Research Article
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Year 2020, Volume: 24 Issue: 3, 446 - 454, 01.06.2020
https://doi.org/10.16984/saufenbilder.646183

Abstract

References

  • [1] E.D. Zanotto and J.C. Mauro, “The Glassy State of Matter: Its Definition and Ultimate Fate,” Journal of Non-Crystalline Solids, vol. 471, pp. 490-495, 2017.
  • [2] M. Sayuti, A.D. Sarhan Ahmed, and M. Hamdi, “Optimizing the Machining Parameters in Glass Grinding Operation on the CNC Milling Machine for Best Surface Roughness,” Advanced Materials Research, vol. 154-155, pp. 721-726, 2011.
  • [3] J. Cheng, C. Wang, X. Wen, and Y. Gong, “Modeling and Experimental Study on Micro-fracture Behavior and Restraining Technology in Micro-grinding of glass,” International Journal of Machine Tools and Manufacture, vol. 85, pp. 36-48, 2014.
  • [4] Ö. Küçükerman, “Glass Art and Examples from Traditional Turkish Glassware,” Turkey Isbank Culture Publications, vol. 271, Art Series: 39, 1985.
  • [5] E. Axinte, “Glasses as Engineering Materials: A review,” Materials and Design, vol. 32, pp. 1717-1732, 2011.
  • [6] B. Karasu, O. Bereket, E. Biryan, and D. Sanoğlu, “The Latest Developments in Glass Science and Technology,” El-Cezerî Journal of Science and Engineering, vol. 4, no 2, pp. 209-233, 2017.
  • [7] S. Öztürk, “Microstructural Analysis of Metal-bond Diamond Tools in Grinding of Flat Glass, Material,” Wissen Schaft Und Werkstoff Technik/Materials Science And Engineering Technology, vol. 45, no. 3, pp. 187-191, 2014.
  • [8] K. Habalı, H. Gökkaya, and H. Sert, “Experimental Investigation of the Effects of Cutting Tool Coating Materials on Surface Roughness in Machining of AISI 1040 Steel,” Journal of Polytechnic, vol. 9, no. 1, 35-38, 2006.
  • [9] S. Ozturk, “Grinding of flat glass with Feand Cu-based diamond tools.” Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 232, no. 9 pp. 1561- 1568 2018.
  • [10] M. F. Kahraman, and S. Öztürk, “Experimental study of newly structural design grinding wheel considering response surface optimization and Monte Carlo simulation.” Measurement, vol. 147, arcticle num. 106825, 2019.
  • [11] S. Öztürk, and M. F. Kahraman, “Modeling and optimization of machining parameters during grinding of flat glass using response surface methodology and probabilistic uncertainty analysis based on Monte Carlo simulation,” Measurement, vol. 145, pp. 274-291, 2019.
  • [12] M. F. Kahraman, H. Bilge, and S. Öztürk, “Uncertainty analysis of milling parameters using Monte Carlo simulation, the Taguchi optimization method and datadriven modeling,” Materials Testing, vol. 61, no. 5, pp. 477-483, 2019.
  • [13] S. Ozturk, “Application of the Taguchi method for surface roughness predictions in the turning process,” Materials Testing, vol. 58, no. 9, pp. 782-787, 2016.
  • [14] S. Ozturk, “Application of ANOVA and Taguchi Methods for Evaluation of the Surface Roughness of Stellite-6 Coating Material,” Materials Testing, vol. 56, no. 11-12, pp. 1015-1020, 2014.
  • [15] E. Kuram, and B. Ozcelik, “Multiobjective optimization using Taguchi based grey relational analysis for micromilling of Al 7075 material with ball nose end mill,” Measurement, vol. 46, no. 6, pp. 1849-1864, 2013.
  • [16] S. Ozturk, “Machinability of stellite-6 coatings with ceramic inserts and tungsten carbide tools,” Arabian Journal of Science and Engineering, vol. 39, no. 10, pp. 7375- 7383, 2014.
  • [17] M. F. Kahraman, H. Bilge, and S. Öztürk, “Uncertainty analysis of milling parameters using Monte Carlo simulation, the Taguchi optimization method and datadriven modeling,” Materials Testing, vol. 61, no. 5, pp. 477-483, 2019.
  • [18] Ş. Bayraktar, Y. Siyambaş, and Y. Turgut, “Drilling Process: A Review,” Sakarya University Journal of the Institute of Science and Technology, vol. 21, no. 2, pp. 120-130, 2017.
  • [19] V. Blank, M. Popov, G. Pivovarov, N. Lvova, and S. Terentev, “Mechanical Properties of Different Types of Diamond,” Diamond and Related Materials, vol. 8, pp. 1531-1535, 1999.
  • [20] R. Calvo, R. D'Amato, E. Gómez, and R. Domingo, “A Comparative Experimental Study of an Alternative CMM Error Model Under Least-squares and Minimum Zone Fittings for İndustrial Measuring,” Procedia Engineering, vol. 132, pp. 780- 787, 2015.
  • [21] D. Kubátová, M. Melichar, and J. Kutlwašer, “Evaluation of Repeatability and Reproducibility of CMM Equipment,” Procedia Manufacturing, vol. 13, pp. 558- 564, 2017.
  • [22] M. Kayri, “The Multiple Comparison (Post-Hoc) Techniques to Determine the Difference Between Groups in Researches,” Fırat University Journal of Social Science, vol. 19, no. 1, pp. 51-64 2009.
  • [23] Y. Dursun, and E. Kocagöz, “Structural Equation Modeling and Regression: A Comparative Analysis,” Erciyes University Faculty of Economics and Administrative Sciences Journal, vol. 35, pp. 1-17, 2010.
  • [24] T.F. Çavuş, and E. Yanıkoğlu, “Reliability Analysis of Complex Systems with Monte Carlo Method,” Sakarya University Journal of the Institute of Science and Technology, vol. 7, no. 3, pp. 99-102, 2003.
  • [25] A. Hançerlioğulları, “Monte Carlo Simulation Method and Mcnp Code System,” Kastamonu Education Journal, vol. 14, no. 2, pp. 545-556, 2006.
  • M. F., Kahraman, and [26] S Öztürk, “Uncertainty analysis of cutting parameters during grinding based on RSM optimization and Monte Carlo simulation,” Materials Testing, vol. 61 no. 12, pp. 1215-1219, 2019.
  • [27] F. Harmancı, “Optimization of Cutting Parameters During Drilling of Glass with Using Statistical Methods,” Msc Thesis, Abant Izzet Baysal University Graduate School of Natural and Applied Sciences, Bolu, 2018.

