Micro-milling of Ti6Al4V: An Investigation into the Size Effect and Minimum Uncut Chip Thickness

Micro-milling of Ti6Al4V: An investigation into the Size effect and Minimum uncut chip thickness

Abstract

Finding the minimum uncut chip thickness is of paramount importance in micro-scale machining in order to optimize the machining process. However, strong dependency of the minimum uncut chip thickness to the tool geometry, workpiece material, tool-work friction and process condition make its evaluation complicated. This paper focuses on determination of the minimum uncut chip thickness experimentally during micro end-milling of titanium alloy Ti6Al4V with respect to influences of cutting parameters and lubricating systems. Experiments were carried out on a CNC machining center Kern evo. Two-flute endmills with 0.8 and 2 mm diameters were used in the tests for micro and macromilling, respectively. It is discovered that the micro-scale milling caused more size effect than macromilling because of higher specific cutting forces and surface microhardness. Specific cutting forces depended strongly on feed per tooth and lubricating system, followed by depth of cut and cutting speed, mainly in micro-scale machining. All cutting parameters presented correlation inversely proportional to the specific cutting force. Finally, depending on different process parameters during micromilling of Ti6Al4V, the minimum uncut chip thickness was found to vary between 0.15 and 0.49 of the cutting edge radius.

Keywords: Micromilling, Size effect, Minimum uncut chip thickness, Titanium alloy.

1 Introduction

Micromilling, one of the mechanical micromachining methods, is generally described as a process of manufacturing miniaturized parts employing tools with diameters less than 1mm. Micromilling is kinematically similar to the conventional milling, however differences arise due to scale of the operation. Scaling down from macro to micro results in rising the so-called “size effect”, a phenomenon characterized by a non-linear increase of specific cutting force (hereafter SCF), which considerably influences aspects including cutting forces, tool wear, surface integrity, and chip formation.

Unlike conventional milling, in micromilling where the uncut chip thickness becomes comparable in size to the cutting edge radius, chip formation is influenced by a minimum uncut chip thickness (hereafter h_min or MUCT) which determines the transition between two cutting conditions; where chips are produced and where ploughing takes place. Figure 1 illustrates three configurations of chip formation with respect to the chip thickness proposed by Chae et al. [1]. Firstly, when the uncut chip thickness, h, is smaller than the h_min, elastic deformation occurs and no material will actually be removed as chip. Subsequently, when the uncut chip thickness approaches the h_min, the chip starts to form by shearing of the workpiece, still with some elastic deformation and recovery. Therefore, the removed material is less than the desired feed per tooth. Finally, when the uncut chip thickness is larger than the h_min, the elastic deformation phenomenon decreases significantly and the material is removed and formed as a chip.

In order to correctly choose the cutting condition to avoid or minimize the ploughing effect as well as achieving desired material removal, it is therefore crucial to estimate the value of MUCT. Strong dependency of the MUCT to the tool geometry [2-4], properties of workpiece material [5-8], tool-workpiece interface friction [9] and process condition make this evaluation complicated. Great efforts have been made to predict MUCT by simulation, analytical formulation, and experimentation.

 

 

Figure 1 Basic concept of micro-scale cutting

Initially, the existence of the minimum uncut chip thickness and its substantial influence on the achievable surface roughness in micromilling was pointed by Weule et al. [10]. They estimated the MUCT to the edge radius ratio for micromachining to be 0.293. According to Weule et al., the minimum uncut chip thickness considerably depends on the material properties.

Filiz et al. [11] proved the existence of “size effect” at small uncut chip thickness where a nonlinear increase of the specific cutting force was observed with feed rate reduction. They explained this phenomenon to be due to the large deformation of material as a result of negative effective rake angle.

Sooraj et al. [12] experimentally studied the size effect by micromilling of brass using carbide end mill of 1 mm diameter. The specific cutting force was found to be between 10-20 Gpa for f_z=1-5 µm/tooth and near 70 Gpa when f_z= 0.5, confirming the size effect. Minimum uncut chip thickness was evaluated 0.97 µm without specifying the cutting edge radius.

The significance of the minimum thickness of a cut in diamond turning was discussed by Ikawa et al. [3, 13] to find out that it is more significantly affected by the sharpness of the cutting edge than by the tool-workpiece interaction. According to the authors, the minimum thickness of cut might be of the order of 0.1 of the cutting edge radius.

Liu et al. [14] developed an analytical model to predict the MUCT values for Al6082-T6 aluminum and AISI 1040 steel over a range of cutting speeds and tool edge radii. The minimum uncut chip thickness was found to be ranged between 0.35–0.40 and 0.20–0.35 of r_e, respectively. They also found that when machining 1040 steel, the MUCT increased with increment of cutting speed or edge radius; however neither the cutting speed nor the tool edge radius had significant effect on minimum uncut chip thickness of the aluminum alloy.

