A new high-performance open CNC system and its energy-aware scheduling algorithm

  • Chang-yi Deng
  • Rui-feng Guo
  • Xun Xu
  • Ray Y Zhong
  • Zhenyu Yin
ORIGINAL ARTICLE
  • 119 Downloads

Abstract

Computer numerical control (CNC) systems are shifting to a direction of open architecture which has better flexibility, adaptability, versatility, and expansibility. Existing CNC systems tend to have a high level energy consumption. This paper introduces a new open CNC system based on the low-power embedded platform, named open and high-performance CNC (OHP-CNC). OHP-CNC is able to achieve high precision, high efficiency, and low power consumption by making use of international standards, open components such as hardware and software, and an energy-aware real-time scheduling algorithm. The proposed algorithm for mixed tasks, including periodic and aperiodic tasks, is divided into two phases. Firstly, the slack time and utilization are calculated on each processor and tasks are assigned to the processor according to the load. Secondly, because there is a trade-off between the energy-saving and the response times of the aperiodic task, the scheduling server is used to schedule aperiodic tasks in order to meet the response time constraints of aperiodic tasks. Meanwhile, periodic tasks recycle the slack time with dynamic voltage scaling technology to achieve low power consumption. Experiment results show that the energy-aware real-time algorithm yields high-performance and effective machining processes.

Keywords

CNC Open architecture Energy-aware Real-time system 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Reference

