Investigation of Thermally Assisted End Milling of 254 SMO Super Austenitic Stainless Steel

doi:10.21203/rs.3.rs-5246858/v1

Given the challenges associated with machining super austenitic stainless steels (SASS), including their high mechanical strength, low thermal conductivity, high work-hardening tendency, and high ductility, thermally assisted machining (TAM) has emerged as a promising approach to enhance the machinability of these materials. Thus, in this study, the machining forces, tool wear, and surface finish generated under different cutting conditions in the milling of SASS 254 SMO heated to 200 ºC were compared to the results obtained in a related study applying dry cutting and commercial nanofluid in minimum quantity lubrication (NMQL). The results showed that machining forces in TAM were, on average, 18.4% lower than in dry cutting and similar to those in NMQL milling (reduction of 19.3%), indicating that thermal softening facilitated chip deformation and reduced machining forces. The tool wear rate in TAM was lower than that in dry cutting, although it was slightly higher than that in NMQL milling (mainly at the end of the test). However, the presence of adhered material on the machined surface and the formation of defects, such as smearing and side flow, imply that the elevated temperature of the workpiece may adversely affect its surface quality.

Super austenitic stainless steel

end milling

thermally assisted machining

machinability

Stainless steels (SS) are widely used because of their corrosion resistance, which is provided by the chromium oxide and hydroxide layers on their surfaces. Amongst the five main classes (ferritic, martensitic, austenitic, precipitation-hardened, and duplex [1]), austenitic stainless steels (ASS) correspond to 72% of the volume of SS produced owing to their high ductility and easy standardization of the manufacturing process [2]. A particular group within this class, the super austenitic stainless steels (SASS) such as AL-6XN, 904L, 254 SMO, and 654 SMO, are notable for their high chromium, nickel, molybdenum, and nitrogen contents, with iron content equal to or less than 50% [3].

Research on SASS and its applications is increasing because of its high corrosion resistance, which is very attractive to the energy, pharmaceutical, healthcare, chemical, petrochemical, marine, and aerospace industries [4]. However, their application is gradual because of the difficulty in obtaining components manufactured from them. SASS is considered a low machinability material owing to its high mechanical strength, low thermal conductivity, high work-hardening tendency, and high ductility [5] [6]. These characteristics result in a high specific cutting pressure, generation of long and serrated chips, formation of a built-up edge (BUE), high tool wear rate, and poor machined surface quality [2] [7] [8]. Furthermore, machining forces tend to present higher fluctuations than those of carbon steels, mainly because of the variation in chip thickness (serration), which then affects the surface finish. The tool wear rate is intensified by the low thermal conductivity of SASS, which leads to high temperatures in the tool-workpiece contact area. Notably, the tool wear rate depends directly on the cutting speed chosen during machining [7]. Another problem is the formation of compressive residual stresses on the machined surface, which are influenced by the mechanical properties of SASS, its low thermal conductivity, and plastic deformations resulting from the machining process [9] [10].

One way to reduce compressive residual stresses and facilitate machining in the SASS is to reduce the work-hardening effects inherent to these materials, which can be achieved through thermal softening. This process reduces material hardness in the cutting zone and facilitates plastic deformation. This phenomenon reduces the hardness of the material in the cutting zone and facilitates plastic deformation. In this case, increasing the temperature above the plastic deformation temperature of the material leads to a decrease in the work hardening [11] [12] [13]. Thermally assisted machining (TAM) has emerged as a valuable method for economically producing high-quality parts because it integrates the principles of conventional machining with controlled heating during the manufacturing process. This procedure involves using devices that apply heat to the workpiece during cutting to change the material properties and facilitate its machining [14]. This thermal assistance can reduce material strength, increase ductility, reduce tool wear, and often improve machinability, mainly in difficult-to-cut materials. Moreover, TAM can reduce the risk of surface cracking and enhance the surface quality of parts, opening up new possibilities for manufacturing high-precision, high-performance components [14] [15]. Amongst the potential heating sources in TAM, acetylene flames, electric currents, induction heating (eddy currents), laser, and plasma are noteworthy. Currently, laser and plasma are considered the most efficacious sources of thermal assistance for the machining process, primarily because of their ability to apply controlled heat in specific workpiece regions, optimizing the energy expended for heating [16] [17].