Ramos et al. [15] experimentally studied the effects of cutting speed and cutting edge radius on the MUCT during micromilling of AISI 1045 steel. Their observation show that the MUCT significantly decreases with higher cutting speeds and to moderately increase with higher cutting edge radii. They discovered the minimum uncut chip thickness was on average 0.295 of the cutting edge radius for 100 m/min cutting speed.

To describe the influence of the material properties in a more detailed way, Son et al. [16] studied the influence of friction coefficient on the minimum uncut chip thickness in micro cutting of aluminum, brass and OFHC copper materials. They developed an analytical model for the prediction of MUCT, as a function of the cutting edge radius and the friction angle. Their observation show, that cutting edge radius and the tool-workpiece friction are the principal factors determining the minimum cutting thickness with a continuous chip. The minimum uncut chip thicknesses were found to be ranged between 0.18-0.24 of r_e for the three materials.

A more recent work from de Oliveira et al.[17] concludes that irrespective of work material, tool geometry and estimating method, the MUCT value vary between 0.25 to 0.33 of the edge radius.

Table 1 presents a summary of research works covering the determination of MUCT. According to the study background, and given in Table 1, the majority of research done in the area of minimum uncut chip thickness in micromachining processes focused on the materials of copper, brass, aluminum and steel, and very little research has been done on difficult-to-cut materials like titanium alloys. Effect of cutting edge radius and material types have frequently been investigated and such process variables as cutting parameters and lubricant were not taken in to consideration. However, these parameters may indirectly affect the size of minimum uncut chip thickness and requires further research in this regard.

Furthermore, in many of previous studies a classic and isolated way was employed to find the minimum uncut chip thickness, without any correlation with other machining characteristics, i.e. roughness, topography and chip formation.

In this paper, an experimental method is used to identify the size effect and MUCT in micro end-milling of titanium alloy Ti6Al4V considering influences of different cutting parameters and lubricating system. Results are correlated with such micromilling characteristics as specific cutting force, surface roughness, topography, and chip formation. The paper has industrial application and findings of this study can be used to improve cutting and machined surface quality when micromilling of titanium alloys.

 

Table 1 Preview research on MUCT values reported among different authors

1.2 Specific Cutting Force

The specific cutting force (SCF) is a measure of the work required to remove a unit amount of material. In micro-scale machining, ratio of the uncut chip thickness (h) to the cutting edge radius (r_e) plays an important role on the specific cutting force especially when h/r_e<<1. A nonlinear increase in specific cutting force is noticed when the uncut chip thickness decreases, due to the ploughing and size effect phenomenon, resulted by the third deformation zone which has significant contributions to the cutting mechanism and the total cutting force as well [27]. Measuring the SCF is one indirect way to determine the size effect in micromachining [28]. Specific cutting forces can be calculated by dividing the average cutting force by the mean cutting section (A_c). The produced mean cutting section and upper view of the tool path are presented in Figure 2a.

The average chip thickness per revolution (h_m) can be calculated from the following equation:

hmφ=∫φeφsfz sinφdφφe-φs=fzcos⁡φs-cos⁡(φe)φe-φs

(1)

Where f_z is the feed per tooth,

φsand

φeare the start and exit engagement angles, respectively.

Figure 2 (a) Cutting area per trochoid to calculate h_m, (b) the mean cutting section

2 Experimental Procedures

Micromilling experimental tests were carried out on an ultra-precision machining center KERN Evo with maximum 50000 rpm, which achieves a positioning accuracy of ±0.1 µm. Figure 3 shows experimental set up used in the study.

The workpiece material was selected as Ti6Al4V with a hardness of 360 Vickers (“as received” material), which is commonly used in aviation and medical devices. Its chemical composition is given in Table 2. A block shape workpiece with dimension of 65×65×8 mm were used in the experiments. Milling tests are made with linear slotting operation in the test area (A_t=14×14 mm) as shown in Figure 3.

Table 2 Chemical composition of Ti6Al4V (wt. %)

Figure 3 Experimental set-up

For the investigations, two-flute carbide endmill tools with diameters of 0.8 and 2.0 mm from NS-Tools were used (MSE230) representing the micro- and macro-scale machining respectively. To measure the cutting edge radii (r_e) of both micro- and macro-endmills, they were wire cut and then the edge radii were measured using Optical Microscope. The mean value of three measurements was found to be 6.089 ±0.234 µm or ±3.8%. In order to minimize the tool wear effect on measured results, a separate tool was used for each machining condition. Figure 4 shows the specifications of used tools in experiments.

 

Figure 4 Micro cutting tool geometry

The machining process was performed following successive steps:

– After a spindle warm-up of 15 min, the specimen was surfaced to get the upper plane (reference for the depth of cut) with a 10 mm diameter endmill, by sweeping along the X-axis of the machine tool. Face milling was carried out using spindle speed of 5500 rpm, feed rate of 280 mm/min, and axial depth of cut of 0.2 mm.

