Modeling and Simulation of 3D Surface Finish of Grinding

Abstract:

The main body of grinding knowledge comes from the experiments done by independent investigators. If such experimental results are not made both human- and machine-comprehensible from the very beginning, then it would be difficult to reuse the results using a computerized network or any other means. In this respect, intelligent systems are needed to create human- and machine-comprehensible models of important results like 3D surface finish, cutting force, tool wear, etc. From this perspective, this paper describes a method for modeling and simulation of 3D surface finish of grinding. A human-friendly simulation tool is developed to implement the method. The simulation result is compared with the real 3D surface finish and a close correlation is found. The presented model can be integrated with the collaborative machining networks for better utilization of grinding resources using computers (e.g., condition monitoring, process planning, automation) and even using humans (e.g., effective exchange of information among peers in the research community and in the industry).

References

[1] K. Syoji (Ed. ). Ultra-Precision Machining and Non-Spherical Surface Machining, NTS Corporation, Tokyo, (2004). (In Japanese).

[2] J. Tamaki, T. Kuriyagawa and Y. M. Baron (Eds. ). Advances in Abrasive Technology VIII, Trans Tech Publications Ltd, Switzerland, (2005).

[3] J. Tamaki, A. Kubo and J. Yan. Experimental Analysis of Elastic and Plastic Behavior in Ductile-Regime Machining of Glass Quartz Utilizing a Diamond Tool, Key Engineering Materials, Vol. 389-390 (2009), pp.30-35.

DOI: 10.4028/www.scientific.net/kem.389-390.30

[4] M. Higuchi, T. Tomiyama, N. Matsumori and H. Ogura. Geometric Modeling of Vitrified Superabrasive Stone Surface, Transaction of the Japan Society of Mechanical Engineers, Series C, Vol. 73(732), (2007), pp.207-212. (In Japanese).

DOI: 10.1299/kikaic.73.2381

[5] T. Yamaguchi, M. Higuchi, S. Shimada, N. Matsumori, I. Yoshizawa and H. Ogura. Fractal modeling method for 3D structure of vitrified-bonded wheel, Precision Engineering, Vol. 31(1), (2007), pp.40-46.

DOI: 10.1016/j.precisioneng.2006.02.003

[6] A.M.M.S. Ullah and K.H. Harib. A Stochastic Model for Simulating Cutting Forces, Proceedings of the Sixth CIRP International Conference on Intelligent Computation in Manufacturing Engineering, 23-25 July, (2008), Naples, Italy, pp.343-348.

[7] A.M.M.S. Ullah and K.H. Harib. Simulation of cutting force using nonstationary Gaussian process, Journal of Intelligent Manufacturing, DOI: 10. 1007/s10845-009-0245-2, in press.

[8] J. D. Cogdell. A convolved multi-Gaussian probability distribution for surface topography applications, Precision Engineering, Vol. 32(1), (2008), pp.34-46.

DOI: 10.1016/j.precisioneng.2007.04.004

[9] K.K. Manesh, B. Ramamoorthy and M. Singaperumal. Equation Numerical generation of anisotropic 3D non-Gaussian engineering surfaces with specified 3D surface roughness parameters, Wear, DOI: 10. 1016/j. wear. 2010. 02. 005, in press.

DOI: 10.1016/j.wear.2010.02.005

[10] A.M.M.S. Ullah, K.H., Harib and S. Aldajah. On the Roughness Profile Modeling using Q-Sequence, Proceeding of the Ninth CIRP Workshop on Modeling of Machining Operations, 11-12, May (2006), Bled, Slovenia pp.431-437.

[11] A.M.M.S. Ullah and K.H. Harib. Knowledge extraction from time series and its application to surface roughness simulation, Information Knowledge Systems Management, 5, (2006), pp.117-134.

[12] P. Butala and A. Sluga. Autonomous Work Systems in Manufacturing Networks, CIRP Annals-Manufacturing Technology, Vol. 55(1) (2006), pp.521-524.

DOI: 10.1016/s0007-8506(07)60473-9

[13] T. Matsuda, F. Tanaka, M. Onosato and H. Date. Development of a Digital Machining Information Model to Support a Real-Virtual Machining System, Journal of Advanced Mechanical Design, Systems, and Manufacturing, Vol. 2(4) (2008), pp.597-608.

DOI: 10.1299/jamdsm.2.597

[14] S.H. Bui and T.V. Vorburger. Surface metrology algorithm testing system, Precision Engineering, Vol. 31(3) (2007), pp.218-225.

DOI: 10.1016/j.precisioneng.2007.01.002