Some studies have applied localized heating to milling operations. Xu et al. [18] proposed electric discharge-assisted milling (EDAM) of a Ti-6Al-4V titanium alloy to facilitate machining. EDAM resulted in a higher reduction in roughness values and decreased machining forces compared with conventional machining. However, despite the reduction of defects on the machined surface owing to the decrease in chip fragments adhered to the surface, excessive energy input by the EDAM in the cutting zone produced new defects, such as the appearance of debris, pits, and pitting corrosion. Teja et al. [19] analyzed the effect of TAM using induction heating at 400 ºC on the end milling of EN24 hardened steel compared with room-temperature machining. The authors observed a decrease in average roughness values in TAM (0.28 to 0.33 µm) compared to dry machining (0.33 to 0.77 µm). Moreover, TAM resulted in lower machining forces than dry machining. However, Grzesik and Ruszaj [15] emphasized that induction heating has limitations related to the heat concentration and temperature profile according to the cutting tool movement. Karabulut et al. [20] analyzed the influence of TAM via open flame preheating at 250 ºC in face milling of Ti-6Al-4V titanium alloy, statistically comparing the effects of machining conditions on surface roughness, vibrations, energy consumption, and flank tool wear. The authors observed that the lowest roughness was achieved by dry milling because the heating process resulted in material smearing, increasing the roughness values in the TAM by 15%. However, the heated conditions exhibited low vibrations and energy consumption. The highest tool wear occurred during dry milling, whereas a slight wear reduction was observed during thermally assisted machining. When applying minimum quantity lubrication (MQL) in TAM, the authors observed a considerable improvement in the process performance and lower tool failures. However, open flame preheating also has limitations related to temperature accuracy in the cutting zone. Even so, the authors ensured accuracy through a computational numerical simulation of the temperature profile.

The correct selection of cutting parameters for the SASS machining tends to be complex because it requires minimizing the effect of excessive temperatures in the cutting zone (which then reduces the tool wear rate), decreasing the BUE formation, and attenuating force fluctuations. In addition, determining the appropriate heating method for each material and process is not yet fully understood, with variations in the optimal cutting points and heating conditions according to the desired response variable [21]. Furthermore, the effectiveness of TAM is presumed to be assured if the heating temperature is controlled according to the plastic deformation temperature of the material. For example, each group of nickel-based superalloys has a different plastic deformation temperature, depending on the alloy constituents and their content [14]. The intensity of this temperature, the deformation rate, and the heating effect at this rate can modify the material structure and control the yield and rupture stress values [15].

Thus, this study seeks to innovatively apply the controlled heating of the workpiece in the SASS machining, which has yet to be explored in the literature to achieve the benefits of thermal softening provided by TAM. The objective is to evaluate the influence of heating on the end milling process of 254 SMO super austenitic stainless steel in terms of machining forces, tool wear, and surface finish, comparing the results with previous studies on the machining of this material under the dry condition (at room temperature) and by applying a commercial nanofluid in minimum quantity lubrication (NMQL).

The experiment involved the end milling of Ultra® 254 SMO super austenitic stainless-steel workpieces with dimensions of 70 mm x 30 mm x 10 mm. Table 1 shows the average chemical composition of the material used in this study, according to the manufacturer's inspection certificate No. 560014 − 303298:0 [22]. Other material characteristics: hardness of 160 HB, PRE = 43, density of 8.0 kg/dm³, modulus of elasticity of 195 GPa, and thermal conductivity of 14 W/(m⋅°C).

Table 1

Chemical composition of Ultra^®254 SMO.
Values	C	Mn	P	S	Si	Cr	Ni	Mo	N	Cu
Maximum	0.020	1.00	0.03	0.010	0.80	20.50	18.50	6.50	0.22	1.00
Certificated	0.012	0.48	0.02	0.001	0.38	20.12	17.76	6.02	0.20	0.69
Minimum	-	-	-	-	-	19.50	17.50	6.00	0.18	0.50

Heat-assisted end milling was performed in a ROMI Discovery 308 machining center (maximum power of 5.5 kW and maximum speed of 4000 rpm). A Walter Tools Xtra-tec® F4042R.W20.02 end mill tool with a diameter of 20 mm and a holder for two Walter Tools Tiger-tec Silver® ADMT10 inserts, class WSM35S, with a tip radius of 0.8 mm and PVD TiAlN + Al₂O₃ coating was used.

