Cutting Temperatures in End Milling of Compacted Graphite Irons

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46th SME North American Manufacturing Research Conference, NAMRC 46, Texas, USA 46th SME North American Manufacturing Research Conference, NAMRC 46, Texas, USA

Cutting Temperatures in End Milling of Compacted Graphite Irons Cutting Temperatures in End Milling of Compacted Graphite Irons a a Manufacturing Engineering Conference MESIC June Leonardo Rosa Ribeiro daSociety SilvaaaInternational *, Antonio Favero Filho2017, , Eder Silva 2017, Costa28-30 , David a a 2017, Vigo (Pontevedra), Spain Leonardo Rosa Ribeiroada Silva *, Antonio Favero Filho , Eder Silva a bc Costa , David

Fernando Marcucci Picoa, Wisley Falco Salesa, Wilson Luiz Guesserbc, Alisson Rocha Fernando Marcucci Pico , Wisley Falco Sales , Wilson Luiz Guesser , Alisson Rocha Machadoad Costing models for capacity optimization in Industry 4.0: Trade-off Machadoad

between used capacity and operational efficiency

Federal Universisty of Uberlândia, Avenue. João Naves de Ávila, 2121 - Santa Mônica, Uberlândia, 38408-100, Brazil b Federal Universisty of Uberlândia, Avenue. JoãoSchmidt, Naves de3400, Ávila,Joinville, 2121 - Santa Mônica,Brazil Uberlândia, 38408-100, Brazil TUPY S.A., R. Albano 89227-901, b c TUPY S.A., R.UDESC, Albano Santa Schmidt, 3400, Joinville, 89227-901, BrazilSC 89223-100, Brasil Center of Technological Sciences, Catarina State University, Joinville, a UDESC, Santa Catarina a,* b b dc Center of Technological Sciences, Joinville, SC 89223-100, Pontifical Catholic University of Paraná, Imac. Conceição, State 1155 University, - Prado Velho, Curitiba, 80215-901, Brasil Brazil d Pontifical Catholic University of Paraná, Imac. Conceição, 1155 - Prado Velho, Curitiba, 80215-901, Brazil a University of Minho, 4800-058 Guimarães, Portugal b Unochapecó, 89809-000 Chapecó, SC, Brazil * Corresponding author. Tel.: +55 34 99151-1062. * Corresponding Tel.: +55 34 99151-1062. E-mail address:author. [email protected] E-mail address: [email protected] a a

