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A cyber-physical machine tool framework based on STEP-NC

Kubota, Tsubasa, Liu, Chao, Mubarok, Khamdi and Xu, Xun 2018. A cyber-physical machine tool framework based on STEP-NC. Presented at: The 48th International Conference on Computers and Industrial Engineering (CIE 48), Auckland, New Zealand, 02 December 2018. Proceedings of International Conference on Computers and Industrial Engineering. -.

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Abstract

Cyber-Physical Machine Tool (CPMT) is one of the main concepts that has emerged with the rise of Industry 4.0 and Machine Tool 4.0. It integrates the physical machine tool and machining processes with computation and networking by creating a Machine Tool Digital Twin (MTDT). Standard for the Exchange of Product data compliant Numerical Control (STEP-NC) defines a machine independent bi-directional data standard for Computer Numerical Control (CNC) systems. It is capable of transferring richer information compared to conventional G-codes. All machine tools in the manufacturing field have physical variances between each other which affect the final machining quality. At present, physical variances between machines are manually compensated by human experiences which is not a consistent method. In this paper, we propose an intelligent CPMT framework for machining parameter optimization based on STEP-NC data model with the capability of taking the physical variances between machine tools into account. This framework correlates real-time physical and numerical data of the machine tool with the rich machining information contained in the STEP-NC model to establish a sustainable machining knowledge base. Established machining knowledge base is utilized for both offline and real-time machining parameter optimizations inside the framework.

Item Type: Conference or Workshop Item (Paper)
Date Type: Published Online
Status: Published
Schools: Engineering
Subjects: T Technology > TJ Mechanical engineering and machinery
Date of First Compliant Deposit: 17 July 2019
Date of Acceptance: 1 November 2018
Last Modified: 17 Jul 2019 15:43
URI: http://orca.cf.ac.uk/id/eprint/123830

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