– Prior to tests and after loading micro tools, the static run-out at the end of tool shaft was controlled to be better than 1 μm.

– Slots were machined along the X-axis with a 0.8 and 2 mm diameter endmill, with full diameter engagement.
Before any change of cutting speed value, the spindle was again submitted to a warm-up. Spindle warm-up is necessary to reduce thermal expansion and thus to control the depth of cut.

A set of experiments were designed to evaluate size effect in milling tests. The factors and levels to be studied are as shown in Table 3. Cutting parameters are designed so that there would exist one condition with same cutting area for both micro- and macro-scale. In cutting tests with f_z=12 and a_p=150 condition, feed per tooth and depth of cut are adopted as maximum for micro-scale milling and minimum for macro-scale milling. Width of cut was the same as the size of tool diameters.

Table 3 Milling parameters and their levels

All milling tests were performed under two modes of dry cutting and minimum quantity lubrication (MQL). For the MQL, a two-nozzle Unilube Micro Lubrication System was used in the experiments. The mixture of oil and air (15 ml/h of UNILUBE 2032 lubricant with 35 mm²/s viscosity) was pulverized in an air flow of 200 l/min at a pressure of 0.6 MPa.

Analysis of Variance (ANOVA) at 95% level of significance was performed for micro- and macro-scale milling separately. Each test was repeated three times and the average values were taken into consideration for further analysis of variance (ANOVA).  Specific cutting force (SCF), microhardness (Hv), surface roughness (Ra) and topography were selected as the output parameters in this study. To determine the specific cutting forces, the mean cutting section for each machining case was calculated using CAD software, according to Figure 2 and Eq. 1. Table 4 presents the mean cutting sections of the milling conditions given in Table 3.

 

Table 4 Mean cutting sections

The milling forces were acquired with a Kistler MiniDyn 9256C1 3-component dynamometer with its charge amplifier (type 5070) and recorded by a LabView application with a sampling rate of 42 kHz. Figure 1 shows the setup used for force measurement experiments.

A Nanofocusµsurf confocal whitelight microscope was used to measure the burr width and to determine the topography and surface roughness of the machined surfaces.

Microhardness measurements were performed employing a Micro indenter Vickers Bareiss (model Vtest) tester, with a precision of 1 Vickers and with 0.1 Kg of load, during 15 s for all the measurements. Three replicates were made in the cross section of the machined surface, 50 µm in depth.

To find the minimum uncut chip thickness, more additional tests were carried out. More discretized feed rates (0.06, 0.3, 0.9, 1.5, 2.1, 3, 6, 12, 21, 30, 42, 60 μm/tooth) were used to evaluate the specific cutting force, burr formation, roughness and topography.

3 Results and Discussion

Measurement of the microhardness generated after micro- and macro-scale machining was made whose results are shown in Figure 5. In all milling tests the microhardness values were higher than the “as received” work material microhardness. Compared to the reference “as received” material, the micromilling showed 33% increase on average the microhardness, while macromilling increased 5. As a result, micromilling was more significantly dependent on the size effect irrespective of machining conditions.

 

 

Figure 5 Effects of milling conditions on workpiece microhardness, 50 µm below the milled surface.

The higher values of hardened surface for the micromilled workpiece can be attributed to the size effect and specific cutting force increase. The dependence of the specific cutting force on milling conditions and machining scales is shown in Figure 6. Results showed that using MQL application, compared to dry cutting, had great influence on specific cutting force reduction both in macromilling (15%) and micromilling (57%), particularly the latter one. This can be attributed to tool wear and build-up edge formation. Larger tool wear and build-up edge formation in dry cutting results in rounding and increasing the cutting edge radius, thus increasing cutting force. Increasing the cutting edge radius causes higher third deformation zone forces and these effects are of great importance in the micro-scale where the chip thickness size is almost the same as the cutting edge radius [27]. This effect will be explained more deeply below. However, using lubricants can remarkably reduce friction and cutting temperature. Furthermore, by preventing formation of build-up edge and keeping the cutting edge of the tool sharp, it provides lower cutting force and specific cutting force as well.

In case of cutting parameters, reduction of the specific cutting force with the increase of cutting speed corresponded to 14 % and 6% respectively for micro and macromilling. At higher cutting speed, cutting forces as well as the specific cutting forces get reduced. In fact, by increasing the cutting speed, the deformation zone volume reduces (the shear angle increases) and, consequently, lower shear energy is required for machining [29].

