CIRP Annals - Manufacturing Technology 57 (2008) 65–68
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The effect of machinability on thermal fields in orthogonal cutting of AISI 4140 steel P.J. Arrazola (3)a, I. Arriola a,b, M.A. Davies (2)c,*, A.L. Cooke c, B.S. Dutterer c a
Manufacturing Department, Faculty of Engineering - Mondragon University, Mondrago´n, Spain marGUNE Center, Elgoibar, Spain c Center for Precision Metrology, Department of Mechanical Engineering and Engineering Science - University of North Carolina at Charlotte, Charlotte, NC, USA b
A R T I C L E I N F O
A B S T R A C T
Keywords: Machinability Temperature measurement Tool wear
The micro-scale temperature fields in the cutting of two AISI 4140 steels with different machinability ratings were measured. A custom infrared microscope was constructed; each pixel was calibrated separately to reduce measurement uncertainty. Orthogonal cutting experiments were performed on a high speed machining center with surface speeds up to 500 m min1 and uncut chip thicknesses ranging from 0.1 mm to 0.3 mm. The results indicate that in certain critical regions of the thermal field, improved machinability correlates with significant reductions in temperature that exceed measurement uncertainties. Such micro-scale temperature measurements will help to design materials with further improved machinability. ß 2008 CIRP.
1. Introduction Modern industry is making increasingly severe demands on the technological and operating characteristics of many materials including steels. Unfortunately, better performance often leads to more difficulty in machining [1]. A scientific methodology based on measurements of cutting process behaviour is needed to design materials that meet performance criteria but do not cause excessive tool wear. Temperature causes exponential activation of wear mechanisms (e.g. chemical reactions and diffusion) and is thus a key variable that must be considered in intelligent material design [2]. Industrial demands for steels drive both material and manufacturing improvements: (1) improvement of steel properties to make stronger, longer lived, and lighter weight components while (2) expanding the use of automated production equipment, increasing productivity and reducing demands on the environment. Progress toward such goals can come in many forms. For example, the development of new tool types, shapes and coatings [3] and minimum quantity lubrication (MQL) are very active areas of work [4]. However, material microstructure and chemistry can also be optimized to reduce tool wear and the need for coolant [5]. An overarching conclusion of researchers seeking to develop materials for improved machinability is that an accurate control of the inclusions and material flow is needed to improve tool life [6]. This research emphasizes treating the tool, base material and the inclusions as a three body system similar to the approach used in the polishing literature where the micro-scale abrasive particles are treated as a third body [7]. The wear can also be significantly affected by stabilizing portions of the material flow, such as occurs
* Corresponding author. 0007-8506/$ – see front matter ß 2008 CIRP. doi:10.1016/j.cirp.2008.03.139
in the formation (mostly inadvertent) of a stable built up edge (BUE) on the tool during machining. Micro- and macro-scale flow patterns as well as the chemical, abrasive, and diffusive processes are important in predicting wear. Many previous studies have addressed tool wear in these terms beginning with Kramer and Von Turkovich [8]. The most recent studies show that the formation of a stable macro-layer (BUE) can: (1) change the cutting edge geometry and subsequently the cutting forces [9]; (2) act as a thermal barrier [10]; (3) act as a protective layer that reduces abrasive, adhesive and diffusive wear mechanisms [11,12]; (4) change the friction coefficient through a lubricant-like effect [13]. The commonality between these studies is wear reduction by the design of materials with a stable layer at the tool–chip interface. In the current study, we use micro-scale thermal imaging [14,15] to identify the effects of changing the machinability rating of the material on the temperature for two grades of AISI 4140, a common steel used in many industries. Of practical importance is the method for quantifying the effect of improved machinability on temperature and related to tool wear mechanisms. The method is intended as a tool for designing materials that lead to less tool wear and thus reduced cost and improved productivity. 2. Experimental design This study focuses on AISI 4140 Standard and AISI 4140 MECAMAX1 Plus. The mechanical properties, hardness (290 3HB), and microstructure (tempered martensite) of the steels are very similar. However, AISI 4140 Plus has globular MnS inclusions and calcium treatment that improves machinability (see Table 1, values in weight percentage). The improvement is believed to result from non-metallic inclusions (MnS) and specific inclusions of CaOMnO-SiO2-Al2O3 system that seem to: (1) reduce abrasion at the tool– work interface, (2) reduce friction coefficient and (3) cause the
