CPS Modeling of CNC Machine Tool Work Processes Using an Instruction-Domain Based Approach

Jihong Chen; Jianzhong Yang; Huicheng Zhou; Hua Xiang; Zhihong Zhu; Yesong Li; Chen-Han Lee; Guangda Xu

doi:10.15302/J-ENG-2015054

PDF(5345 KB)

Engineering ›› 2015, Vol. 1 ›› Issue (2) : 247-260. DOI: 10.15302/J-ENG-2015054

Research

CPS Modeling of CNC Machine Tool Work Processes Using an Instruction-Domain Based Approach

Author information +

History +

Abstract

Building cyber-physical system (CPS) models of machine tools is a key technology for intelligent manufacturing. The massive electronic data from a computer numerical control (CNC) system during the work processes of a CNC machine tool is the main source of the big data on which a CPS model is established. In this work-process model, a method based on instruction domain is applied to analyze the electronic big data, and a quantitative description of the numerical control (NC) processes is built according to the G code of the processes. Utilizing the instruction domain, a work-process CPS model is established on the basis of the accurate, real-time mapping of the manufacturing tasks, resources, and status of the CNC machine tool. Using such models, case studies are conducted on intelligent-machining applications, such as the optimization of NC processing parameters and the health assurance of CNC machine tools.

Keywords

cyber-physical system (CPS) / big data / computer numerical control (CNC) machine tool / electronic data of work processes / instruction domain / intelligent machining

Cite this article

EndNote

Ris (Procite)

Bibtex

Download citation ▾

Jihong Chen, Jianzhong Yang, Huicheng Zhou, Hua Xiang, Zhihong Zhu, Yesong Li, Chen-Han Lee, Guangda Xu. CPS Modeling of CNC Machine Tool Work Processes Using an Instruction-Domain Based Approach. Engineering, 2015, 1(2): 247‒260 https://doi.org/10.15302/J-ENG-2015054

References

Publishing order | Descend order by publishing year | Descend order by cited within

[1]	H. Kagermann, Recommendations for<?Pub Caret?> implementing the strategic initiative Industrie 4.0: Final report of the Industrie 4.0 Working Group. 2013

[2]	J. C. Jensen, D. H. Chang, E. A. Lee. A model-based design methodology for cyber-physical systems. In: Proceedings of the 7th International Wireless Communications and Mobile Computing Conference (IWCMC). New York: IEEE, 2011: 1666−1671

[3]	P. Derler, E. A. Lee, A. S. Vincentelli. Modeling cyber-physical systems. Proc. IEEE, 2012, 100(1): 13−28

[4]	Y. Wu, L. Chen. Simulation Optimization Method for Multi-domain Physical Systems. Beijing: Science Press, 2011 (in Chinese)

[5]	A. Vijayaraghavan, W. Sobel, A. Fox, D. Dornfeld, P. Warndorf. Improving machine tool interoperability using standardized interface protocols: MTConnect^TM. In: Proceedings of 2008 International Symposium on Flexible Automation (ISFA). Atlanta, GA, USA, 2008: 23−26

[6]

A. Kao, J. Lee, R. Lapira, S. Yang, Y. Huang, N. Yen. iFactory cloud service platform based on IMS tools and Servo-lution. In: J. Lee, J. Ni, J. Sarangapani, J. Mathew, eds. Engineering Asset Management 2011: Proceedings of the Sixth World Congress on Engineering Asset Management. London: Springer, 2011: 699−709

[7]	L. H. Wang. Machine availability monitoring and machining process planning towards Cloud manufacturing. CIRP J. Manuf. Sci. Technol., 2013, 6(4): 263−273

[8]	J. Lee, B. Bagheri, H. A. Kao. A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems. Manufacturing Letters, 2015, 3: 18−23

[9]	J. Lee, E. Lapira, B. Bagheri, H. Kao. Recent advances and trends in predictive manufacturing systems in big data environment. Manufacturing Letters, 2013, 1(1): 38−41

[10]	J. Wan, M. Chen, F. Xia, L. Di, K. Zhou. From machine-to-machine communications towards cyber-physical systems. Comput. Sci. Inf. Syst., 2013, 10(3): 1105−1128

[11]	J. Lee, F. Wu, W. Zhao, M. Ghaffari, L. Liao, D. Siegel. Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications. Mech. Syst. Signal Pr., 2014, 42(1−2): 314−334

[12]	V. Plapper, M. Weck. Sensorless machine tool condition monitoring based on open NCs. In: Proceedings of the 2001 IEEE International Conference on Robotics & Automation. New York: IEEE, 2001: 3104−3108

[13]	J. F. G. Oliveira, F. Ferraz Júnior, R. T. Coelho, E. J. Silva. Architecture for machining process and production monitoring based in open computer numerical control. Proc. Inst. Mech. Eng., B J. Eng. Manuf., 2008, 222(12): 1605−1612

Acknowledgements

The financial support of the studies is from the National Major Scientific and Technological Special Project for “Development and comprehensive verification of complete products of open high-end CNC system, servo device and motor” (2012ZX04001012). The authors thank the R&D team of National Numerical Control System Engineering Research Center, in particular, Hao Zhou, Chifei Ma, Cong Xue, Guotao Ding, Kun Ying, et al., for their contributions and supports. The authors also thank Professor Jay Lee and Dr. Wenjing Jin of Center for Intelligent Maintenance Systems (IMS Center) of University of Cincinnati, for their assistance.

Compliance with ethics guidelines

Jihong Chen, Jianzhong Yang, Huicheng Zhou, Hua Xiang, Zhihong Zhu, Yesong Li, Chen-Han Lee, and Guangda Xu declare that they have no conflict of interest or financial conflicts to disclose.

Funding