A. Santana , P. Afonso , A. Zanin , R. Wernke

Abstract Abstract Abstract Under the concept of "Industry 4.0", production processes will be pushed to be increasingly interconnected, With the increasing fortime greater fueland, efficiency, automotive companies urge to develop and more efficient engines. In information based demand on a real basis necessarily, much more efficient. In this new context, capacity optimization With the increasing demand for greater fuel automotive companies urge for toengines develop and more engines. In orderbeyond to withstand the high compression ratesefficiency, and temperatures atcontributing which these super arenew subjected to, efficient vermicular cast iron goes the traditional aim of capacity maximization, also organization’s profitability and value. order to withstand the high compression rates and temperatures at which these super engines are subjected to, vermicular cast iron or compacted graphite iron (CGI) has been identified as the most suitable material to replace gray cast iron (LCI) in the production Indeed, lean management and continuous improvement approaches suggest capacity optimization instead of or graphite iron (CGI) has However, been identified as the graphite most suitable material to replace gray cast iron (LCI)when in thecompared production of compacted engine blocks and cylinder compacted iron needs different machining conditions to maximization. The study ofheads. capacity optimization and costing models is an important research topic that deserves of engine blocks and cylinder heads. compacted graphiteinvolved iron needs different machining when compared to gray cast iron, therefore studies of theHowever, various output parameters in the machining of thisconditions material are important. This contributions from bothstudies the practical and theoretical perspectives. This paper presents and discussesarea important. mathematical gray cast iron,the therefore the various output parameters involved in the this material paper studies influence of theof cutting conditions (cutting speed and feed rate) onmachining the averageofmachining temperature near toThis the model for capacity management based on different costing models (ABC and TDABC). A generic model near has been paper the influence of the cutting conditions speedprocess and feed the average to the cuttingstudies zone using an infrared thermal camera in the(cutting end milling of rate) high on strength CGIs. machining The surfacetemperature roughness and power developed and it was used to analyze idle capacity and to design strategies towards the maximization of organization’s cutting zone using an infrared thermal in the end process of has higha strength CGIs. The surface roughness andaverage power consumption were also monitored. The camera results showed thatmilling the cutting speed greater influence than the feed rate on the value. trade-off capacity vs operational efficiency highlighted and it is feed shown that capacity consumption were also monitored. The that the cutting speed aisgreater influence than rateThe on the average cutting The temperature, mainly due tomaximization the results higher showed energy provided to the systemhas when the cutting speed isthe increased. increase in optimization might hide operational inefficiency. cutting temperature, mainly due to the higher energy provided to the system when the cutting speed is increased. The increase in the feed rate generates more heat and greater temperature variability in the cutting zone, since the thicker chip sizes have more © 2017 Published by Elsevier B.V. the feedThe rate generates more heat and greater temperature in thethat cutting zone, since the thickerhad chipmore sizesinfluence have more influence in Authors. the heat dissipation from the cutting zone. It isvariability also observed the material characteristics in Peer-review responsibility of thethe scientific of the Manufacturing Society International influence in under the of heat from the cuttingcommittee zone.than It isthe also observed that theEngineering material characteristics had moreConference influence in the temperature thedissipation regions near to cutting zone machining parameters. 2017. the temperature of the regions near to the cutting zone than the machining parameters. © 2018 The Authors. Published by Elsevier B.V. © 2018 The Authors. Published by Elsevier B.V. Keywords: Cost Models; ABC; TDABC; Capacity Management; IdleofCapacity; Operational Efficiency © 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility ofthe the scientific committee NAMRI/SME. Peer-review under responsibility of scientific committee of the 46th SME North American Manufacturing Research Conference. Peer-review under responsibility of the scientific committee of NAMRI/SME. Keywords: End Milling; Compacted Graphite Iron; Cutting Power Measurement; Cutting Zone Temperature Measurement; 1. Introduction Keywords: End Milling; Compacted Graphite Iron; Cutting Power Measurement; Cutting Zone Temperature Measurement;

The cost of idle capacity is a fundamental information for companies and their management of extreme importance in modern©production systems. In general, it isB.V. defined as unused capacity or production potential and can be measured 2351-9789 2018 The Authors. Published by Elsevier 2351-9789 2018responsibility The Authors. Published by Elsevier B.V.hours Peer-review of the scientific committee of NAMRI/SME. in several©under ways: tons of production, available of manufacturing, etc. The management of the idle capacity Peer-review underTel.: responsibility the761; scientific committee NAMRI/SME. * Paulo Afonso. +351 253 of 510 fax: +351 253 604of741 E-mail address: [email protected]

2351-9789 © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the Manufacturing Engineering Society International Conference 2017. 2351-9789 © 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 46th SME North American Manufacturing Research Conference. 10.1016/j.promfg.2018.07.056