When depth of cut tripled, specific cutting force reduced 13% in micromilling. The same relationships for macromilling attained only 6%. The decreased specific cutting force (SCF) with increased depth of cut indicates that the increase of cutting section area is dominant over cutting force increase during micromilling of this alloy. Moreover, quantity of grains per cutting section may vary the SCF more remarkably considering the anisotropy due to grain contours and different crystallographic orientations [17]. Therefore, in greater mean cutting section more grains will be cut where variation of SCF can be reduced due to more homogeneous chip removal during micromilling at higher depth of cut.

The mean specific cutting force for feed rate was reduced approximately 55% for micromilling and 27% for macromilling. Hence, the reduction of specific cutting force as cutting parameters increased (size effect) is more pronounced in micro scale and also more sensible to the feed per tooth.

 

Figure 6 Influence of machining parameters and milling scales on the SCF.

Table 5 presents the ANOVA data to support the distinct sensibilities of feed per tooth (f_z), depth of cut (a_p), cutting speed (v_c) and lubricating system upon specific cutting force. The feed per tooth and cooling system are found to be significant upon specific cutting force for micromilling once P-value was smaller than 0.05 (95% confidence) in the ANOVA table.

Nevertheless, cooling system is the only significant parameter for macromilling while the other cutting parameters are insignificant. Feed per tooth has a major impact on the specific cutting force than cutting speed and depth of cut and all cutting parameters are inversely proportional to the response, which confirms the downward trend of specific cutting force averages presented in Figure 7, irrespective machining scale employed.

Figure 7 Effect of cutting parameters on SCF in: (a) micro-scale and (b) macro-scale.

Table 5 ANOVA of milling parameters upon SCF

As presented in Figure 6, the effect of machining scale on the SCF can be analyzed by comparing the conditions of f_z12–a_p150 (macromilling) and f_z12–a_p150 (micromilling). In spite of the same cutting parameters and cutting section area, the SCF for micro-scale was ~150% (dry cutting) and ~80% (MQL application) greater than for macro-scale milling, implying that different specific cutting forces are needed for distinct geometries of cutting section areas and chip formation as can be seen in Figure 5. The main reason for the higher amounts of SCF produced in micro-scale can be attributed to the “edge forces” or “third zone” which are greatly influenced by the ploughing [27]. To confirm the significance of ploughing in micro-scale, edge forces are identified by linear regression of the measured forces for different feed rates, illustrated on Figure 8. The edge forces were found to be 8.89 and 0.31 N respectively for micro- and macro-scale in dry cutting; while for the MQL, values of 3.11 and 0.76 N were resulted for micro- and macro-scale, respectively, suggesting that effect of third deformation zone on total cutting force in micro-scale is significantly higher compared to macro-scale milling operations. Additionally, according to Figure 8, using MQL application resulted in lower edge forces mainly due to its positive effects on reducing tool wear and consequently preventing enlargement of the cutting edge radius, while effects of the edge radius on edge forces and cutting forces are very important in micro milling [27].

Figure 8 Feed rate (µm/tooth) vs total cutting forces (N) derived for both micro- and macro-scale at 60 m/min cutting speed and 150 µm depth: (a) dry, (b) MQL.

As illustrated in Figure 9, a recurrent behavior can be seen in the dynamometer signals through analyzing the cutting force components. The normal component (and so the cutting force) can be divided into six distinct partitions, corresponding exactly with the mechanism of chip formation.

 

Figure 9 Cutting force components for milling condition f_z12-a_p150: (a) and (b) dry, (c) and (d) MQL condition

Figure 10 Partitions and engagement angles that corresponds to the cutting force component

In Figure 10,

φ1=0°corresponds to point A. Tool cutting edge starts to contact with the work material at point A (partition I), where the normal force begins to rise as well. At this moment, the up-milling strategy occurs while the chip thickness increases continuously.

At contact angle of

φ2the cutting edge reaches the MUCT. Until reaching this point, large deformation of the material (ploughing) takes place at the part-tool interface without any appreciable chip formation.

Following the minimum uncut chip thickness, the chip formation begins until the angle reaches point B at

φ3=30.26°, where the chip thickness is in accordance with the r_e. Partition II encompasses points B and C, where the latter is

φ4=39.55°and the chip thickness reaches the mean thickness h_m. At this point, the instantaneous normal force value equals to the mean normal force.

Between

φ4=39.55°and

φ5=90°(partition III), the chip thickness increases to reach the maximum thickness (f_z) at point D. After that the strategy will change and down-milling occurs instead of up-milling.

By beginning partition IV (down-milling), the contact angle increases and consequently, chip gradually diminish to thickness h_m at point E (

φ6=140.45°).

As the chip thickness becomes the same as the r_e, partition V ends at point F with

φ7=149.74°. Once more, the cutting edge reach the MUCT at

φ8(partition VI) and finish its cycle at

φ9=180°(point G) resulting in a zero chip thickness.

