件图形推导模型驱动的数据孤岛的预处理方法,以将分散的数据与知识模式相关联。此外,通过两个行业案例研究,发现IDMW在管理异构数据,互连资源实体,处理领域知识以及特别是在加工车间地板上进行加工操作控制方面非常有效。

更新日期:2020-08-29
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