Surface Roughness Prediction and Experimental Analysis in Grinding the Material of Zirconia Used by Dental Restoration

Abstract:

Surface roughness plays an important role in product quality, especially for that used in the domain of dental restoration. This paper presents a study on the surface roughness prediction and experimental analysis in grinding the material of zirconia used for dental restoration. For this purpose, the experiment using the orthogonal method is employed. The orthogonal array and range analysis were applied to study the effect of the process parameter had on the surface roughness. A high accuracy machining center, a new dental bur used only for dentistry, and a surface roughness measuring instrument which have excellent properties, are been employed to conducted the experiment. The experimental results demonstrated that the amount of feed, be the major parameter on surface roughness, followed by the width of cut. At the last part of this paper, a model for predict the surface roughness in grinding zirconia is developed based on the experiment by means of linear regression analysis, which can be used to estimate the values of surface roughness given certain grinding parameters.

• Periodical: Materials Science Forum (Volumes 800-801)
• Pages: 160-166
• DOI: https://doi.org/10.4028/www.scientific.net/MSF.800-801.160
• Online since: July 2014
• Authors: Xiao Bao Lei*, Feng Xie
• Keywords: Grinding, Orthogonal Design, Surface Roughness (SR), Zirconia

References

[1] Richard D. Stures, DDS, MS, The history and clinical application of a chairside CAD/CAM dental restoration system, Journal of Shanghai Journal of Stomatology, 2006, 15. 449-455.

[2] Ulrich Lohbauer, Frank A. Muller, Anselm Petschelt, Influence of surface roughness on mechanical strength of resin composite versus glass ceramic materials, Journal of MaterialsDental materials, 2008, 24. 250-256.

DOI: 10.1016/j.dental.2007.05.006

[3] Julie Z. Zhang , Joseph C. Chenb, E. Daniel Kirby, Surface roughness optimization in an end-milling operation using the Taguchi design method, Journal of Materials Processing Technology, 2006, 184. 233-239.

DOI: 10.1016/j.jmatprotec.2006.11.029

[4] Cevdet Gologlu, Nazim Sakarya, The effects of cutter path strategies on surface roughness of pocket milling of 1. 2738 steel based on Taguchi method, Journal of materials processing technology, 2008, 206. 7-15.

DOI: 10.1016/j.jmatprotec.2007.11.300

[5] Jae-Seob Kwak, Application of Taguchi and response surface methodologies for geometric error in surface grinding process, Journal of International Journal of Machine Tools & Manufacture, 2005, 45. 327-334.

DOI: 10.1016/j.ijmachtools.2004.08.007

[6] Lou MS, Chen JC, Li C, Surface roughness prediction technique for CNC end- milling, Journal of Ind Technol, 1998, 15. 1-6.

[7] Hasan O¨ktem, Tuncay Erzurumlu, Mustafa Co¨, A study of the Taguchi optimization method for surface roughness in finish milling of mold surfaces, Journal of Int J Adv Manuf Technol, 2006, 28. 694–700.

DOI: 10.1007/s00170-004-2435-6

[8] Yang JL, Chen JC, A systematic approach for identifying optimum surface roughness performance in end-milling operations, Journal of Ind Technol, 2001, 17: 2.

[9] Eyup Bagci, Seref Aykut, A study of Taguchi optimization method for identifying optimum surface roughness in CNC face milling of cobalt-based alloy (stellite 6), Journal of Int J Adv Manuf Technol, 2006, 29. 940-947.

DOI: 10.1007/s00170-005-2616-y

[10] C.X. (Jack) Feng, X. Wang. Development of empirical models for surface roughness prediction in finish turning, Journal of Advanced manufacturing technology, 2002, 20. 48-356.

DOI: 10.1007/s001700200162

[11] Ersan Aslan, Necip Camus_cu, Burak Birgoren, Design optimization of cutting parameters when turning hardened AISI 4140 steel (63 HRC) with Al2O3 + TiCN mixed ceramic tool, Journal of Materials & Design, 2007, 28. 1618-1622.

DOI: 10.1016/j.matdes.2006.02.006

[12] J.A. Ghani, I.A. Choudhury, H.H. Hassan, Application of Taguchi method in the optimization of end milling parameters, Journal of Material Processing Technology, 2004, 145. 84-92.

DOI: 10.1016/s0924-0136(03)00865-3

[13] Eleana Kontonasakia, Nikolaos Kantiranisb, Lambrini Papadopouloub et. al. Microstructural characterization and comparative evaluation of physical, mechanical and biological properties of three ceramics for metal–ceramic restorations, Journal of Dental materials, (2008).

[14] Isabelle Denrya, J. Robert Kelly, State of the art of zirconia for dental applications, Journal of Dental materials, 2008, 24. 299-307.

DOI: 10.1016/j.dental.2007.05.007

[15] J. Vivancos, C.J. Luis, L. Costa, J.A. Ort´ız, Optimal machining parameters selection in high speed milling of hardened steels for injection moulds, Journal of Material Processing Technology, 2004, 155-156. 1505-1512.

DOI: 10.1016/j.jmatprotec.2004.04.260

[16] Dae Kyun Baek , Tae Jo Kob, Hee Sool Kim, Optimization of feedrate in a face milling operation using a surface roughness model, Journal of International Journal of Machine Tools & Manufacture, Journal of International Journal of Machine Tools & Manufacture, 2001, 41. 451–462.

DOI: 10.1016/s0890-6955(00)00039-0

[17] Indrajit Mukherjee, Pradip Kumar Ray, A review of optimization techniques in metal cutting processes, Journal of Computers & Industrial Engineering, 2006, 50. 15–34.

DOI: 10.1016/j.cie.2005.10.001

[18] A. Noorul Haq & P, Marimuthu & R. Jeyapaul, Multi response optimization of machining parameters of drilling Al/SiC metal matrix composite using grey relational analysis in the Taguchi method, Journal of Adv Manuf Technol, 2008, 37. 250–255.

DOI: 10.1007/s00170-007-0981-4

[19] John L. Yang, Joseph C. Chen, A Systematic Approach for Identifying Optimum Surface Roughness Performance in End-Milling Operations, Journal of industrial technology, 2001, 17. 1-8.