Therefore, such partitions and engagement angles that corresponds to the cutting force, can be attributed to chip formation at the very defined partitions; at which, the thickness reaches specific values namely r_e, h_min, h_m and f_z.

By knowing that the size effect is more highlighted in micromilling, for f_z is more influential on SCF and the relation between f_z and r_e plays an important role on the size effect, Figure 11 presents the asymptotical growing of the SCF for feed rates more discretized and smaller than cutting edge radius. Two different scale domains can be divided. Macro-scale is identified by a slight decrease in SCF when f_z> 6 μm/tooth. Micro-scale occurs as the feed per tooth varies between 0.06 and ~6 and the SCF increases hyper-proportionally when feed decreases.

In case of the macro-scale, regardless of different machining conditions, the SCF tends toward a constant level near 4 GPa with increasing the f_z. This demonstrates that at higher levels of feed per tooth, the cutting edge radius does not affect chip formation due to its lower measurement than cutting thickness. Furthermore, for micro-scale domain, the SCF approaches to the same range as finish grinding ones for the lower levels of feed per tooth [30]. This highly-accelerated growth implies that the values near ~2.1 or less for feeds per tooth may have the same size as the cutting edge radius, which inflicts damages on the chip formation process without complete material removal, and profoundly increases the SCF.

 

 

Figure 11 Dependence of specific cutting force on feed per tooth at various machining conditions in micromilling

Comparing the effects of milling parameters on SCF as illustrated in Figure 11, the specific cutting forces lightly reduces as the depth of cut (a_p) and cutting speed (v_c) increase, independently of feed per tooth.

By increasing the depth of the cut, the specific energy decreases, which affects the lower feed rates where fz<re more significantly, but in macromilling scale where fz>re does not change significantly. The cutting speed has the same influence as depth of cut on special cutting force.

Meanwhile, MQL application had great influence on reduction of the specific cutting force particularly at lower feeds per tooth. This is mainly due to effectiveness of MQL on reducing the tool wear and build-up edge formation which are inevitable in dry cutting of titanium alloys and thereby minimizing the ploughing effect. However, it should be noted that with MQL application similar trend to the dry cutting is still observed for specific cutting force reduction when the feed per tooth increases and the explained domains do not change very much.

Moreover, coefficient of determination, R², is found to be greater than 0.98 confirming the validity of test results. It means that the SCF can be well defined by a negative potential function (

SCF=k1.f-k2). So, the size effect is more profound when the k₂ coefficient increases.

According to Figure 11, the size effect is strongly depending on the relation between f_z and r_e. Providing that the cutting edge radius (r_e) was measured by optical microscopy, the MUCT at which chip formation starts remains to be assigned.

In order to investigate the size of MUCT, the feed per tooth was incrementally increased. Figures 12, 14, 15 correlate roughness, topography and chips of the micromilled surface for the following rates of f_z/r_e: 1%, 5%, 15%, 25%, 34%, 49%, 99%, 197%, 345%, 493%, 690%, and 985%.

Surface finish of the bottom surface of the micro-slots was measured using a confocal white-light microscope (Nanofocus). The dependence of the roughness Ra, on machining parameters is depicted in Figure 12. As observed, regardless of milling conditions, these ranges of feed per tooth can be divided into three distinct regions as micro, transition and macro regions with respect to the Ra values. First, in the range where f_z is between 0.06 and 1.5 (0.01 < f_z/r_e < 0.25), namely the Micro region, surface roughness decreases with an increase of feed per tooth irrespective of cutting speed and depth of cut, particularly in the dry cutting condition. This is because of reducing ploughing effect for higher feed per tooth and thereby less elastic recovery of the workpiece material. This agrees with Mativenga et al. [31] who reported that when machining at feeds per tooth less than the cutting edge radius, surface roughness increases with a decrease of feed per tooth.

 

Figure 12 Effect of feed reduction on surface roughness at: (a) a_p=50 µm and (b) a_p=150 µm.

Second, when f_z is between 1.5 and 6, named as Transition region in Figure 11, surface roughness remains constant and the optimum surface finish is obtained.

Third, where f_z is between 6 and 60 ( 1< f_z/r_e <10 ), the Macro region, surface roughness increases with an increase of chip load. In this case, the effect of feed per tooth is the same as the one occurring in macromachining. This agrees with Filiz et al. [11] who reported that when micromilling at feed per tooth higher than the cutting edge radius, surface roughness increase with feed per tooth as in shearing mechanisms.

In case of MQL application, as shown in Figure 12a and b, similar behavior as for the dry cutting is observed except for the first region where smaller Ra values are achieved. This is associated with the tool wear. Figure 13 compares the microtools’ condition after the test. It obviously can be seen that MQL application reduces tool wear as well as the buildup edge formation, thus prevents rounding of cutting edges and so the ploughing effects. Consequently, the best roughness Ra in micromilling of Ti6Al4V is at a trade-off between the ploughing and traditional feed effects.

