Research on Wear and Life Prediction of Hobbing Cutter in Cryogenic Cutting with MQL

Abstract:

An ANN BP model is built to imitate the relative between output, the wear of hobbing cutter, and input, such as rotary speed of cutter, air flow, air jet speed, air temperature, situation of hobbing cutter and hardness of work piece. A program is compiled to extrapolate the total life of hobbing cutter based on the BP model. The conclusion can be obtained by the program about the total life of hobbing cutter in cryogenic cutting with MQL, as follow. When parameters vary in the given zone, air jet speed has the largest effect on the total life of hobbing cutter by 23.8%, and follows the air flow by 13.5%, and last is the air temperature by 4.4%.

• Periodical: Advanced Materials Research (Volumes 430-432)
• Pages: 842-848
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.430-432.842
• Online since: January 2012
• Authors: Xiao Hong Zhang, Chong Xia, Peng Chen, Guo Fu Yin
• Keywords: Artificial Neural Network (ANN), Cryogenic Cutting, Gear Hobbing, Near Dry Machining, Prediction Model, Wear

References

[1] C. Zhang, and M. Tong: Tool Technology, Vol. 38(2004)No. 3, pp.61-63(in Chinese).

[2] D. Chen, Y. Suzuki, and K. Sakai: China Mechanical Engineering, Vol. 11(2000)No. 9, pp.1035-1038(in Chinese).

[3] H. Yokota, and M. Wu: Aviation precision Manufacturing Technology, Vol. 40(2004)No. 1, pp.24-26(in Chinese).

[4] J. Ren: Manufacturing Technology and Machine Tool, (2001)No. 10, pp.30-32(in Chinese).

[5] G. Itoigawa, T.H.C. Childs, T. Nakamura, and et al : Wear, Vol. 260(2006)No. 3, pp.339-344.

[6] L. Han: Artificial Neural Network Theory, Design, and Application(Chemical Industry Press, China 2002).

[7] X. Zhang, and G. Yin: Coal Technology, Vol. 29(2010)No. 10, pp.23-25.