Articles | Volume 10, issue 1
https://doi.org/10.5194/ms-10-243-2019
https://doi.org/10.5194/ms-10-243-2019
Research article
 | 
14 Jun 2019
Research article |  | 14 Jun 2019

Estimation of tool life and cutting burr in high speed milling of the compacted graphite iron by DE based adaptive neuro-fuzzy inference system

Longhua Xu, Chuanzhen Huang, Rui Su, Hongtao Zhu, Hanlian Liu, Yue Liu, Chengwu Li, and Jun Wang

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Subject: Machining and Manufacturing Processes | Techniques and Approaches: Reliability and Probability Analysis
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Cited articles

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Chuang, C., Singh, D., Kenesei, P., Jon, Almer, J., Hryn, J., and Huff, R.: Application of X-ray computed tomography for the characterization of graphite morphology in compact-graphite iron, Mater. Charact., 141, 442–449, https://doi.org/10.1016/j.matchar.2016.08.007, 2018. 
Dong, M. G. and Wang, N.: Adaptive network-based fuzzy inference system with leave-one-out cross-validation approach for prediction of surface roughness, Appl. Math. Model., 35, 1024–1035, https://doi.org/10.1016/j.apm.2010.07.048, 2011. 
Gabaldo, S., Diniz, A. E., Andrade, C. L. F., and Guesser, W. L.: Performance of carbide and ceramic tools in the milling of compact graphite iron-CGI, J. Braz. Soc. Mech. Sci., 32, 511–517, https://doi.org/10.1590/S1678-58782010000500011, 2010. 
Gill, S. S., Singh, R., Singh, J., and Singh, H.: Adaptive neuro-fuzzy inference system modeling of cryogenically treated AISI M2 HSS turning tool for estimation of flank wear, Expert Syst. Appl., 39, 4171–4180, https://doi.org/10.1016/j.eswa.2011.09.117, 2012. 
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Short summary
We solve the issues based on the ANFIS with DE. It indicates that once the cutting parameters are determined, we can give better predictions of tool life and heights of cutting burrs compared with other models. We redesigned the ANFIS model and this model was optimized with new learning algorithm called DE. This model can export two outputs at the same time. Based on the ANOVA, the results show that the most effect on the tool life and height of cutting burrs are cutting speed and feed rate.