Optimization of Axial Misalignment due to Glass Drilling by Statistical Methods

Year 2020, Volume: 24 Issue: 3, 446 - 454, 01.06.2020
https://doi.org/10.16984/saufenbilder.646183

Abstract

Flat glass has a significant utilization in the domestic appliances sector. Drilling of glass is frequently used in the white goods sector. In this research, the glass drilling method is explained in detail, the determined axial misalignment values using the tool rotation speed and the feed rate were investigated. The drilling operation with its parameters must be optimized precisely, in order to have good control over the productivity, quality, and cost aspect of the application. Using the Ø18.3 mm drill tool, drilling process was performed with different rotation speeds (rpm) and feed rates (mm/sec). The impressions of drilling parameter on output variable were investigated using Analysis of Variance (ANOVA). Probabilistic uncertainty analysis based on Monte Carlo simulation was carried out. According to the results, the suggested model and optimization method could be used for estimating axial misalignment and this investigation is reliable and proper for figuring out the problems met in machining operations. Furthermore, Monte Carlo simulations were obtained quite effective for identification of the uncertainties in axial misalignment that could not be possible to be caught by deterministic ways. The optimum axial misalignment value was found to be 0.11823 mm.

References

  • [1] E.D. Zanotto and J.C. Mauro, “The Glassy State of Matter: Its Definition and Ultimate Fate,” Journal of Non-Crystalline Solids, vol. 471, pp. 490-495, 2017.
  • [2] M. Sayuti, A.D. Sarhan Ahmed, and M. Hamdi, “Optimizing the Machining Parameters in Glass Grinding Operation on the CNC Milling Machine for Best Surface Roughness,” Advanced Materials Research, vol. 154-155, pp. 721-726, 2011.
  • [3] J. Cheng, C. Wang, X. Wen, and Y. Gong, “Modeling and Experimental Study on Micro-fracture Behavior and Restraining Technology in Micro-grinding of glass,” International Journal of Machine Tools and Manufacture, vol. 85, pp. 36-48, 2014.
  • [4] Ö. Küçükerman, “Glass Art and Examples from Traditional Turkish Glassware,” Turkey Isbank Culture Publications, vol. 271, Art Series: 39, 1985.
  • [5] E. Axinte, “Glasses as Engineering Materials: A review,” Materials and Design, vol. 32, pp. 1717-1732, 2011.
  • [6] B. Karasu, O. Bereket, E. Biryan, and D. Sanoğlu, “The Latest Developments in Glass Science and Technology,” El-Cezerî Journal of Science and Engineering, vol. 4, no 2, pp. 209-233, 2017.
  • [7] S. Öztürk, “Microstructural Analysis of Metal-bond Diamond Tools in Grinding of Flat Glass, Material,” Wissen Schaft Und Werkstoff Technik/Materials Science And Engineering Technology, vol. 45, no. 3, pp. 187-191, 2014.
  • [8] K. Habalı, H. Gökkaya, and H. Sert, “Experimental Investigation of the Effects of Cutting Tool Coating Materials on Surface Roughness in Machining of AISI 1040 Steel,” Journal of Polytechnic, vol. 9, no. 1, 35-38, 2006.
  • [9] S. Ozturk, “Grinding of flat glass with Feand Cu-based diamond tools.” Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 232, no. 9 pp. 1561- 1568 2018.
  • [10] M. F. Kahraman, and S. Öztürk, “Experimental study of newly structural design grinding wheel considering response surface optimization and Monte Carlo simulation.” Measurement, vol. 147, arcticle num. 106825, 2019.