To support the above explanations, topography of machined surface at various milling conditions is presented in Figure 14. A topographic pattern formed by excessive ploughing is observed when using lower feeds per tooth.

Observing Figure 14a₁-a₈, with increasing the feed and so the chip thickness, roughness pattern of the machined surface is changing as well. For the feed rate of 1.5 μm/tooth (Fig. 14a₄), there is still a minimum amount of ploughing force which influences the micromilled roughness. However, for the tool feeds greater than 3 μm/tooth, such roughness pattern completely disappears and tool feed mark takes the place of that (Fig. 14a₆). So, when cutting thickness exceeds the f_z=3, the chip forms completely and the SCF reduces to levels smaller than 4 GPa as presented in Figure 11.

Figure 13 Microtools wear condition in: (a) MQL and (b) dry cutting

However, when using MQL application, cleaner cut with more clear topography is observed and roughness pattern disappears sooner compared to the dry cutting (Fig. 14c₁-c₈). For feeds per tooth greater than 2.1 μm/tooth (Fig. 14c₅), tool feed marks is completely formed. This is attributed to the cutting edge radius size, and effects of build-up edge formation and tool wear which prevent enlarging the edge radius. In addition, it can be concluded that a better surface is obtained once micromilling is accomplished at higher depth of cuts. The aforementioned argument is aligned with the findings of specific cutting force, depicted in Figure 11, where, as a result of ploughing, higher amount of SCF is obtained at lower level of depth of cut.

 

Figure 14 Machined surface topography (v_c=60 m/min)

Furthermore, the magnitudes of the top burr width were measured using an optical microscope.  In dry cutting, the burr width size varies from 22 to 442 µm depending on the ratio of feed per tooth to the cutting edge radius. Burr formation reduces when feed per tooth increases. When f_z<3 µm, larger burrs were formed indicating a higher portion of ploughing during chip formation. At higher feed per tooth when f_z>3 µm, the burr size is significantly reduced and stabilized near 22 µm. This stabilization happened at f_z=21 µm/tooth for a_p=50 µm and at f_z=12 µm/tooth for a_p=150 µm, respectively. However, it should be noted that when using MQL application much smaller burrs were formed varies from 19 to 212 µm depending on the ratio of feed per tooth to the cutting edge radius.

Chip formation was also explored using the digital microscope. Figure 15 presents the formation of the continuous and discontinuous chips at different feeds per tooth. For feed rates below 3 µm/tooth chips were not formed continuously, but rather intermittently. Figures 15a-e presents a gathering of particles removed from the workpiece by cutting tool which cannot be designated as chip-like. Because of the processes of crushing and extruding, discontinuous chip formed for lower feeds per tooth of 0.06, 0.3, 0.9, 1.5 and 2.1. When the f_z was greater than 2.1 µm (Fig. 15f), chips began to form continuously, which confirmed that the MUCT has been passed.

 

Figure 15 Microscopic images of chip formed for micromilling (dry cutting, v_c= 60 m/min, a_p= 150 μm)

Owing to the low volume effectively removed from dry micromilled part of these five smaller feed rates (0.06, 0.3, 0.9, 1.5 and 2.1 µm/tooth) and the high deformation of micromilled surface, the SCF increased to levels close to or greater than 70 GPa (Figure 11). In addition, the minimum uncut chip thickness required to provide complete chip formation was not achieved for the lowest level of feed in particular. This may be confirmed by visual verification using images of those extracted particles presented in Figure 15a-e. However, Figures 15f–i clearly show that the particles extracted by the cutting tool may be classified as chips due to present gathering of curved ends which are replicas of the microtool tip radii. Therefore, the f_z= 3 μm/tooth is recognized as a candidate for the MUCT that represents the feed per tooth from which the complete chip formation may happens.

With these in mind, Figure 16 shows a composite result of chip formation, specific cutting force, and topography as well as surface roughness up to the interval of the ratio between feed per tooth and cutting edge radius, assigned as MUCT.

Figure 16 Determination of minimum uncut chip thickness by combining the chip formation, workpiece roughness and specific cutting force (dry cutting at v_c=60 m/min and a_p=150 µm).

For f_z=1.5 μm/tooth (f_z/r_e=25%), the chip is formed, but the qualitative roughness still shows noticeable ploughing. For f_z=3.0 μm/tooth (f_z/r_e=49%), the chip is completely formed and the micromilled surface is free of ploughing with minimum roughness value. In addition, this h_min interval is placed at the inflectionregion of the SCF curve, where feeds per tooth smaller than h_min range cause excessive ploughing (increasing SCF) and feeds per tooth greater than h_min generate feed marks (decreasing SCF). Therefore, considering the combined analysis of all variables, it can be inferred that h_min is between 1.5 and 3.0 μm (0.25-0.49 of r_e), since the chip will be formed, but still some ploughing may or may not be observed. As a result, it should be noted that determination of the h_min is more efficient when combining qualitative and quantitative machining characteristics, mainly surface roughness and chip formation.