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Table 1 Compositions of AISI 4140 steels (iron balance) Constituent
AISI 4140 Standard
AISI4140 MECAMAX1 Plus
Carbon (%) Manganese (%) Silicon (%) Phosphorus (%) Sulfur (%) Calcium (%)
0.40 0.81 0.33 0.011 0.026 0.0004
0.40 0.86 0.23 0.011 0.073 0.0013
appearance of non-metallic protective layers on the tool known as selective built up layers (B.U.L.) [16]. It is suspected, but has not been shown previously, that the improved machinability is also directly connected with a reduction in the local tool–chip temperature. To investigate the relationship between temperature and machinability, a high-bandwidth infrared microscopic imaging system was constructed. The system utilizes a 320 by 256, liquidnitrogen-cooled, indium-antimonide detector array with a spatial resolution of less than 10 mm, had a bandwidth of 488 Hz and accepted mid-range radiation from 3 mm to 5 mm in wavelength. The system was mounted to a high-speed machining center as shown in Fig. 1. 2.1. Machining arrangement To minimize variations in material properties and residual stresses from drawing, the tubular samples were machined from a solid bar: each measured 45-mm in length, 25-mm in outer diameter, and 1-mm in thickness with a 30-mm long solid base for clamping. Tools were ground so that image plane was perpendicular to the optical axis of the microscope. Focus and emissivity variations were minimized by re-machining the outer diameter in the CAT-40 mounting fixture used for the experiments and then polishing the workpiece surface in situ for uniformity to a finish of approximately 250 nm, making them essentially specular in the range of the accepted radiation (3–5 mm). The microscope, an aluminum monolithic tool post, a 12.5 mm square tool holder, and a zero-rake, five-degree clearance, tungsten carbide insert were attached to a 37 mm thick aluminum plate on the machining center (Fig. 1). An orthogonal cut was produced by removing the end of the tube. The tool and chip were measured in the plane perpendicular to the cutting direction. 2.2. Calibration The microscope was calibrated (Fig. 2) by direct heating of the both the carbide tool and the AISI 4140 steels [15]. To reduce uncertainties, direct emissivity measurements of both materials
Fig. 2. Calibration arrangement.
were also made and utilized to correct for bias errors as described below. To obtain a relation between temperature and camera signal for the steels, a 12.7 mm diameter cylindrical electric heater was interference-fit into the tube to produce a uniform thermal contact (verified with a thermocouple). To obtain a similar relation for the tool material, the insert was modified to incorporate an interference-fit with a 6.35 mm diameter cylindrical electric heater and the entire assembly was enclosed in a ceramic housing to maintain uniformity. In each case, the microscope was focused on the artefact surface. The temperature was varied from 50 8C to 750 8C in intervals of 50 8C and allowed to stabilize for several minutes. The temperature (T) was measured with a type-K thermocouple and the camera signal was recorded (S). Signal and temperature data were fit to an interpolating function, based on the Sakuma equation [16], T ¼ a1 lnðS þ a2 Þ þ a3
(1)
using a least squares method, where a1, a2 and a3 are the fit parameters. Thermal imagers have non-uniform spatial responsivity as well as the non-linear responsivity of the individual detecting elements. Therefore, one unique approach taken here to minimize errors was to disallow the use for a non-uniformity correction (so called NUC) in the camera software and calibrate each pixel as an independent measuring device. Thus, the interpolating functions reduce uncertainty in data processing by acting both to calibrate each independent pixel signal in terms of radiance temperature, and also to remove the image nonuniformity resulting from detector variation. 2.3. Procedure Orthogonal cutting experiments were performed for a range of cutting parameters while varying the cutting speeds (vc ) (up to 500 m min1) and the uncut chip thickness ( f) ranged from 0.1 mm to 0.3 mm). At each set of cutting conditions, a thermal movie of approximately 300–400 frames of data was obtained. This data was converted to temperature and showed an approximately exponential approach to steady state: 50 sequential frames of steady state data were taken for each set of cutting conditions. The cutting edge was also replaced and relocated using a backlighting technique following each experiment to avoid problems with wear. 2.4. Experimental data treatment
Fig. 1. Experimental arrangement.
The largest source of uncertainty in these experiments is the emissivity of the materials and its variation with wavelength/ temperature, finish, oxidation, camera focus changes, etc. [15,17– 19]. Fig. 3 shows our radiometric measurements of the workpiece
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Table 2 Experimental temperature measurement uncertainty
Fig. 3. Normal spectral emissivity for different levels of oxidation, finish, temperature and wavelength.
