Research on Transient Temperature of Cutting Tool during High Speed Slot Milling of AISI H13

2014 ◽  
Vol 800-801 ◽  
pp. 715-719
Author(s):  
Fu Lin Jiang ◽  
Zhan Qiang Liu ◽  
Yi Wan ◽  
Han Zhang

Cutting tool temperature is the main factor that directly affects tool wear and tool life. In this paper we developed temperature model of tool insert during slot milling process, constructed by a combination of cutting time model and non-cutting model. A set of experiments are designed and carried out to obtain cutting induced temperatures at different cutting speeds during slot milling of AISI H13 steel. Experiments results indicate that tool insert temperature increases first and then decreases as the cutting speed grows, and a critical cutting speed for the tool insert temperature exists during slot milling of AISI H13 steel. Some possible reasons for the drop of tool insert temperature are proposed and discussed, and they are decreased heat flux into tool insert and increased heat convection coefficient.

2013 ◽  
Vol 770 ◽  
pp. 226-229
Author(s):  
Yong Hui Zhou ◽  
Jun Zhao ◽  
Xiao Bin Cui

In the present study, high-speed and ultra-high-speed face milling of AISI H13 steel (4647 HRC) was conducted in order to acquire a thorough understanding of the Al2O3-based micro-nanocomopsite ceramic cutting tool AWT10 wear mechanisms in high-speed hard milling. For different cutting speeds, the typical tool wear mechanisms is analyzed and compared. The analysis of the tool wear show that abrasive wear, adhesive wear, spalling and breakage are the primary wear mechanisms of AWT10 when cutting speed reaches 3000m/min. Micro-nanocomposite ceramic material AWT10 has favorable property of shock resistance. Improved cutting speed is in favor of cutting force reduction.


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 966-967 ◽  
pp. 152-167 ◽  
Author(s):  
Alejandro Pereira ◽  
Javier Martínez ◽  
Maria Teresa Prado ◽  
José A. Pérez ◽  
Thomas Mathia

The wear of TiCN coating carbide cutting tools (Sandvik® Grade 1010 and 4220) in different hard-milling machining conditions was monitored, analyzed, and discussed for AISI H13 steel. This material is commonly used in the forge industry in order to optimize the manufacturing process according to a qualimetry/cost compromise criterion. AISI H13 steel generally is used in modern production for high wear-resistant dies and molds. One of the most basic and primary geometric shapes in the manufacture of molds and die cavities is the geometry known as "inclined plane." Experimental investigations were carried out on a "mold model" design with the aim of analyzing and optimizing the principal manufacturing conditions. The tests are dependent on manufacturing factors, particularly their impactin a complex tribological process. Five clearly defined different surfaces of the hardened AISI H13 steel model mold, with appropriate geometries were studied; i) vertical downward; ii) curved downward; iii) horizontal; iv) curved upward; and v) vertical upward.The analysis of cutting tool wear during this process was based on computerized measurements of visually observable wear and power consumption. Morphological investigations of the surface topography for the cutting tool, as well as of the work-piece surfaces, were systematically carried out. Moreover, the interactions with simultaneously measured energy consumption during the process are also explicated in the present study and therefore tentative methods to optimize hard-milling machining are offered.


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.


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