  • [11] S. Öztürk, and M. F. Kahraman, “Modeling and optimization of machining parameters during grinding of flat glass using response surface methodology and probabilistic uncertainty analysis based on Monte Carlo simulation,” Measurement, vol. 145, pp. 274-291, 2019.
  • [12] M. F. Kahraman, H. Bilge, and S. Öztürk, “Uncertainty analysis of milling parameters using Monte Carlo simulation, the Taguchi optimization method and datadriven modeling,” Materials Testing, vol. 61, no. 5, pp. 477-483, 2019.
  • [13] S. Ozturk, “Application of the Taguchi method for surface roughness predictions in the turning process,” Materials Testing, vol. 58, no. 9, pp. 782-787, 2016.
  • [14] S. Ozturk, “Application of ANOVA and Taguchi Methods for Evaluation of the Surface Roughness of Stellite-6 Coating Material,” Materials Testing, vol. 56, no. 11-12, pp. 1015-1020, 2014.
  • [15] E. Kuram, and B. Ozcelik, “Multiobjective optimization using Taguchi based grey relational analysis for micromilling of Al 7075 material with ball nose end mill,” Measurement, vol. 46, no. 6, pp. 1849-1864, 2013.
  • [16] S. Ozturk, “Machinability of stellite-6 coatings with ceramic inserts and tungsten carbide tools,” Arabian Journal of Science and Engineering, vol. 39, no. 10, pp. 7375- 7383, 2014.
  • [17] M. F. Kahraman, H. Bilge, and S. Öztürk, “Uncertainty analysis of milling parameters using Monte Carlo simulation, the Taguchi optimization method and datadriven modeling,” Materials Testing, vol. 61, no. 5, pp. 477-483, 2019.
  • [18] Ş. Bayraktar, Y. Siyambaş, and Y. Turgut, “Drilling Process: A Review,” Sakarya University Journal of the Institute of Science and Technology, vol. 21, no. 2, pp. 120-130, 2017.
  • [19] V. Blank, M. Popov, G. Pivovarov, N. Lvova, and S. Terentev, “Mechanical Properties of Different Types of Diamond,” Diamond and Related Materials, vol. 8, pp. 1531-1535, 1999.
  • [20] R. Calvo, R. D'Amato, E. Gómez, and R. Domingo, “A Comparative Experimental Study of an Alternative CMM Error Model Under Least-squares and Minimum Zone Fittings for İndustrial Measuring,” Procedia Engineering, vol. 132, pp. 780- 787, 2015.
  • [21] D. Kubátová, M. Melichar, and J. Kutlwašer, “Evaluation of Repeatability and Reproducibility of CMM Equipment,” Procedia Manufacturing, vol. 13, pp. 558- 564, 2017.
  • [22] M. Kayri, “The Multiple Comparison (Post-Hoc) Techniques to Determine the Difference Between Groups in Researches,” Fırat University Journal of Social Science, vol. 19, no. 1, pp. 51-64 2009.
  • [23] Y. Dursun, and E. Kocagöz, “Structural Equation Modeling and Regression: A Comparative Analysis,” Erciyes University Faculty of Economics and Administrative Sciences Journal, vol. 35, pp. 1-17, 2010.
  • [24] T.F. Çavuş, and E. Yanıkoğlu, “Reliability Analysis of Complex Systems with Monte Carlo Method,” Sakarya University Journal of the Institute of Science and Technology, vol. 7, no. 3, pp. 99-102, 2003.
  • [25] A. Hançerlioğulları, “Monte Carlo Simulation Method and Mcnp Code System,” Kastamonu Education Journal, vol. 14, no. 2, pp. 545-556, 2006.
  • M. F., Kahraman, and [26] S Öztürk, “Uncertainty analysis of cutting parameters during grinding based on RSM optimization and Monte Carlo simulation,” Materials Testing, vol. 61 no. 12, pp. 1215-1219, 2019.
  • [27] F. Harmancı, “Optimization of Cutting Parameters During Drilling of Glass with Using Statistical Methods,” Msc Thesis, Abant Izzet Baysal University Graduate School of Natural and Applied Sciences, Bolu, 2018.
There are 27 citations in total.

