Development of machine tools design and operational properties

  • Jerzy Jedrzejewski
  • Wojciech Kwasny


This paper presents the main directions in the development of machine tools, their producers’ and users’ business determinants, and the current and future development of intelligent machine tools, ensuring, among other things, their high productivity and machining accuracy. The role of the modelling and simulation of operational properties in the state-of-the-art improvement of machine tools and the importance of increasing the precision of the latter taking into account the carried out process are discussed. Much attention is also given to the energy intensity of machine tools and machining processes from both the technical and economic point of view. In conclusions, expectations as to the further development of machine tools are formulated.


Intelligence High performance Accuracy Holistic modelling Simulation Energy consumption 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Jedrzejwski J, Kwasny W (2013) Knowledge base and assumptions for holistic modelling aimed at reducing axial errors of complex machine tools. Journal of Machine Engineering 13(2):7–25Google Scholar
  2. 2.
    Brecher C (2009) Interaction of manufacturing process and machine tool. CIRP Ann-Manuf Techn 58(2):588–607CrossRefGoogle Scholar
  3. 3.
    Mayr J, Jedrzejewski J, Uhlmann E, Donmez MA, Knapp W, Hartig F, Wendt K, Moriwaki T, Shore P, Schmitt R, Brecher C, Wurz T, Wegener K (2012) Thermal issues in machine tools. CIRP Ann-Manuf Techn 61:771–791CrossRefGoogle Scholar
  4. 4.
    Tsuchiya S (2010) Continuously renovating machines and systems adaptable for new era. Proceedings of the 14th International Machine Toll Engineers Conference, Tokyo Japan: 13–25Google Scholar
  5. 5.
    Weck M (1995) Reduction and compensation of thermal errors in machine tools. CIRP Ann-Manuf Techn 44(2):598–598CrossRefGoogle Scholar
  6. 6.
    Moriwaki T (1993) Intelligent machine tool. Journal of JSME 96(901):1010–1014Google Scholar
  7. 7.
    Shirase K, Nakamoto K (2013) Simulation technologies for the development of an autonomous and intelligent machine tool. Int J Autom Technol 7(1):6–15CrossRefGoogle Scholar
  8. 8.
    Shirase K (2014) Advanced technologies, to achieve intelligent machine tool. Proceedings of the 16th IMEC, Tokyo Japan: 119–128Google Scholar
  9. 9.
    Suzuki Y (2014) Development of intelligent functions of machine tools, Proc. of the 16th IMEC, Tokyo Japan: 139–159Google Scholar
  10. 10.
    Jedrzejewski J, Kwasny W (1992) Multisensor system for diagnosing machine tools. Instrumentation and Measurement Technology Conference, IMTC ‘'92, 9th IEEE: 194–199Google Scholar
  11. 11.
    Altintas Y, Kersting P, Biermann D, Budak E, Denkena B, Lazoglu I (2014) Virtual process systems for part machining operations. CIRP Ann-Manuf Techn 63:585–605CrossRefGoogle Scholar
  12. 12.
    Fortunato A, Ascari A (2013) The virtual design of machining centers for HSM: towards new integrated tools. Mechatronics 23:264–278CrossRefGoogle Scholar
  13. 13.
    Jedrzejewski J, Kwasny W, Kowal Z, Winiarski Z (2014) In-house system for holistic modelling of machine tool operating properties. 2nd International Conference on Systems and Informatics, ICSAI 2014, Shanghai China: 409–414Google Scholar
  14. 14.
    Jedrzejewski J, Kwasny W (2015) A step towards the holistic modelling of the HSC machining centre and the efficient compensation of its errors. Int J Comput Integ M 28(1):126–136CrossRefGoogle Scholar
  15. 15.
    Moehring HCH (2014) Advanced materials in machine tool structures. Proc. of the 16th IMEC, Tokyo Japan: 76–88Google Scholar
  16. 16.
    Neugebauer R, Denkena B, Wegener K (2007) Mechatronic systems for machine tools. CIRP Ann-Manuf Techn 56(2):657–686CrossRefGoogle Scholar
  17. 17.