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1. Introduction Although both spheroidal (SGI) and vermicular (CGI) cast irons were simultaneously invented in 1948 and patented in 1949, it is remarkable that the discovery of CGI occurred by accident, during the invention of the SGI, even though vermicular cast iron was initially considered a degraded form of the spheroidal cast iron [1, 2]. Although efforts were made before the 80's to improve CGI mass production techniques [1, 3, 4], it can be considered that only starting from the 90's this production reached a considerable level when compared to the lamellar or gray cast iron (LCI), mainly driven by the production of supercharged diesel or gasoline engine blocks in Europe [2, 5-8]. Due to its characteristics, the main fields of application of the CGI are projects in which are required materials with superior mechanical properties to that of the LCI and also superior heat/vibrations dissipation to the SGI [2]. When compared to both LCI and aluminum alloys, the CGI properties leads to improvements in the project of relatively heavy parts of the powertrain, like the cylinder block and head, in aspects like downsizing and peak pressure capacity [2, 6, 7] as well as wear resistance [5, 9-11]. Optimization of these features are usually associated with gains in energy efficiency and reduction of emission of pollutants in internal combustion engines [12-17]. Advances were made in the use of the CGI for making components subjected to the intensive wear and/or thermal fatigue such as exhaustion manifolds [18] and brake elements [18, 19]. The measurement of the resulting temperature in the cutting zone during the milling process is a difficult task. Factors such as the milling being a interrupted cutting operation, the mobility of the zone affected by the heat promoted by feed rate of the process and the presence of chips are the main obstacles to the accuracy of these measurements [20]. The most commonly used tools for measuring temperature in this operation are thermocouples, especially type K, [21, 22], detection of emitted infrared radiation [23-27] or a combination of both techniques [28, 29]. This paper aims to investigate the behavior of the temperature near to the cutting zone during end milling process of three different types of compacted graphite

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iron, with different hardness and graphite shape (nodularity). In this study, the cutting speed and the feed rate were varied. The cutting temperatures were determined using a thermal camera, to which the calibration was verified using T-type thermocouples. The cutting temperatures were correlated with the power required to machine, determined by booth Hall sensors and a piezoelectric dynamometer. The surface roughness was also monitored during the experiments. Nomenclature ap AWJM BUE CGI ºC f Fr HB i(t) kgf kHz LCI Pc Ra SGI T v(i) Vb ve ε η σ

Depth of the Cut (mm) Abrasive Water Jet Machining Built-up Edge Vermicular or Compact Graphite Cast Iron Celsius Degrees Feed Rate (mm/rev) Resulting Cutting Force (N) Hardness Brinell Instantaneous Electric Current (A) kilogram-force kilo Hertz Lamellar or Gray Cast Iron Cutting Power (W) Average Roughness Spheroidal Cast Iron Time (s) Instantaneous Electric Voltage (V) Maximum Flank Wear (mm) Effective Cutting Speed (m/min) Emissivity Machine Efficiency Standard Deviantion

2. Materials and Methods Three workpieces of different Compacted Graphite Iron microstructures were evaluated. CGI-A is the Standard material of grade 450, CGI-B has a slightly higher graphite nodularity and higher hardness, while CGI-C was alloyed with molybdenum and also present higher nodularity and higher hardness. The three materials have chemical composition with 4.2% of carbon equivalent (C+Si/3+P/3), 0,9%Cu and 0,07%Sn, while CGI-C was alloyed with 0,1%Mo.

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They show fully pearlitic matrices, having the CGI-A larger graphite particles when compared to both CGIB and CGI-C, as shown in the Fig. 1. CGI-C also show small Mo-carbide particles. The Brinell hardness and nodularity for each material are respectively illustrated, according to ISO 945 [30] and ISO 16112 [31], in the Fig. 2.

(produced by abrasive water jet machining - AWJM), thus preventing that the position of the test relative to the rest of the specimen could influence the results. The track in red represent the area that was machined in each cutting condition used.

Fig. 2. Metallurgical properties of the CGIs. Fig. 1. Microstructures of the materials used in this paper. The right pictures are higher magnification etched samples (Nital 2% for 30 seconds).

The lower values of nodularity and Brinell hardness were found for CGI-A, followed by CGI-B and CGIC. The correspondence between these variables can be explained by the fact that higher nodularities leads to lower stress concentrations in the matrix, thus increasing the Brinell macrohardness, which was measured with a load of 187.5 kgf using a 5 mm tungsten carbide sphere. One problem encountered when doing experimental temperature tests is the fact that tests carried out in the borders of the workpieces have different mass contours as compared to the mid of the workpiece, which may influence the results. In order to avoid this, the workpieces of the three CGIs were sectioned as shown in Fig. 3, so that each test region has a surface area of 30 mm of width and 40 mm of length. Each section is separated from its neighbor by a void channel of 2 mm of thickness and 30 mm long

Fig. 3. Representation of a workpiece used in the end milling tests. Dimensions in millimeters.