The experiment consisted of executing 15 runs (corresponding to a machined length of 450 mm or a cutting time of 2.7 min), varying one cutting parameter every five runs while keeping the other two parameters constant at a medium level. Table 2 shows the cutting parameters used in this study. It should be noted that runs 3*, 8*, and 13* maintain the three parameters at a medium level. These reference runs are used to verify variations in machining forces due to tool wear.

Table 2

Cutting parameters selected for each coolant-lubricant condition
	Varying depth of cut					Varying feed per tooth					Varying cutting speed
Run	1	2	3*	4	5	6	7	8*	9	10	11	12	13*	14	15
v_c	100					100					60	80	100	120	140
f_z	0.06					0.02	0.04	0.06	0.08	0.10	0.06
a_p	0.2	0.4	0.6	0.8	1.0	0.6					0.6

The thermally assisted machining proposed in this study was based on the controlled heating of the workpiece at 200°C, allowing for a variation of up to 5% in the average temperature field. This control ensures that the machined region remains within the defined temperature range even when the axial cutting depth (a_p) changes. A workpiece fixture device with electric-resistance heating controlled by a potentiometer (up to 3.0 kW) was developed for this study. The equipment also features internal cooling, enabling it to be coupled to a piezoelectric dynamometer without a heat source, ensuring operational stability on force measurements. Figure 1 shows the experimental setup of the system.

To determine the heat flux (q"_heat) required for heating and to maintain the proposed temperature, an analytical solution was obtained using Eq. (1) to Eq. (4). The data and results are listed in Table 3. SimScale software was used to confirm the analytical solution and verify the temperature field distribution via finite element analysis. From the thermal model, a temperature variation of 200 ± 5 ºC was obtained (Fig. 2). In both cases, the heat source was considered on the bottom surface of the workpiece, the sides used for clamping were considered thermally isolated, and the remaining surfaces loosed energy via convection (q_conv) and radiation (q_rad) heat fluxes. The emissivity value (ε) was determined experimentally using the temperature measured on the surface with a K-type thermocouple and verified using an Electrophysics® EZ THERM thermograph. The obtained value aligns with literature data for polished metallic surfaces [23].

Table 3. Data and values obtained in the heat transfer analysis.

Variable	Description	Value	Unit
${A_{conv}}$	Surface area for convection	2.7 x 10^− 3	m²
${A_{rad}}$	Surface area for radiation	2.7 x 10^− 3	m²
	Surface area for heating	2.1 x 10^− 3	m²
$\overline {h}$	Average heat transfer coefficient (convection)	6	W/(m²⋅K)
$\sigma$	Stefan-Boltzmann constant	5.67 x 10^− 8	W/(m²⋅K⁴)
$\varepsilon$	Emissivity	0.25	-
${T_S}$	Workpiece surface temperature	200 (473)	°C (K)
${T_\infty }$	Ambient temperature	25 (298)	°C (K)
${q_{conv}}$	Heat loss due to convection	2.84	W
${q_{rad}}$	Heat loss due to radiation	1.61	W
${q_{heat}}$	Heat input to the workpiece	4.45	W
	Heat flux from the heat source	2120	W/m²

The surface temperature was monitored using the thermograph throughout the experiment to validate the previously calculated results and ensure the steady-state temperature of the workpiece. Figure 3 shows the thermography images obtained before and during machining, where "S" specifies the temperature value (in °C) of the center spot, and "E" is the emissivity value (0.25).

