Investigation on industrial dataspace for advanced machining workshops: enabling machining operations control with domain knowledge and application case studies

Abstract

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 Centralized-Data 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.

Digital Twins-Based Smart Design and Control of Ultra-Precision Machining: A Review

“…The parameters together their complicated relations affecting product quality in UPM Prediction while considering the influence of working conditions on product quality [32][33][34][35]…”

“…Chen et al [47] proposed a digital twin-based straightening quality control method for slender rod straightening. Li et al [32] presented a three-layer process-workpiece-centric knowledge schema framework for predicting the machining quality of multiple products. Pan et al [33] discussed artificial intelligence-based to ground surface roughness prediction for evaluating the efficiency of the grinding process and guiding the feedback control of the grinding parameters in real-time to reduce the cost of production.…”

Assembly process case matching based on a multilevel assembly ontology method

“…(Li and Chai, 2002;Chang et al, 2009), which requires high efficiency and low-cost generation of an assembly process (Zhang et al, 2014;Gao et al, 2002). Referring to the assembly knowledge and assembly design experience of similar products can facilitate the above demand (Li et al, 2020a;Gertosio and Dussauchoy, 2004).…”