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T-type thermocouples were fixed at approximately 6 mm of the cutting zone for one test at each cutting condition, as shown by red circles in the Fig. 4. These thermocouples allowed verification of the accuracy of the temperatures obtained by the thermographic camera. The thermocouples were properly calibrated at temperatures between 20 and 70 °C, using a digital thermostatic bath model MQBTC A-100, manufactured by Microquímica® Equipamentos LTDA, with resolution of 0.1 °C and stability of 0.01 °C.

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6211 acquisition board, and the power being calculated by Eq. 2. Prior to the tests, the power required for rotating the tool and feed movement was measured, without machining (axes running freely). This value was subtracted from the power found during machining, the resulting value being the effective machining power. 𝑃𝑃𝑐𝑐 =

𝑃𝑃𝑐𝑐 =

𝐹𝐹𝑟𝑟 𝑣𝑣𝑒𝑒 60ƞ

(𝑊𝑊)

1 𝑇𝑇 ∫ 𝑇𝑇 0

𝑖𝑖(𝑡𝑡). 𝑣𝑣(𝑡𝑡) 𝑑𝑑𝑑𝑑

(1) (2)

Fig. 4. Workpiece with welded thermocouples.

Fig. 5. Setup of the sensors, workpiece and tool used in the machining tests.

The machining tests were carried out in a ROMI – Bridgeport Discovery® 720 CNC machining center. The machining test setup are shown in Fig. 5. In order to measure the machining forces used to calculate the cutting power in each tested condition, the workpiece was fixed on a Kistler® platform, model 9265B, by two M12 screws in the points indicated by the blue circles of Fig. 3. The cutting power was calculated using the measured machining forces, according to Eq. 1. The resulting force acting on the X, Y and Z axes was used as the machining force. The forces on the X and Y axes are generated by the cut and feed actions on the workpiece. The force on the Z axis comes from the elastic recovery of the work material pushing the tool. The cutting power was also determined by Hall current and voltage sensors located at the power inlet cable of the machining center, being the voltage and current acquired at a rate of 60 kHz using a NI USB-

The thermocouples were connected to the same data acquisition system previously used to calibrate them, being the temperature acquired at a rate of 10 samples per second. The infrared thermographic camera used was a FLIR Tools® model A325, which has a resolution of 320 x 240 pixels, a measuring range from 0 to 350 ºC with an accuracy of ± 2 °C. The thermal images were acquired at a rate of 30 frames per second. After the tests, each frame was converted into an array and, using an algorithm made in MATLAB®, the maximum temperature was identified, allowing the average of these maximum temperatures in the cut region during the entire machining process be calculated. The closer to the source of heat generation zone, the temperature gradient of the interface between the cutting region and the material falls at a higher rate [32]. This explains why the temperature measurements using thermal cameras tend to present

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lower temperature values to the interface tool/chip/workpiece than those measured by punctual methods such as the tool/workpiece thermocouple [33-35]. Each pixel in fact measures an area with a temperature gradient, showing an average of these temperatures. Therefore, we can conclude that the accuracy of the pixel temperature compared to the real values rapidly increases in the regions adjacent to the cutting zone. The thermal images are shown to be effective to show how the regions surrounding the cutting zone heat up, since the excessive heating of these zones can lead to metallurgical changes of the material, as well as this heating is a valuable indicator of the machinability of the material for the given cut condition used. Before the tests the specimen was painted with a matte black paint (Fig. 4) to reduce reflectivity and allowing the emissivity of the workpiece to be adjusted at ε = 0.95 [36]. The camera was fixed at the left of the workpiece on the worktable of the machining center, in a way that the relative distance between the camera and the specimen were kept constant in 400 mm, thus avoiding any focal loss. The tools used were integral tungsten carbide end milling cutters coated with TiAlN supplied by Walter Tools®, with specification H3023018-10. They have 10 mm of diameter and four cutting edges. A depth of cut (ap) of 1 mm and a cutting width (ae) of 10 mm (full tool diameter) were used for all the tests, being varied the cutting speed (vc) and the feed rate (f) according to Tab. 1. A test and two replicas were conducted, summing up 3 repetitions for each test condition. In order to minimize the influence of the parameters related to wear of the cutting edge, the tools were always changed before the average flank wear (VB) reached 0.05 mm, thus avoiding the influence of the tool wear on the results. At the end of the tests, the surface roughness was measured using a Taylor Hobson® contact profilometer, model S100, having a diamond stylus with a tip radius of 0.2 µm. Three measurements were performed for each test, with a sampling length of 25.6 mm, totaling nine measurements for each machining condition. After the raw data were collected, the profiles were linearized and a Gaussian filter of 0.8 µm was applied, only then being calculated the mean square roughness (Ra).

