scholarly journals Experimental Analysis and Theoretical Modelling of Cutting Parameters in the Drilling of AISI H13 Steel with Coated and Uncoated Drills

2018 ◽  
Vol 42 (2) ◽  
pp. 83-96 ◽  
Author(s):  
İsmail Tekaüt ◽  
Halil Demir ◽  
Ulvi Şeker
2015 ◽  
Vol 667 ◽  
pp. 35-40
Author(s):  
Xiao Bin Cui ◽  
Jing Xia Guo ◽  
Xiao Yang Wang

For the purpose of acquiring thorough understanding of the characteristics of cutting force in high and ultra-high-speed face milling of hardened steel, experimental investigations on face milling of AISI H13 steel (46-47 HRC) are conducted in the present study. The cutting speed of 1400 m/min, at which relatively low cutting force and relatively low surface roughness can be obtained at the same time, is considered as a critical value for both mechanical load and surface finish. The Taguchi method is applied to investigate the effects of cutting parameters on cutting force in different speed ranges (below and above 1400 m/min). In different speed ranges, the contribution order of the cutting parameters for the resultant cutting force is the same, namely axial depth of cut, cutting speed and feed per tooth. However, the contributions of cutting speed and feed per tooth increase substantially as the cutting speed surpasses 1400 m/min. Within the range of cutting parameters used in the present study, the optimum cutting conditions for the cutting force are cutting speed 200 m/min, feed per tooth 0.02 mm/tooth and axial depth of cut 0.1 mm.


2014 ◽  
Vol 800-801 ◽  
pp. 590-595
Author(s):  
Qing Zhang ◽  
Song Zhang ◽  
Jia Man ◽  
Bin Zhao

Surface roughness has a significant effect on the performance of machined components. In the present study, a total of 49 end milling experiments on AISI H13 steel are conducted. Based on the experimental results, the signal-to-noise (S/N) ratio is employed to study the effects of cutting parameters (axial depth of cut, cutting speed, feed per tooth and radial depth of cut) on surface roughness. An ANN predicting model for surface roughness versus cutting parameters is developed based on the experimental results. The testing results show that the proposed model can be used as a satisfactory prediction for surface roughness.


2020 ◽  
Vol 831 ◽  
pp. 35-39 ◽  
Author(s):  
The Vinh Do ◽  
Quoc Manh Nguyen ◽  
Minh Tan Pham

In metal cutting, surface roughness plays an important role in assessing the quality of processed products. The roughness depends greatly on the selection of machining parameters such as cooling conditions and cutting parameters. For this purpose, cooling conditions including dry, MQL, and Silica-based nanofluid MQL as well as cutting parameters including cutting speed, depth-of-cut and feed-rate were investigated to determine their influence on machining roughness during hard milling of AISI H13 steel. The DOE method developed by G. Taguchi was used to design the experiments. An analysis of the signal-to-noise response and ANOVA were carried to obtain the optimal values of cutting parameters for minimizing surface roughness. The results of the present study show that Silica-based nanofluid MQL, minimum feed-rate, minimum depth-of-cut, and maximum cutting speed is an optimal cutting condition for reducing machining roughness.


2015 ◽  
Vol 270 ◽  
pp. 266-271 ◽  
Author(s):  
S.D. Jacobsen ◽  
R. Hinrichs ◽  
I.J.R. Baumvol ◽  
G. Castellano ◽  
M.A.Z. Vasconcellos

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