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

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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.

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Abbreviations

\( \text{A}\,\Theta \,\text{B} \) :

A has an association with B

ct_abc :

URI of cutting tool abc

ft_abc :

URI of feature abc

mm_abc :

URI of machining methods abc

mstq_abc :

URI of quality measure tool abc

mps_abc :

URI of machining process status abc

mt_abc :

URI of machining tool abc

mts_abc :

URI of measure tool/sensor abc

mp_abc :

URI of machining process abc

qf_abc :

URI of quality feature abc

rXX :

The XXth response to sXX

sXX :

The XXth operation sequence

\( t_{P}^{s} \) :

Arriving timeline from the last process to the current process p

\( t_{P}^{si} \) :

Starting timeline of loading workpiece to machine tool table in process p

\( t_{P}^{ei} \) :

Ending timeline of loading workpiece in machine tool table in process p

\( t_{P}^{sp} \) :

Starting timeline of processing the workpiece in process p

\( t_{P}^{ep} \) :

Ending timeline to processing workpiece in process p

\( t_{P}^{so} \) :

Starting Timeline of putting workpiece off machine tool table in process p

\( t_{P}^{eo} \) :

Ending timeline of putting workpiece off machine tool table in process p

\( t_{P}^{e} \) :

Leaving timeline from the current process p

\( T_{P - 1}^{p} \) :

Transportation time from process p − 1 to process p

\( T_{P}^{x} \) :

Processing time of x in process p

wk_abc :

URI of worker abc

wp_abc :

URI of workpiece abc

APP:

Applications

CNC:

Computer numerical control

CPS:

Cyber-physical-system

ERP:

Enterprise resource planning

IDMW:

Industrial dataspace for machining workshop

MEPN:

Machining error propagation network

MES:

Manufacturing execution systems

MOC:

Machining operations control

NGIT:

New generation of information technology

OBDA:

Ontology-based data access

OWL:

Web ontology language

RFID:

Radio frequency identification

SQL:

Structured query language

URI:

Uniform resource identifier

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Acknowledgements

The research work is under the financial supports of the Natural Science Foundation of China with Grant Nos. 51975464 and 71571142. Thanks are also extended to the China Scholarships Council (CSC) and Brunel University London for hosting the academic scholarship.

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Authors and Affiliations

  1. State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, China

    Pulin Li & Pingyu Jiang

  2. College of Engineering, Design and Physical Science, Brunel University London, Uxbridge, UB8 3PH, UK

    Kai Cheng & Kanet Katchasuwanmanee

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  1. Pulin Li
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Correspondence to Pingyu Jiang.

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Li, P., Cheng, K., Jiang, P. et al. Investigation on industrial dataspace for advanced machining workshops: enabling machining operations control with domain knowledge and application case studies. J Intell Manuf 33, 103–119 (2022). https://doi.org/10.1007/s10845-020-01646-2

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