Table. 1. Machining parameters. Condition

vc (m/min)

f (mm/rev)

1

120

0.1

2

120

0.2

3

240

0.1

3. Results and discussions 3.1. Validation of the infrared thermographic camera emissivity calibration using T-type thermocouples The results of the temperature measurements from the thermocouple and the analogue region in the thermographic camera for the tested conditions are shown in Fig. 6. For all the conditions, the temperature of the thermographic camera and the thermocouples showed an adjustment greater than 90%, indicating that the emissivity was correctly input, thus allowing a reliability in the accuracy of the temperatures measured in the other regions.

Fig. 6. Comparison of temperature given by the thermocouples and the infrared thermographic camera.

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3.2. Measurement of the machining power using the dynamometer and Hall sensors The cutting powers given by Eq. 1 and Eq. 2 for each cutting condition and the three CGI grades are displayed in Fig. 7 and Fig. 8 respectively, for a confidence interval of ± 2σ. A good agreement between the power measurement systems is observed, with the values measured by both sensors within the standard deviation of their analogue. As theoretically expected, both the increase in the feed rate and in the cutting speed resulted in an increase in cutting power. It is noted, however, that since most of the useful power is required by the spindle, the increase in the cutting speed is more effective than an increase in feed rate [37].

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The results of the power consumption obtained during machining the three CGI grades at the same cutting condition, followed the same order of their hardness and nodularity, that is the highest power was for machining the CGI-C grade, followed by the CGI-B and finally by the CGI-A. Increasing nodularity and mainly increasing hardness were the reasons for the highest power consumption. 3.3. Surface roughness The average values of the surface roughness (Ra) obtained in each cutting condition tested are shown in Fig. 9, for a confidence interval of ± 2σ. For all the work materials tested, the Condition 2 presented the highest values of Ra because of the higher feed rate (double) employed. Theoretical value of Ra is directly related to the square of the feed rate [37, 38] what fully explains these results. On the top of this, augmenting the feed rate, the cutting forces also increase, leading to more vibration and poorer surface roughness [37, 38]. The increase in the cutting speed allowed condition 3 to have a lower Ra value than condition 1. This can be explained by the fact that higher cutting speed results in higher heating of the cutting zone and consequently reduction of machining forces, thus reducing the mechanical resistance to the cut and improving the surface finish.

Fig. 7. Cutting power measured using a dynamometer. The numbers 1, 2 and 3 after the material codes indicate the machining conditions according to Table 1.

Fig. 9. Average Ra values for each cutting condition tested.

Fig. 8. Cutting power measured using Hall sensors.

Although BUE is usually detected when machining cast irons under low cutting speeds [37, 38], it is very unlikely that this phenomenon is

