Manufacturing Technology 2018, 18(3):363-368 | DOI: 10.21062/ujep/106.2018/a/1213-2489/MT/18/3/363

Mathematical Methods of Surface Roughness Evaluation of Areas with a Distinctive Inclination

Ondřej Bílek, Vladimír Pata, Milena Kubišová, Martin Řezníček
Faculty of Technology, Tomas Bata University in Zlín, Vavreckova 275, 76001 Zlin, Czech Republic

Surface roughness is one of the most significant evaluation factor in metal machining operations. Despite the small descriptiveness is usually quantified as the arithmetical mean roughness Ra especially in the automotive industry. In order to maintain the desired surface roughness, the appropriate setting of machining parameters is important to be set before the actual cutting process. The objective of this research is to analyse the effect of machining parameters on surface roughness of stainless steel X153CrMoV12-1 in CNC milling of slope surfaces with sintered carbide tool. The data were processed using multiparametric statistical methods to find optimal results. Linear regression models and probability dendrograms of similarities were determined for cutting conditions, cutting tools and slope of machined surfaces.

Keywords: CNC Milling, Cutting Tool, Multiparametric Statistical Methods, Surface Roughness, Surface Slope

Published: June 1, 2018  Show citation

ACS AIP APA ASA Harvard Chicago IEEE ISO690 MLA NLM Turabian Vancouver
Bílek O, Pata V, Kubišová M, Řezníček M. Mathematical Methods of Surface Roughness Evaluation of Areas with a Distinctive Inclination. Manufacturing Technology. 2018;18(3):363-368. doi: 10.21062/ujep/106.2018/a/1213-2489/MT/18/3/363.
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. CHAHAL, M., SINGH, V., GARG, R., KUMAR, S. (2012). Surface Roughness Optimization Techniques of CNC Milling. In: International Journal of Scientific and Engineering Research, Vol. 3, No., pp. 1-17. IJSER.
    2. KUNDRAK, J., FELHO, C. (2016). 3D Roughness Parameters of Surfaces Face Milled by Special Tools. In: Manufacturing Technology, Vol. 16, No. 3, pp. 532-538. Univerzita J. E. Purkyne, Czechia. Go to original source...
    3. ČEP, R., JANÁSEK, A., PETRŮ, J., SADÍLEK, M., MOHYLA, P., VALÍČEK, J., HARNIČÁROVÁ, M., CZÁN, A. (2013). Surface Roughness after Machining and Influence of Feed Rate on Process. In: Key Engineering Materials, Vol. 581, pp. 341-347. TTP. Switzerland. Go to original source...
    4. LEGUTKO, S., KROLCZYK, G., KROLCZYK, J. (2014). Quality evaluation of surface layer in highly accurate manufacturing. In: Manufacturing Technology. Vol. 14, No. 1, pp. 50-56. Univerzita J. E. Purkyne, Czechia. Go to original source...
    5. MIKÓ, B., BEŇO, J. (2013). Effect of the Working Diameter to the Surface Quality in Free-Form Surface Milling. In: Key Engineering Materials, Vol. 581, pp. 372-377. TTP. Switzerland.
    6. SADÍLEK, M., ČEP, R., BUDAK, I., SOKOVIĆ, M. (2011). Aspects of using tool axis inclination angle. In: Strojniski Vestnik/Journal of Mechanical Engineering, Vol. 57, No. 9, pp. 681-688. SV-JME. Slovenia. Go to original source...
    7. TWARDOWSKI, P., WOJCIECHOWSKI, S., WIECZOROWSKI, M., MATHIA, T. (2011). Surface roughness analysis of hardened steel after high-speed milling. In: Scanning, Vol. 33, No. 5, pp. 386-395. Hindawi. UK. Go to original source...
    8. WOJCIECHOWSKI, S., TWARDOWSKI, P., WIECZOROWSKI, M. (2014). Surface texture analysis after ball end milling with various surface inclination of hardened steel. In: Metrology and Measurement Systems, Vol. 21, No. 1, pp. 145-156. Polish academy of science. Poland. Go to original source...
    9. ZĘBALA, W. (2015) Tool deflection in the milling of titanium alloy: case study. In: Proceedings of SPIE - The International Society for Optical Engineering, p. 96624Q, SPIE, Poland. Go to original source...
    10. MALOTOVA, S., CEP, R., CEPOVA, L., PETRU, J., STANCEKOVA, D., KYNCL, L., HATALA, M. (2016). Roughness Evaluation of the Machined Surface at Interrupted Cutting Process. In: Manufacturing Technology, Vol. 16, No. 1, pp. 168-173. Univerzita J. E. Purkyne, Czechia. Go to original source...