Changing the cutting parameters such as depth of cut and cutting speed does not affect the minimum uncut chip thickness significantly, while an effective lubrication system can significantly reduce tool wear and build-up edge formation especially compared to dry machining of the given alloy. As a result the specific cutting force reduces and so does the minimum uncut chip thickness. The value of h_min in MQL conditions was found to be between 0.9 and 2.1 (15- 34% of r_e).

With all the quantitative and qualitative researches conducted on size effect and h_min, the main idea when investigating micro-scale milling is not to necessarily find the MUCT, but to determine a critical value which provide complete chip formation and preserves the machined surface integrity as well. This critical thickness will be larger than MUCT. Therefore, just finding the MUCT does not guarantee a preserved micromilled surface integrity. As an illustration, in this particular study, f_z=1.5 μm/tooth could be MUCT since chips were formed (Fig. 15); but this feed per tooth still ploughed the machined surface (Fig. 14) and increased the SCF considerably (Fig. 11).

Finally, it can be concluded that depending on different process parameters during micromilling of Ti6Al4V, the h_min will vary between 0.15 and 0.49 of the cutting edge radius.

4 Conclusions

This paper studied the effect of milling scales on size effect by analyzing the behavior of the machined surface microhardness and specific cutting force. Moreover, the minimum uncut chip thickness was was experimentally investigated by correlating quantitative variables of specific cutting force and surface roughness with qualitative analysis of the chip formation and machined surface topography  during micromilling of Ti-6Al-4V. The following conclusions can be drawn from the present study:

• The size effect, represented by specific cutting force, proves to be governed by the mechanism of surface and subsurface hardening in the workpiece, which is reflected in the workpiece machined surface through the plastic deformation zone around the tool-workpiece contact. The size effect occurs in both macro and micromilling, but is more pronounced in micromilling; because the ratio of f_z/r_e can reach values lower than unit since smaller tool feeds are usually used to achieve to finishing requirements for the part and to avoid microtool breakage.
• The size effect is influenced by cutting section because it comes from the cutting thickness. But, different specific cutting forces are resulted when using equal areas since area shapes are distinct.
• Through scaling of the undeformed chip thickness, it was inferred that with low undeformed chip thicknesses, the specific cutting forces increase nonlinearly and a significantly higher burr formation with poor surface finish occurs because of ploughing effects. The best surface finish was obtained when the undeformed chip thickness is selected to be in the transition zone. At this range there is a trade-off between the ploughing effect and conventional shearing mechanisms. Feed per tooth and MQL application were found to be dominant factors for reducing the specific energy or improving surface finish.
• Determination of the minimum uncut chip thickness based on combination of quantitative and qualitative analyses is found to be efficient, especially when correlating the specific cutting force with surface roughness, topography and chip formation (both qualitative and quantitative evaluation).
• The study suggests that minimum uncut chip thickness can be varied approximately between 0.15 and 0.49 of the cutting edge radius.
• It is found that other than the ratio of feed per tooth to tool edge radius, the MQL application and to some extent the depth of cut, are other dominant control factor for influencing the size effect or process mechanism. Cutting speed was found to be insignificant. This information is important for optimizing the process or for breaking the lower limit of the micro-machining process.

References

[1] Chae J, Park S S, Freiheit T (2006) Investigation of micro-cutting operations. Int J Mach Tools Manuf 46(3–4):313–332.

[2] Basuray PK, Misra BK, Lal GK (1977) Transition from ploughing to cutting during machining with blunt tools. Wear 43:341–9.

[3] Ikawa N, Shimada S, Tanaka H, Ohmori G (1991) An atomistic analysis of nanometric chip removal as affected by tool-work interaction in diamond turning. CIRP Annals-Manufacturing Technology 40(1):551-554.

[4] Weule H, Huntrup V, Tritschler H (2001) Micro-Cutting of steel to meet new requirements in miniaturization. CIRP Annals – Manufacturing Technology 50(1):61–64.

[5] Kim C J, Mayor JR, Ni J (2004) A static model of chip formation in microscale milling.
Trans ASME J Manuf Sci Eng 126:710–8.

[6] Weule H, Hüntrup V, Tritschler H (2001) Micro-cutting of steel to meet new requirements in miniaturization. Ann CIRP 50:61–4.

[7] Vogler MP, DeVor RE, Kapoor SG (2004) On the modelling and analysis of machining performance in micro end-milling. Part I. Surface generation. Trans ASME J Manuf Sci Eng 126:685–94.
[8] Son SM, Lim HS, Ahn JH (2005) Effect of the friction coefficient on the minimum cutting thickness in micro cutting. Int J Mach Tool Manuf 45:529–35.