The acquisition of force signals in the orthogonal directions (F_x, F_y, F_z) was performed in each run using a Kistler^® 9272 piezoelectric dynamometer. The acquired analog signals were conditioned using a Kistler^® 5070A charge amplifier and collected via a Measurement Computing^® PCIM-DAS 1602/16 DAQ board installed on a dedicated computer. Finally, the data were processed using the LabVIEW™ 9.0 software. The data acquisition rate used was 1.0 kHz. To determine the resultant force values (F_Ri) using Eq. (5), a sample of N = 2000 points collected in the stable machined surface was considered, that is, excluding the entry and exit of the tool from the workpiece. The machining force ($\:{\text{F}}_{\text{U}}$) was obtained from the arithmetic mean of the calculated values (Eq. 6).

$${F_{Ri}}=\sqrt {F_{{xi}}^{2}+F_{{yi}}^{2}+F_{{zi}}^{2}}$$

5

$${F_U}=\frac{{\sum\nolimits_{{i=1}}^{N} {{F_{Ri}}} }}{N}$$

6

Images of tool wear and failure were collected for each set of three runs using a Dino-Lite^® AM413-ZT digital microscope assisted by DinoCapture^® 2.0 software. Besides, the tool-wear mechanism analyses were performed via a Carl Zeiss AG EVO® 50 scanning electron microscope (SEM) at the end of the 15 runs. The SEM was operated at voltages ranging from 0.2 to 30 kV, with a resolution of 3 nm in the 30 kV condition.

The surface roughness parameters (R_a, R_z, and R_t) were measured after TAM using a Mitutoyo^® SJ-201P stylus profilometer with a resolution of 0.01 µm. A 0.8-mm sampling length and 4.0-mm evaluation length were set according to DIN EN ISO 4288 for values of 0.1 < R_a ≤ 2.0 µm and 0.5 < R_z ≤ 10 µm. Five measurements were performed on a stable machined surface (as cited above) for each sample. Moreover, SEM images of the machined surface were also captured using the Carl Zeiss AG EVO® 50.

The results from the present study (machining forces, tool wear, and surface finishes) considering workpiece heating at 200 ± 10°C during the end milling of SASS 254 SMO were compared with the findings obtained by Passari et al. [24], who investigated this machining at room temperature (dry cutting) and with commercial nanofluid in minimum quantity lubrication (NMQL) using the same cutting conditions.

3.1 Machining Force

Figure 4 graphically shows the machining force (F_U) values for the 15 runs performed in TAM compared with those under dry and NMQL conditions [24]. The relationship between F_U and the cutting parameters in the heated condition followed the pattern observed in this previous study, in which variations in the axial depth of cut (a_p) and feed per tooth (f_z) strongly influenced the force variation. In contrast, the variation in the cutting speed (v_c) had little effect on the results. Analogous results were observed by Alabdullah [25] during the machinability analysis of AL-6XN steel in flood machining. Comparatively, the F_U values for the TAM were similar to those presented by NMQL milling, highlighted as the lubri-cooling condition that generated the lowest machining forces compared to dry and flood milling [24].

On average, forces in TAM were 18.4% lower than those in dry cutting and similar to those in NMQL machining (a reduction of 19.3%). Maintaining low F_U values in heat-assisted end milling, even without lubri-cooling effects, indicates that thermal softening of the material is achieved with an increase in temperature, facilitating chip deformation and reducing the work-hardening tendency [15] [20] [26]. Additionally, the TAM and NMQL conditions showed good stability in F_U values over the 15 runs (the average values were 210 N and 208 N, respectively), unlike the dry condition (average value of 257 N), in which the average values were 182 N until run 9 and 370 N from run 10. This force value significantly increases in dry cutting owing to previous tool failure. At the end of the test, run 15 displayed a difference in F_U value of 44% between the conditions at room temperature (dry cutting) and with heating at 200°C (TAM). This variation is similar to that obtained by Teja et al. [19] when machining EN24 hardened steel at 400°C, where the reduction in force due to heating was 46%. The authors also observed that this difference increased with increasing a_p, similar to that recorded in Fig. 4 between runs 1 to 5.

3.2 Tool Failures

The differences in machining force values are associated with cutting tool failures, as evidenced by the increased tool life in TAM compared to dry cutting, where the workpiece temperature is lower than TAM, and the same level of thermal softening does not occur. Figure 5 shows the flank wear (VB) values collected after every three runs performed in heat-assisted end milling compared to those obtained in dry and NMQL machining [24].

It was observed that TAM performed similarly to NMQL until run 12. Passari et al. [24] highlighted that NMQL is the best lubri-cooling condition for enhancing tool life compared to dry and flood milling. However, the measurement taken at run 15 showed an increase of 265% in the VB value (above 0.3 mm). According to Karabulut et al. [20], the lack of lubrication in TAM facilitates the growth of wear mechanisms, mainly adhesion and abrasion. In addition, between runs 13 and 15, the cutting speed increased from 100 to 140 m/min. These factors may have increased the tool failure after the 12th run. Even so, such effects were minimized under NMQL because nanofluid application reduces the friction coefficient and the actions of wear mechanisms, thus extending tool life.