  1. 1.
    Wang K, Zhang C, Xu X, Ji S, Yang L (2013) A CNC system based on real-time Ethernet and Windows NT. Int J Adv Manuf Technol 65(9–12):1383–1395CrossRefGoogle Scholar
  2. 2.
    Yusof Y, Latif K (2015) A novel ISO 6983 interpreter for open architecture CNC systems. Int J Adv Manuf Technol 80(9–12):1777–1786CrossRefGoogle Scholar
  3. 3.
    Xu X (2012) From cloud computing to cloud manufacturing. Robot Comput Integr Manuf 28(1):75–86CrossRefGoogle Scholar
  4. 4.
    Pritschow G, Altintas Y, Jovane F, Koren Y, Mitsuishi M, Takata S et al (2001) Open controller architecture—past, present and future. CIRP Annals-Manufacturing Technology 50(2):463–470CrossRefGoogle Scholar
  5. 5.
    Han ZY, Wang YZ, Fu HY (2007) Development of a PC-based open architecture software-CNC system. Chin J Aeronaut 20(3):272–281CrossRefGoogle Scholar
  6. 6.
    Zhou L, Yuan JL, Gao P, Ren YH (2014) A new architecture of open CNC system based on compiling mode. Int J Adv Manuf Technol 73(9–12):1597–1603CrossRefGoogle Scholar
  7. 7.
    Blem E, Menon J, Vijayaraghavan T, Sankaralingam K (2015) ISA wars: understanding the relevance of ISA being RISC or CISC to performance, power, and energy on modern architectures. ACM Transactions on Computer Systems (TOCS) 33(1):3CrossRefGoogle Scholar
  8. 8.
    OSACA Association (2001) OSACA handbook. Version 2.0. OSACA Association. StuttgartGoogle Scholar
  9. 9.
    OMAC API work group (1999) OMAC API SET. Version 0.23. OMAC API Work Group, Detroit, USA.Google Scholar
  10. 10.
    OSE Consortium, OSEC-II Project, Tech. Rep., 1998. [Online]. Available: http://www.mli.co.jp/OSE/
  11. 11.
    Wright PK, Greenfeld I (1990) Open architecture manufacturing: the impact of open-system computers on self-sustaining machinery and the machine tool industry. Proc Manufacturing International’90 2:41–47Google Scholar
  12. 12.
    Yu D, Hu Y, Xu XW, Huang Y, Du S (2009) An open CNC system based on component technology. IEEE Trans Autom Sci Eng 6(2):302–310CrossRefGoogle Scholar
  13. 13.
    Erwinski K, Paprocki M, Grzesiak LM, Karwowski K, Wawrzak A (2013) Application of Ethernet Powerlink for communication in a Linux RTAI open CNC system. IEEE Trans Ind Electron 60(2):628–636CrossRefGoogle Scholar
  14. 14.
    Wu J, Li D, Wang S The design and experimental research of an open architecture soft-CNC system based on RTX and an IPC. Int J Adv Manuf Technol:1–13Google Scholar
  15. 15.
    Latif K, Yusof Y, Nassehi A, Latif QBAI (2016) Development of a feature-based open soft-CNC system. Int J Adv Manuf Technol:1–12Google Scholar
  16. 16.
    Huang H, Chi G, Wang Z (2016) Development and application of software for open and soft multi-axis EDM CNC systems. Int J Adv Manuf Technol 86(9–12):2689–2700CrossRefGoogle Scholar
  17. 17.
    Hu P, Han Z, Fu H, Han D (2016) Architecture and implementation of closed-loop machining system based on open STEP-NC controller. Int J Adv Manuf Technol 83(5–8):1361–1375CrossRefGoogle Scholar
  18. 18.
    Shin D, Kim J (2006) Dynamic voltage scaling of mixed task sets in priority-driven systems. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 25(3):438–453CrossRefGoogle Scholar
  19. 19.
    Lee CH, Shin KG (2004) On-line dynamic voltage scaling for hard real-time systems using the EDF algorithm. In: Real-time systems symposium, 2004. Proceedings. 25th IEEE international. IEEE, New York, pp 319–335Google Scholar
  20. 20.
    Wang G, Li W, Hei X (2015) Energy-aware real-time scheduling on heterogeneous multi-processor. In: Information sciences and systems (CISS), 2015 49th annual conference on. IEEE, New York, pp 1–7Google Scholar
  21. 21.
    Doh Y, Kim D, Lee YH, Krishna CM (2004) Constrained energy allocation for mixed hard and soft real-time tasks. In: Real-time and embedded computing systems and applications. Springer, Berlin Heidelberg, pp 371–388CrossRefGoogle Scholar
  22. 22.
    Qi B, Liu S, Shen Q, Liao S, Lin Z, Cai W, ... & An Q (2014) A compact PCI-based measurement and control system for satellite-ground quantum communication. arXiv preprint arXiv:1406.3953.Google Scholar
  23. 23.
    Dang TT, Kim JH, Jeon JW (2013) Performance analysis of Mechatrolink-III. In: Industrial informatics (INDIN), 2013 11th IEEE international conference on. IEEE, New York, pp 152–157CrossRefGoogle Scholar
  24. 24.
    International Electrotechnical Commission (2007) Industrial communication networks–Fieldbus specifications–Part 3–12: data-link layer service definition–Part 4–12: datalink layer protocol specification–Type 12 elements. IEC, Dec 61(1):58–53Google Scholar
  25. 25.
    Zhong RY, Dai Q, Qu T, Hu G, Huang GQ (2013) RFID-enabled real-time manufacturing execution system for mass-customization production. Robot Comput Integr Manuf 29(2):283–292CrossRefGoogle Scholar
  26. 26.
    Xu X (2017) Machine Tool 4.0 for the new era of manufacturing. The International Journal of Advanced Manufacturing Technology. doi: 10.1007/s00170-017-0300-7
  27. 27.
    Abeni L, Buttazzo G (1998) Integrating multimedia applications in hard real-time systems. In: Real-Time Systems Symposium, 1998. Proceedings. The 19th IEEE. IEEE, New York, pp 4–13Google Scholar
  28. 28.
    Zhong RY, Huang GQ, Dai QY, Zhang T (2014) Mining SOTs and dispatching rules from RFID-enabled real-time shopfloor production data. J Intell Manuf 25(4):825–843CrossRefGoogle Scholar
  29. 29.
    Aydin H, Melhem R, Mossé D, Mejia-Alvarez P (2001) Dynamic and aggressive scheduling techniques for power-aware real-time systems. In: Real-Time Systems Symposium, 2001.(RTSS 2001). Proceedings. 22nd IEEE. IEEE, New York, pp 95–105Google Scholar
  30. 30.
    Sahuquillo J, Hassan H, Petit S, March JL, Duato J (2016) A dynamic execution time estimation model to save energy in heterogeneous multicores running periodic tasks. Futur Gener Comput Syst 56:211–219CrossRefGoogle Scholar
  31. 31.
    Schlechtendahl J, Kretschmer F, Sang Z, Lechler A, Xu X (2017) Extended study of network capability for cloud based control systems. Robot Comput Integr Manuf 43:89–95CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2017

Authors and Affiliations

  • Chang-yi Deng
    • 1
    • 2
    • 3
  • Rui-feng Guo
    • 1
    • 3
  • Xun Xu
    • 2
  • Ray Y Zhong
    • 2
  • Zhenyu Yin
    • 1
    • 3
  1. 1.Shenyang Institute of Computing TechnologyChinese Academy of SciencesShenyangChina
  2. 2.Department of Mechanical EngineeringUniversity of AucklandAucklandNew Zealand
  3. 3.University of Chinese Academy of SciencesBeijingChina

Personalised recommendations