[9] Yuan Z J, Zhou M, Dong S (1996) Effect of diamond tool sharpness on minimum cutting thickness and cutting surface integrity in ultra precision machining. J Mater Process Technol 62(4):327–330.

[10] Weule H, Huntrup V, Tritschler H (2001) Micro-Cutting of steel to meet new requirements in miniaturization. CIRP Annals – Manufacturing Technology 50(1):61–64.

[11] Filiz S, Conley CM, Wasserman MB, Ozdoganlar OB (2007) An experimental investigation of micro-machinability of copper 101 using tungsten carbide micro-endmills. Int J Mach Tools Manuf 47:1088–1100
[12] Sooraj V, Mathew J (2011) An experimental investigation on the machining characteristics of microscale end milling. Int J Adv Manuf Technol 56:951–958.

[13] Ikawa N, Shimada S, Tanaka H (1992) Minimum thickness of cut in micromachining. Nanotechnology 3(1):6.

[14] Liu X, Devor R E, Kapoor S G (2006) An analytical model for the prediction of minimum chip thickness in micromachining. J Manuf Sci Eng 128:474–481.

[15] Cuba Ramos A, Autenrieth H, Strauß T, Deuchert M, Hoffmeister J, Schulze V (2012) Characterization of the transition from ploughing to cutting in micro machining and evaluation of the minimum thickness of cut. J Mater Process Technol 212:594–600.

[16] Son SM, Lim HS, Ahn JH (2005) Effects of the friction coefficient on the minimum cutting thickness in micro cutting. J Mach Tools Manuf 45:529–535.

[17] de Oliveira FB, Roger Rodrigues A, Teixeira Coelho R, Fagalide Souza A (2015) Size effect and minimum chip thickness in micromilling. Int J Mach Tools Manuf 89:39–54.

[18] Shimada S, Ikawa N, Tanaka H, Ohmori G, Uchikoshi J, Yoshinaga H (1993) Feasibility study on ultimate accuracy in microcutting using molecular dynamics simulation. CIRP Ann Manuf Technol 42(1):91–94.

[19] Vogler MP, DeVor RE, Kapoor SG (2004) On the modeling and analysis of machining performance in micro endmilling, part II: cutting force prediction. J Manuf Sci Eng 126:695–705.

[20] Son SM, Lim HS, Ahn JH (2005) Effects of the friction coefficient on the minimum cutting thickness in micro cutting. J Mach Tools Manuf 45:529–535.

[21] Lai X, Li H, Li C, Lin Z, Ni J (2008) Modelling and analysis of micro scale milling considering size effect, micro cutter edge radius and minimum chip thickness. Int J Mach Tool Manuf 48:1–14.
[22] Woon KS, Rahman M, Fang F Z, Neo K S, Liu K (2008) Investigations of tool edge radius effect in micromachining: a FEM simulation approach. J Mater Process Technol 195:204–211.

[23] Kang I S, Kim J S, Seo Y W (2011) Investigation of cutting force behaviour considering the effect of cutting edge radius in the micro-scale milling of AISI 1045 steel. Proc Inst Mech Eng. Part B: J Eng Manuf 225:163–171.

[24] Malekian M, Mostofa M G, Park S S, Jun M B G (2012) Modeling of minimum uncut chip thickness in micro machining of aluminum. J Mater Process Technol 212:553–559.

[25] SrinivasRao  U, Vijayaraghavan L (2013) Determination of minimum uncut chip thickness in mechanical micro-machining using Johnson-Cook fracture model. International Journal of Mechatronics and Manufacturing Systems 6(4):367-380.

[26] Wu X, Li L, Zhao M, He N (2016) Experimental investigation of specific cutting energy and surface quality based on negative effective rake angle in micro turning. The International Journal of Advanced Manufacturing Technology 82(9-12):1941-1947.

[27] Budak E, Ozlu E, Bakioglu H, Barzegar Z (2016) Thermo-mechanical modeling of the third deformation zone in machining for prediction of cutting forces. CIRP Annals-Manufacturing Technology 65(1):121-124.

[28] Lui K, Melkote SN (2007) Finite element analysis of the influence of tool edge radius on size effect in orthogonal micro-cutting process. Int J Mech Sci 49:650–60.

[29] Singaravel B, Selvaraj T (2016) Experimental investigation on cutting forces, specific cutting pressure, co-efficient of friction and shear energy in turning of HSLA steel. Management and Production Engineering Review 7(1):71-76.

[30] Malkin S (2008) Grinding Technology: Theory and Applications of Machining with
Abrasives, second ed., Industrial Press, New York.

[31] Aramcharoen A, Mativenga P T (2009) Size effect and tool geometry in micromilling of tool steel. Precision Engineering 33(4):402-407.