Scanning electron microscopy (SEM) analysis helped to understand the tool wear mechanisms. In the TAM, after the 15th run (Fig. 6), the cutting tool showed high flank wear (FW) and chipping, which possibly accelerated during run 15, given the maintenance of the machining forces (Fig. 4).

A large quantity of adhered material was also observed on the rake face of the tool. According to Alabdullah et al. [12], super-austenitic stainless steels exhibit high ductility and a tendency for work hardening. Heating the workpiece helped with thermal softening, which, combined with the high cutting speed of run 15 (v_c = 140 m/min), resulted in an extensive material adhesion to the tool. This process induced the formation of BUE during machining. Consequently, the adhered material caused damage when pulled out from the tool, resulting in chipping that caused failure. These findings are in line with the conclusions obtained by Polishetty et al. [27] because even in the flood lubri-cooling condition, the authors noted the presence of BUE in runs with high cutting speed (v_c = 150 m/min) during the milling of AL6XN steel.

Analysis of the secondary cutting edge of the tool (Fig. 7) shows the presence of adhered materials and microchippings. These minor fractures were caused by the removal of the adhered material during friction between the tool and the side walls of the end-milled surface [28]. Both phenomena show that despite improving the tool life compared to dry milling, TAM needs to be applied in a controlled range of cutting parameters to be effective.

3.3 Surface Roughness and Texture

Figure 8 illustrates the average roughness (R_a) values measured for the 15 samples generated by TAM compared with dry and NMQL machining [24]. The results show that the TAM resulted in machined surfaces with higher roughness values and a larger dispersion of values. Moreover, the cutting parameters had little influence on the R_a values. Considering the mean values measured for the 15 samples, NMQL milling produced the best results (grade N5), whereas dry machining and TAM generated R_a values corresponding to grade N6 [29].

The values of the mean roughness depth (R_z) and maximum peak-to-valley height (R_t) followed the behavior shown by R_a in the TAM process, maintaining the ratio observed in previous studies under all lubri-cooling conditions (R_z/R_a ≈ 6 and R_t/R_a ≈ 8). Table 4 summarizes the R_a, R_z, and R_t values (mean and standard deviation) under TAM, dry, and NMQL conditions. In general, TAM exhibited the highest roughness values compared to the others. However, NMQL is the best strategy for surface finishing because of its lubricating effect, which reduces the friction coefficient during the machining process.

Table 4

Summary of the average roughness values measured on the 15 runs
Parameter	Dry	NMQL	TAM
R_a (µm)	0.44 ± 0.09	0.33 ± 0.04	0.58 ± 0.10
R_z (µm)	2.77 ± 0.61	2.07 ± 0.22	3.52 ± 0.53
R_t (µm)	3.49 ± 0.96	2.64 ± 0.51	4.81 ± 1.28

The SEM analysis elucidated the greater surface roughness produced by heat-assisted end milling than in dry and NMQL machining. The SEM image of sample 5 (Fig. 9a) shows several fragments (chip debris) of diverse sizes adhering to the surface. These fragments result from chip forming and adhering to the tool edge, forming BUE, which breaks into tiny particles deposited on the workpiece surface during machining (Fig. 9b). A similar phenomenon was observed by Li et al. [30] when milling Ti-6Al-4V titanium alloy; the authors observed various chip debris on the machined surface, mainly because of the high cutting speed and consequent increase in temperature.

The presence of adhered materials on the machined surface of SASS 254 SMO was also observed by Passari et al. [24] during dry machining because the absence of lubrication intensified BUE formation. However, at room temperature, the presence of debris was low and did not significantly affect the roughness of the machined surface. Ahmed and Mulapeer [13] concluded that increasing the temperature in SASS reduces hardness and mechanical strength and increases plastic deformation, which facilitates the adhesion of workpiece material to the cutting tool compared to room temperature.