emissivity done in vacuum using a Fourier transform infrared spectrometer [17]. The emissivity varies for different surface conditions and wavelength. The shaded area in Fig. 3 represents the band of radiation accepted by the measurement system. The emissivity varies from 0.1 to 0.9 as depending on surface condition and oxidation alone. Thus, although the thermal microscope is theoretically calibrated against the workpiece and tool, changes during the measurement or the calibration can lead to significant uncertainty in the emissivity and therefore temperature. To handle this uncertainty, we make two assumptions: (1) the workpiece material is in the heavily oxidized state during the calibrations; and (2) the time spent in the measurement window (less than 1 ms in all cases), is not sufficient for a heavy (several micrometer) oxide layer to form. The time for oxides to form as seen in the measurement of emissivity changes in our experiments indicate that the associated changes in emissivity occur over times of several seconds. Calibrations of the workpiece under heavily oxidized conditions have an approximately constant emissivity of 0.875–0.9 while the measurements are assumed to occur in the polished state. Because the oxidized surface used for calibration also has a wavelength independent emissivity (so-called grey body) in the range of interest (Fig. 3), Planck’s law [19] can be used to obtain an equivalent blackbody calibration curve and then temperatures can
Source of uncertainty
Workpiece
Tool
Calibration Experimental fluctuations Emissivity variations Combined uncertainty
10 8C 25 8C 35 8C 44 8C
10 8C 25 8C 10 8C 28 8C
be calculated, using a wavelength dependent emissivity for the (pre-polished) material being machined (note emissivity variation with wavelength for the polished 4140 samples); the tool was assumed to be oxidized in cutting and during calibration. This was done for all 50 frames to produce a mean thermal profile for each case. The remaining source of emissivity uncertainty is the change due to plastic deformation and its effect on surface finish as discussed below. Comparison of temperatures is often based upon the maximum temperatures measured on the tool rake face [15]. Here this can be problematic because small fluctuation in the tool–chip interface during cutting can cause a high uncertainty in the local emissivity (tool and workpiece emissivity may differ by up to 50%). Thus, here more stable thermal profiles 15 mm inside the tool and inside the chip as shown in Fig. 4 are used. The experimental measurement uncertainties are summarized in Table 1 for the worst conditions in the tool and chip. The largest source of uncertainty remains the possible fluctuations in emissivity during plastic deformation in the chip. Davies et al. [15] quote emissivity measurements done on plastically deformed samples from Hopkinson bar tests bar that place this uncertainty at 10 percent. In the tool the uncertainty is 3 percent and is dominated by the uncertainty of the emissivity measurement system. Table 2 details the uncertainties for the tool and workpiece for the worst case conditions (i.e. uncertainty is a function of many variables and is in all cases less than the quoted values). 3. Results Representative thermal fields and maps of the uncertainties in the mean temperature obtained from the experimental fluctuations are shown in Figs. 5 and 6. Note that the experimental fluctuations also appear to be highest at the tool–chip interface and
Fig. 5. Thermal maps. 400 m min1 and 0.2 mm. 4140 Standard temperature (left) and uncertainty (right).
Fig. 4. Temperature measurements just above and below the tool–chip interface. 100 m min1 and 0.2 mm AISI 4140 Plus.
Fig. 6. Thermal maps. 400 m min1 and 0.2 mm. 4140 Plus temperature (left) and uncertainty (right).
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developed here is a practical tool for the scientific design of more machinable materials and reduce the need for tedious, timeconsuming and expensive than machinability tests (ISO 3685) [21]. Acknowledgments To the Basque and Spanish Governments for the financial support given to the projects: INCLUMEC (UE200703) and MAQUIMODEL (DPI2006-15502-C02-01). Authors also thank the company Sidenor (Spain) for the technical and material support given to this work. References
Fig. 7. Experimentally measured maximum tool temperature (solid line) and maximum chip temperature (dotted line) versus cutting speed and uncut chip thickness. The red is AISI 4140 Standard and the green is AISI 4140 Plus.
that (noting the change in scale) the temperatures in cutting the standard grade are significantly higher over the whole field in the AISI 4140 Standard. Fig. 7 makes this more quantitative showing maximum temperature in the chip and tool for various parameters. From 100 m min1 to 300 m min1 the difference remains approximately in 40 8C for both the chip and tool, but jumps to 95 8C (chip side) and 75 8C (tool side) at 400 m min1. The same types of trends are observed versus uncut chip thickness with differences more pronounced in the tool and becoming as great at 50 8C. 4. Conclusions It has been observed that across a range of parameters that enhanced machinability in AISI 4140 Plus does lead to reduced temperatures in the tool–chip region. The greatest differences were observed at the higher cutting speed of 400 m min1, which is consistent with the precipitation and consequent deposition of the MnS layer on the rake face [20]. This also matches with the V15 [21] of the AISI 4140 Plus (best machinability) obtained at the same cutting speed of 400 25 m min1 compared with the one obtained for the AISI 4140 Standard: 295 25 m min1. The results indicate that in certain critical regions of the thermal field, improved machinability correlates with reductions in temperature that exceed measurement uncertainties, most notably in the tool where the measurement uncertainty is only 28 8C. This method holds promise for designing materials with further improved machinability. Further experiments are needed to determine if friction effects of the precipitates can be directly attributed to changes in the rake face temperatures. The method
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