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Analytical intelligence tools for multicriterial diagnostics of CNC machines

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Analytical Intelligence is a set of methods and tools for acquisition and transformation of raw data into meaningful and useful information. Multicriterial diagnostics is an approach to obtain a real status of machining process just in time and produce a big pile of raw data. The paper presents a scheme of utilisation of analytical intelligence tools in multicriterial diagnostic of CNC machine tools. It is an effort to obtain a complex perception about all influences represented with measured data on machine precision.
Twórcy
autor
  • Faculty of Mechanical Engineering, University of Žilina, Univerzitna 1, 010 26, Žilina, Slovakia
autor
  • Faculty of Mechanical Engineering, University of Žilina, Univerzitna 1, 010 26, Žilina, Slovakia
autor
  • Faculty of Mechanical Engineering, University of Žilina, Univerzitna 1, 010 26, Žilina, Slovakia
Bibliografia
  • 1. Witten I. Data mining. Morgan Kaufman Publishers, 2011.
  • 2. Cheng K. Machining dynamics. Springer, 2009.
  • 3. Shirinzadeh B. and Teoh P.L. Laser interferometrybased guidance methodology for high precision positioning of mechanisms and robots. Robotics and Computer-Integrated Manufacturing, 26, 2010, 74–82.
  • 4. Lovicz R. and Dalley R. Wear particle analysis - a predictive maintenance tool. The Predictive Maintenance Technology Conference, 2006.
  • 5. Castroa H.F.F. and Burdekinb M. Calibration system based on a laser interferometer for kinematic accuracy assessment on machine tools. Inter. Journal of Machine Tools and Manufacture, 46, 2006, 89–97.
  • 6. Jozwik J. and Kuric I. Bezkontaktowe systemy diagnostyczne obrabiarek sterowanych numerycznie CNC (in Polish). 14th Intern. Conference Automation in Production Planning and Manufacturing, Zilina, 2013.
  • 7. Majda P. The influence of geometric errors compensation of a CNC machine tool on the accuracy of movement with circular interpolation. Advances in Manufacturing Science and Technology, 36(2), 2012, 59–67.
  • 8. Stancekova D., Semcer J., Rudawska A. and Cep R. Identification of drilling of biocompatible materials based on titanium. Manufacturing Technology, 15(4), 2015, 699–704.
  • 9. Nakazawa H. and Ito K. Measurement system of contouring accuracy on NC machine tools. Bull. Japan Soc. Prec. Eng., 12(4), 1978, 189.
  • 10. Saga M. et al. Advanced methods in computational and experimental mechanics. Pearson Education Limited, London, United Kingdom, 2013, 57–112.
  • 11. Rudawska A., Cubonova N., Pomaranska K., Stancekova D. and Gola A. Technical and organizational improvements of packaging production process. Advances In Science And TechnologyResearch Journal, 10(30), 2016, 182–192.
  • 12. Medik S. Motion errors. Introduction to Precision Machine Design and Error Assessment. Edited by Samir Mekid, CRC Press, 2008, 9–73.
  • 13. Sapietova A., Saga M. and Novak P. Multi-software platform for solving of multibody systems synthesis. Communication - Scientific Letters of the University of Zilina, 14(3), 2012, 43–48.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d184c26c-cd67-488c-a048-ecae52f0b790
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