    Nishiyama Y (2014) High-speed, high accuracy & high quality machining of machine tools by adopting new materials, Proc. of the 16th IMEC, Tokyo, Japan, 89–96Google Scholar
  18. 18.
    Wagner P Simulation in design of high performance machine tool, Gebr. HELLER Maschinenfabrik GmbH
  19. 19.
    Schäfers E, Denk J, Hamann J (2006) Mechatronic modeling and analysis of machine tools. Proceedings of the CIRP 2nd International Conference on High Performance Cutting (HPC'06), VancouverGoogle Scholar
  20. 20.
    Sulitka M, Sindler J, Susen J (2014) Coupled modelling for machine tool structural optimization. Journal of Machine Engineering 14(3):21–34Google Scholar
  21. 21.
    Kwasny W, Turek P, Jedrzejewski J (2011) Survey of machine tool error measuring methods. Journal of Machine Engineering 11(4):7–38Google Scholar
  22. 22.
    Knap W (2012) Trends and future possibilities of ISO standards for machine tools–accuracy tests, capability tests and environmental assessment. The 15th International Machine Tool Engineers’ Conference (IMEC), Tokyo Japan, 2–3 November: 33–45Google Scholar
  23. 23.
    Schwenke H, Knappp W, Haitjema H, Weckenmann A, Schmitt R, Delbressine F (2008) Geometric error measurement and compensation of machines—an update. CIRP Ann-Manuf Techn 57(2):660–675CrossRefGoogle Scholar
  24. 24.
    Jedrzejewski J, Kwasny W (2010) Modelling of angular contact ball bearings and axial displacements for high-speed spindles. CIRP Ann-Manuf Techn 59:377–382CrossRefGoogle Scholar
  25. 25.
    Jedrzejewski J, Kwasny W, Kowal Z, Winiarski Z (2014) Development of the modelling and numerical simulation of the thermal properties of machine tools. Journal of Machine Engineering 14(3):5–20Google Scholar
  26. 26.
    Verl A, Frey S (2010) Correlation between feed velocity and preloading in ball screw drives. CIRP Ann-Manuf Techn 59(1):429–432CrossRefGoogle Scholar
  27. 27.
    Kehl G, Wagner P (2014) Simulation method for determining the thermally induced displacement of machine tools—experimental validation and utilization in the design process. World Academy of Science, Engineering and Technology International Journal of Mechanical, Aerospace, Industrial and Mechatronics Engineering 8(11):1777–1784Google Scholar
  28. 28.
    Turek P, Jedrzejewski J, Modrzycki W (2010) Methods of machine tool error compensation. Journal of Machine Engineering 10(4):5–26Google Scholar
  29. 29.
    Hong JW, Chen JS (2012) Dynamic thermal error modeling of a built-in permanent magnet motor high-speed spindle. MM Science Journal, 9th International Conference on Machine Tools, Automation, Technology and Robotics, Prague, Czech Republic, ISSN 1803–1269Google Scholar
  30. 30.
    Horejs O, Mares M, Hornych J (2013) Complex verification of thermal error compensation model of a portal milling centre. International Conference NEWTECH 2013, Stockholm Sweden: 322–332Google Scholar
  31. 31.
    Mares M, Horejs O, Hornych J (2013) Robust thermal error compensation model of portal milling centre based on superposition of participating thermal sources. International Conference NEWTECH 2013, Stockholm Sweden: 22–332Google Scholar
  32. 32.
    Mares M, Smolik J (2013) Robustness and portability of machine tool thermal error compensation model based on control of participating thermal sources. Journal of Machine Engineering 13(1):24–36Google Scholar
  33. 33.
    Jedrzejewski J, Kwasny W, Kowal Z, Modrzycki W (2008) Precise model of HSC machining centre for aerospace parts machining. Journal of Machine Engineering 8(3):29–41Google Scholar
  34. 34.
    Jedrzejwski J, Kwasny W, Modrzycki W (2011) Identification and reduction of thermal errors in high performance 5-axis machining centre. Total Quality Management & Excellence 39(1):17–22Google Scholar
  35. 35.
    Mori M, Fujishima M, Inamasu Y, Oda Y (2011) A study on energy efficiency improvement for machine tools. CIRP Ann-Manuf Techn 60:145–148CrossRefGoogle Scholar
  36. 36.