    11. BENARDOS, P.G., VOSNIAKOS, G.C. (2003). Predicting surface roughness in machining: A review. In: International Journal of Machine Tools and Manufacture, Vol. 43, No. 8, pp. 833-844. Elsevier. Netherlands. Go to original source...
    12. BEŇO, J., MIKÓ, B., MAŇKOVÁ, I., VRABEL', M. (2013). Influence of Tool Path Orientation on the Surface Roughness when End Ball Milling Rounded Surfaces. In: Key Engineering Materials, Vol. 581, pp. 329-334. TTP. Switzerland. Go to original source...
    13. AFIFAH M. A., ERRY Y. T. A., DELVIS A., SITI N. M. B. (2014). Development of Surface Roughness prediction Model for High Speed End Milling of Hardened Tool Steel. In: Asian Journal of Scientific Research, Vol. 4, No. 3, pp. 255-263. Science Alert. UAE. Go to original source...
    14. AGARWAL, N. (2012). Surface Roughness Modeling with Machining Parameters (Speed, Feed & Depth of Cut) in CNC Milling. In: MIT International Journal of Mechanical Engineering, Vol. 2, No. 1, pp. 55-61. MIT Publication. India.
    15. FELHŐ, C., KARPUSCHEWSKI, B., KUNDRÁK, J. (2015). Surface Roughness Modelling in Face Milling. In: Procedia CIRP, Vol. 31, pp. 136-141. Elsevier. Netherlands. Go to original source...
    16. HOSSAIN, S.J., AHMAD, N. (2012). Artificial Intelligence Based Surface Roughness Prediction Modeling for Three Dimensional End Milling. In: International Journal of Advanced Science and Technology, Vol. 45, pp. 1-18. IJAST, Australia.
    17. HRICOVA, J., NAPRSTKOVA, N. (2015). Surface roughness optimization in milling aluminium alloy by using the Taguchi's design of experiment. In: Manufacturing Technology, Vol. 15, No. 4, pp. 541-546. Univerzita J. E. Purkyne, Czechia. Go to original source...
    18. QUINTANA, G., GARCIA-ROMEU, M.L., CIURANA, J. (2011). Surface roughness monitoring application based on artificial neural networks for ball-end milling operations. In: Journal of Intelligent Manufacturing, Vol. 22, No. 4, pp. 607-617. Springer. USA. Go to original source...
    19. SCHORNIK, V., ZETEK, M., BAKSA, T. (2017). Influence of Ground End Mill Surface Quality on Cutting Tool Life. In: Manufacturing Technology, Vol. 17, No. 6, pp. 952-957. Univerzita J. E. Purkyne, Czechia. Go to original source...
    20. SHAHRIAR JAHAN HOSSAIN, N.A. (2012). Surface Roughness Prediction Model for Ball End Milling Operation Using Artificial Intelligence. In: Management Science and Engineering, Vol. 6, No. 2, pp. 41-54. CRDCSC. Canada.
    21. SURESH KUMAR REDDY, N., VENKATESWARA RAO, P. (2005). A Genetic Algorithmic Approach for Optimization of Surface Roughness Prediction Model in Dry Milling. In: Machining Science and Technology, Vol. 9, No. 1, pp. 63-84. Taylor & Francis Online. UK. Go to original source...
    22. WIECZOROWSKI, M., CELLARY, A., MAJCHROWSKI, R. (2010). The analysis of credibility and reproducibility of surface roughness measurement results. In: Wear, Vol. 269, No. 5-6, pp. 480-484. Elsevier. Netherlands. Go to original source...
    23. ZAIN, A.M., HARON, H., SHARIF, S. (2010). Prediction of surface roughness in the end milling machining using Artificial Neural Network. In: Expert Systems with Applications, Vol. 37, No. 2, pp. 1755-1768. Elsevier. Netherlands. Go to original source...
    24. MAHESH, G., MUTHU, S., DEVADASAN, S.R. (2012). Experimentation and prediction of surface roughness of the machining parameter with reference to the rake angle in end mill. In: International Review of Mechanical Engineering, Vol. 6, No. 7, pp. 1418-1428. Indian Institute of Technology Kanpur. India.
    25. MATRAS, A. (2015). The influence of tool inclination angle on the free form surface roughness after hard milling. In: SPIE 9662, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2015, p. 96624N, SPIE, Poland. Go to original source...
    26. VASILKO, K., MURČINKOVÁ, Z. (2017). The proposal how to make the basic machining technologies - Turning, milling, planing - more productive. In: Manufacturing Technology, Vol. 17, No. 2, pp. 261-267. Univerzita J. E. Purkyne, Czechia. Go to original source...

    This is an open access article distributed under the terms of the Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0), which permits non-comercial use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return to the content