The SEM image of sample 5 at a higher magnification (Fig. 10) also exhibits smearing and side flows. According to Sarıkayaa et al. [31], surface defects such as grooves, scratches, chip debris, cracks, smearing/side flow, cavities, tearing, plucking, adhered materials, and surface burning are caused by excessive temperatures and irregularities of the tool edges owing to failures that occur during the machining of superalloys. The authors also mentioned that smearing occurs because of excessive plastic deformation induced by the side flow of a workpiece under the clamping motion between the tool clearance face and the machined surface during the tool movement along the feed direction. Therefore, the presence of these defects indicates that despite the advantages of TAM in reducing machining forces and tool wear, excessive temperature can be harmful in fine-surface finishes.

This study investigated the effect of thermally assisted machining (TAM) on the end milling of 254 SMO super austenitic stainless steel approaching machining forces, tool failures, and workpiece surface finish. A comparison with previous results in dry and NMQL milling helped to analyze the controlled heating effects. Thus, the main conclusions obtained are as follows:

Controlled heating at 200°C in SASS milling enabled the thermal softening of 254 SMO steel, reducing the machining forces with increasing axial depth of cut compared to dry milling at room temperature. On average, the forces in TAM were 18.4% lower than those in dry machining and similar to those in NMQL machining (a reduction of 19.3%).
The significant reduction in force values during the heat-assisted end milling at the end of the 15th run is an outcome of the higher tool integrity, which showed a larger failure only after the 12th run. In contrast, failure occurred after the 9th run in dry machining.
The wear behavior of the tool in the TAM until its failure was similar to that presented for NMQL machining, which was identified as the best lubri-cooling condition in the previous study. However, the higher cutting speed in run 15 favored quicker failure in the TAM.
The increased cutting speed in TAM contributed to material softening and BUE formation, intensifying adhesive and abrasion wear on the cutting tool. These wear mechanisms may have caused tool chipping because of the removal of the adhered material.
The roughness values resulting from TAM were slightly higher than those generated by dry and NMQL milling because the SEM images showed various chip debris adhered to the machined surface due to fragments of BUE. Smearing and side flow were also observed in the analysis, indicating excessive plastic deformation owing to temperature.
Finally, the TAM application can be beneficial in the semi-finishing machining of SASS, in which a suitable material removal rate is required without prioritizing fine finishing. As a proposal, hybrid machining (TAM + NMQL) could be an effective solution to achieve the best process performance.

Acknowledgements

The authors thank M.Sc. Abdiel M. Vilanova for the donation of SASS, Liess Co. for the workpiece preparation, Walter Tools Co. for the donation of cutting tools, BR-Sul Microscopy and Microanalysis Center for the SEM images, SimScale for the academic license for thermal simulation, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Grant No. 88887.840963/2023-00) for a student scholarship, and the Federal Institute of Santa Catarina (Process No. 23292.030882/2022-26) for granting leaves for study.

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Investigation of Thermally Assisted End Milling of 254 SMO Super Austenitic Stainless Steel

Status:

Version 1

Abstract

Figures

1 INTRODUCTION

2 MATERIALS and METHODS

3 RESULTS and DISCUSSIONS

3.1 Machining Force

3.2 Tool Failures

3.3 Surface Roughness and Texture

4 CONCLUSIONS

Declarations

Acknowledgements

References

Status:

Version 1

Variable	Description	Value	Unit
\({A_{conv}}\)	Surface area for convection	2.7 x 10^− 3	m²
\({A_{rad}}\)	Surface area for radiation	2.7 x 10^− 3	m²
	Surface area for heating	2.1 x 10^− 3	m²
\(\overline {h}\)	Average heat transfer coefficient (convection)	6	W/(m²⋅K)
\(\sigma\)	Stefan-Boltzmann constant	5.67 x 10^− 8	W/(m²⋅K⁴)
\(\varepsilon\)	Emissivity	0.25	-
\({T_S}\)	Workpiece surface temperature	200 (473)	°C (K)
\({T_\infty }\)	Ambient temperature	25 (298)	°C (K)
\({q_{conv}}\)	Heat loss due to convection	2.84	W
\({q_{rad}}\)	Heat loss due to radiation	1.61	W
\({q_{heat}}\)	Heat input to the workpiece	4.45	W
	Heat flux from the heat source	2120	W/m²