Details

Primary Language English
Subjects Mechanical Engineering
Journal Section Research Articles
Authors

Faruk Harmancı 0000-0002-2892-7436

Sabri Ozturk 0000-0002-1377-9338

Publication Date June 1, 2020
Submission Date November 13, 2019
Acceptance Date January 16, 2020
Published in Issue Year 2020 Volume: 24 Issue: 3

Cite

APA Harmancı, F., & Ozturk, S. (2020). Optimization of Axial Misalignment due to Glass Drilling by Statistical Methods. Sakarya University Journal of Science, 24(3), 446-454. https://doi.org/10.16984/saufenbilder.646183
AMA Harmancı F, Ozturk S. Optimization of Axial Misalignment due to Glass Drilling by Statistical Methods. SAUJS. June 2020;24(3):446-454. doi:10.16984/saufenbilder.646183
Chicago Harmancı, Faruk, and Sabri Ozturk. “Optimization of Axial Misalignment Due to Glass Drilling by Statistical Methods”. Sakarya University Journal of Science 24, no. 3 (June 2020): 446-54. https://doi.org/10.16984/saufenbilder.646183.
EndNote Harmancı F, Ozturk S (June 1, 2020) Optimization of Axial Misalignment due to Glass Drilling by Statistical Methods. Sakarya University Journal of Science 24 3 446–454.
IEEE F. Harmancı and S. Ozturk, “Optimization of Axial Misalignment due to Glass Drilling by Statistical Methods”, SAUJS, vol. 24, no. 3, pp. 446–454, 2020, doi: 10.16984/saufenbilder.646183.
ISNAD Harmancı, Faruk - Ozturk, Sabri. “Optimization of Axial Misalignment Due to Glass Drilling by Statistical Methods”. Sakarya University Journal of Science 24/3 (June 2020), 446-454. https://doi.org/10.16984/saufenbilder.646183.
JAMA Harmancı F, Ozturk S. Optimization of Axial Misalignment due to Glass Drilling by Statistical Methods. SAUJS. 2020;24:446–454.
MLA Harmancı, Faruk and Sabri Ozturk. “Optimization of Axial Misalignment Due to Glass Drilling by Statistical Methods”. Sakarya University Journal of Science, vol. 24, no. 3, 2020, pp. 446-54, doi:10.16984/saufenbilder.646183.
Vancouver Harmancı F, Ozturk S. Optimization of Axial Misalignment due to Glass Drilling by Statistical Methods. SAUJS. 2020;24(3):446-54.