    Altintas Y, Verl A, Brecher C, Uriarte L, Pritschow G (2011) Machine tool feed drives. CIRP Ann-Manuf Techn 60(2):779–796CrossRefGoogle Scholar
  37. 37.
    Abele E, Altintas Y, Brecher C (2010) Machine tool spindle units. CIRP Ann-Manuf Techn 59(4):781–802CrossRefGoogle Scholar
  38. 38.
    Wang Z, Soshi M, Yamazaki K (2010) A comparative study on the spindle system equipped with synchronous and induction servo motors for heavy duty milling with highly stable torque control. CIRP Ann-Manuf Techn 59:369–372CrossRefGoogle Scholar
  39. 39.
    Soshi M, Yu S, Ishii S, Yamazaki Y (2011) Development of a high torque—high power spindle system equipped with a synchronous motor for high performance cutting. CIRP Ann-Manuf Techn 60(1):399–402CrossRefGoogle Scholar
  40. 40.
    Brecher C, Trofimov Y, Bäumler S (2011) Holistic modelling of process machine interactions in parallel milling. CIRP Ann-Manuf Techn 60(1):387–390CrossRefGoogle Scholar
  41. 41.
    Brecher CH (2011) Resource efficiency in machine tool design. Proceedings of Machener Werkzeugmaschinen KolloquiumGoogle Scholar
  42. 42.
    Denkena B, Flüeter F, Huelsemeyer L (2012) Energy-efficient machine tools and technologies. The 15th International Machine Tool Engineers’ Conference (IMEC), Tokyo, Japan, 2–3 November 2012: 174–187Google Scholar
  43. 43.
    Dietmair A, Verl A, Eberspaecher P (2009) Predictive simulation for model based energy consumption optimization in manufacturing systems and machine control. Proceedings of International Conference on Flexible Automation and Intelligent Manufacturing, FEIM 2009, Teeside UK: 226–233Google Scholar
  44. 44.
    Neugebauer R, Drossel W, Wertheim R, Hochmuth C, Dix M (2012) Resource and energy efficiency in machining using high-performance and hybrid processes. 5th CIRP Conference on High Performance Cutting, Procedia CIRP 1:3–16Google Scholar
  45. 45.
    Duflou J, Sutherland J, Dornfeld D, Herrmann C, Jeswiet J, Kara S, Hauschild M, Kellens K (2012) Towards energy and resource efficient manufacturing: a process and systems approach. CIRP Ann-Manuf Techn 61(2):587–609CrossRefGoogle Scholar
  46. 46.
    Behrendt T, Zein A, Min S (2012) Development of an energy consumption monitoring procedure for machine tools. CIRP Ann-Manuf Techn 61:43–46CrossRefGoogle Scholar
  47. 47.
    Jedrzejewski J, Kwasny W (2009) Development of high performance machine tools. Journal of Machine Engineering 9(2):5–31Google Scholar
  48. 48.
    Jedrzejewski J, Kwasny W (2011) Study on reducing energy consumption in manufacturing systems. Journal of Machine Engineering 11(3):7–20Google Scholar
  49. 49.
    Dietmair A, Verl A (2008) Energy consumption modeling and optimization for production machines. ICSET 2008, Proc. of the IEEE Conference for Sustainable Energy Technologies, SingapurGoogle Scholar
  50. 50.
    Denkena B, Guemmer O, Floeter F (2014) Evaluation of electromagnetic guides in machine tools. CIRP Ann-Manuf Techn 63:357–360CrossRefGoogle Scholar
  51. 51.
    Nessehi A (2011) Untangling complexities of machining energy consumption prediction for process planning. Presentation to STC O, CIRP January Meeting. (University of Bath)Google Scholar
  52. 52.
    TRAUB catalogue, CNC Dreh-Fräszentrum, TNX65/42, 04.10–808 WA Technische Änderungen vorbehalten, TRAUB Drehmaschinen GmbH & Co. KGGoogle Scholar
  53. 53.
    Newman ST, Nassehi R, Nimani-Asrai R, Dhokia V (2012) Energy efficient process planning for CNC machine. CIRP J Manuf Sci Technol 5:127–136CrossRefGoogle Scholar
  54. 54.
    Diaz N, Ninomiya K, Noble J, Dornfeld D (2012) Environmental impact characterization of milling and implications for potential energy savings in industry. 5th CIRP Conference on High Performance Cutting, Procedia CIRP 1:518–523Google Scholar

Copyright information

© Springer-Verlag London 2017

Authors and Affiliations

  1. 1.Wroclaw University of Science and TechnologyWroclawPoland

Personalised recommendations