Analysis of transient average tool temperatures in face milling

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Abstract

The increased tool temperature has great effect on tool life, machining efficiency and even the quality of the products in face milling. The objectives of this study are to predict the transient average tool temperatures under different cutting conditions with fixed cutting velocity and metal removal rate, and investigate the evolution of tool temperature with cutting condition. Finite element simulations of orthogonal metal cutting are performed so as to predetermine the evolution process of the heat source on the tool rake face. An analytical model is proposed to calculate and analyze the tool temperatures under nine different cutting conditions. The results reveal that the minimum transient average tool temperature can be acquired by adopting suitable cutting condition. The proposed theoretical method provides insight into the complex evolution of tool temperatures. It also provides information for the search for the optimum cutting condition under which the longest tool life can be obtained.

Introduction

In the cutting process, conversion of the mechanical work occurs in the plastic deformation in chip formation and friction between the tool and workpiece, resulting in the generation of heat. As part of the heat conducts into the cutting tool, high tool temperatures appear near the cutting edge. In the interrupted cutting process, the cutting tools are subjected to cyclical heating and cooling as they pass in and out of the workpiece, which is hardly encountered in the continuous cutting process. As a typical interrupted cutting process, face milling is widely used to generate smooth surfaces with high geometric accuracy. In the milling process, the uncut chip thickness and tool–chip contact area on the rake face vary with the tool rotation. The intensity and area of the heat source change cyclically, leading to the complex evolution of the tool temperatures. With the increment of temperature, the cutting tools may become softer and wear more rapidly, resulting in the shorter tool lives, lower machining efficiency, and even lower dimensional accuracy of the products. It is essential to predict and analyze the tool temperatures in face milling process.

Many researches on temperatures in interrupted cutting especially milling have been conducted experimentally and theoretically. In the 1920s, the famous Salomon curve was proposed by Salomon [1] via high-speed milling tests. The curve suggests that the cutting temperature can be reduced as the cutting speed increases. Schmidt [2] investigated the maximum temperature in and near the surface of the workpiece in the milling process using thermocouple embedded in the workpiece. Ueda et al. [3] investigated experimentally the temperature of the flank face of a cutting tool in high speed milling by means of a two-color pyrometer with an optical fiber. Sato et al. [4] developed an infrared radiation pyrometer with two optical fibers connected by a fiber coupler which was applied to the measurement of tool–chip interface temperature in end milling with a binderless CBN tool. McFeron and Chao [5] derived an approximate, iterative procedure for the calculation of the average, transient tool–chip interface temperature in plain peripheral milling. And the average tool–chip interface temperatures were measured by means of a tool-work thermocoupling technique. Palmai [6] reported with no direct experimental support that, in contrast to continuous cutting, as the cutting speed increases the temperatures in interrupted cutting decrease. Stephenson and Ali [7] investigated the tool temperatures in interrupted cutting theoretically and experimentally. Theoretically, the general nature of tool temperature distribution was analyzed by means of the temperature in a semi-infinite rectangular corner heated by a time-varying heat flux with various spatial distributions. The results of this analysis were compared with the cutting temperatures measured using infrared and tool–chip thermocouple technique. Based on the finite difference method, a numerical model was proposed by Lazoglu and Altintas [8] to predict tool and chip temperature fields in continuous machining and time-varying milling process. As reported in the literature, the simulated results are in satisfactory agreement with the measured temperature.

Previous studies on milling temperatures presented much valuable information. But little research was conducted to investigate the tool temperatures in face milling theoretically. As has been discussed, because of the varying intensity and area of the heat source, the evolution process of the tool temperatures is complex in face milling. Moreover, it is difficult to identify quantitatively how the intensity and area of the heat source develop with the tool rotation. Probably for these reasons, few studies concentrated on the theoretical analysis of tool temperatures in face milling.

In the present study, a theoretical method is proposed to investigate the transient average tool temperatures in face milling of AISI H13 tool steel with uncoated carbide tool. Finite element simulations of metal cutting are performed. The simulated results are analyzed and calculated so as to fit the evolution process of the intensity and area of the heat source. An analytical model for the transient average tool temperatures is established with the variation of heat source considered. As concluded by Longbottom and Lanham [9] in the review of research related to Salomon's hypothesis on cutting speeds and temperatures, the Salomon curve might not be valid for the tool–work interface temperature. In other words, according to most of the existing studies, the increased cutting speed might not lead to reduction in tool temperature. Therefore, for the purpose of reducing tool temperature, investigation on acquiring the minimum transient average tool temperature in face milling with cutting speed and metal removal rate fixed is conducted based on the established model.

Section snippets

Evolution of the heat source

The set-up of face milling under consideration is shown in Fig. 1. The diameter of the face milling cutter is 120 mm. Four inserts are clamped peripherally and uniformly. As the axial depth of cut ap is mainly determined by technological requirements, it remains fixed at 1 mm. The cutting velocity v is kept at an invariable value 600 m/min. The maximum value of radial depth of cut ae and feed rate f are 60 mm and 0.96 mm/r, respectively. The metal removal rate is fixed.

The evolution of intensity and

Analytical model for the transient tool temperature

As shown in Fig. 1, the insert is modeled as a semi-infinite rectangular corner heated by a heat source of which the intensity and area vary with tool rotation. As stated by Stephenson [7], the assumption of the tool being treated as a semi-infinite body would probably lead to an underestimation of temperatures in the long term, but it would have relatively little effect on the oscillating component of the temperature field. In the present study, heat radiation and the effects of temperature on

Transient average tool temperature

By means of programming calculation, the transient average tool temperature TAVE(Lx, Lymax, z, t) under different cutting conditions can be obtained. As shown in Fig. 4, the transient average tool temperatures under nine different cutting conditions with metal removal rated fixed are investigated. As shown in Fig. 4, the width of the workpiece is 60 mm. For conditions 1 and 2, the radial depth of cut is the same, namely 20 mm. The radial depth of cut is 40 mm for conditions 3 and 4. As for

Conclusions

The evolution of intensity and area of the heat source related to the uncoated carbide insert in face milling AISI H13 steel are predetermined using the results of finite element simulations of orthogonal metal cutting. An analytical model for the transient average tool temperatures in face milling is established.

Based on the theoretical method proposed in this paper, the transient average tool temperatures for nine different cutting conditions with fixed cutting velocity and metal removal rate

Acknowledgments

This research is supported by the National Basic Research Program of China (2009CB724402) and the Graduate Independent Innovation Foundation of Shandong University, GIIFSDU (yzc10119).

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Communicated by P. Cheng and W.Q. Tao.

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