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present under the cutting condition used here (120 and 240 mm/min). Therefore, the behavior of the surface roughness is mostly related to the effect of the cutting speed on the cutting forces. The tests performed with the CGI-A presented higher Ra values than their counterparts when comparing at the same cutting conditions. This can be explained by the larger free graphites of this material in comparison to the other two (Fig. 1), which results in more structural embrittlement, since a bigger percentage of the matrix is subject to some abrupt discontinuities, and consequently, to additional stress concentration. During machining a more abrupt and unstable chip detachment is observed, leading to a lower surface finish quality. The increased toughness of the material that came from higher nodularity is probably the responsible for the similar results of Ra when machining the CGI-B and the CGI-C. As the graphites worms are more finely scattered in the matrix of the CGI-B and CGIC, the stress concentrations from the interfaces between the pearlite and the graphite are attenuated when compared to the CGI-A. This results in a more continuous value of cutting forces, as well as a more stable chip detachment, thus explaining the lower roughness of the CGI-B and CGI-C relative to CGI-A. Although the presence of carbides in the CGI-C increased the cutting forces, the high dispersion of those carbides in the matrix causes them to have little influence on the roughness. 3.4. Temperatures near to the cutting zone The average temperatures values near to the cutting zone are shown in Fig. 10, for a confidence interval of ± 2σ. The temperature maps for the frame with the maximum temperature when machining under the three different cutting conditions tested for the CGI-A, CGI-B and CGI-C are shown in Figs. 11 to 13, respectively. The effect of the cutting speed and feed rate on the cutting temperature follows a trend similar to that of the cutting power (Fig. 7 and Fig. 8), that is, when increasing them the cutting temperatures also increased. This was expected since more mechanical energy will be converted into heat. When machining under the highest feed rate of 0.2 mm/rev (condition 2) higher standard deviations of the average temperatures are observed. This can be explained by

the thicker chips generated, which dissipate more heat from the system, as shown by the condition 2 in Figs.11.2, 12.2 and 13.2), thus causing the temperature in the cutting region to oscillate more. The increase in the cutting speed resulted in higher machining temperatures due to the increased interactions between the tool and the workpiece, being this additional friction the driving force for the extra heating in relation to condition 1.

Fig. 10. Average maximum temperatures values near to the cutting zone during the cutting process.

The temperature in the cutting zone was much more sensitive to the changes in the material than the cutting power. Higher nodularity and higher macrohardness are probably the main factors, increasing the cutting forces, and as a consequence the maximum temperature. Higher nodularity results in increasing difficulties for chip breakage [39], and the consequences are higher forces and temperatures on the cutting tool. For CGI-C, alloyed with molybdenum, the presence of small carbides in the microstructure could contribute to increase the cutting power and the maximum temperature. The average maximum cutting temperature of the two CGI-B and CGI-C are higher than those obtained when machining the CGI-A, regardless the cutting condition used. This happened even in the conditions that required less cutting power. The CGI-C presented even higher machining temperatures than the CGI-B, probably due to the molybdenum carbides acting to increase even more the friction in the shear zones. Even though the thermal conductivity was not measured in the present work, it is known that thermal conductivity decreases with increasing nodularity [40], what helps to explain the increasing in the temperature with higher nodularity.

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Fig. 11. Frame containing the highest temperature peak for each of the three conditions investigated in the CGI-A.

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Fig. 12. Frame containing the highest temperature peak for each of the three conditions investigated in the CGI-B.

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4. Conclusions Regarding to the methodology of preparation of the workpieces used in the temperature tests it can be concluded that: The use of T-type thermocouples was effective in checking if the emissivity was correctly adjusted in the thermal camera.  The method of sectioning the workpiece was effective in isolating each test unit from its neighbors, making each condition equivalent to an isolated test surrounded only by the environment. The technical results presented in this paper can be summarized based on Fig. 14. This figure shows the percentage relation between the values of the cutting power, cutting temperature and surface roughness of the three CGI, with different microstructure. 

Fig. 14. Summary of the technical results.



 

Fig. 13. Frame containing the highest temperature peak for each of the three conditions investigated in the CGI-C



Increasing the hardness and nodularity results in increased cutting power and increased max average cutting temperature. The effect of the hardness seems to be more important than the effect of nodularity. Doubling the cutting speed had a greater influence in the temperature near to the cutting zone than doubling the feed rate. For all the materials tested, a greater oscillation in the temperature was observed under condition 2. This can be explained by the fact that the thicker chips were formed in this condition. The temperature was more sensitive to the change in the material than the cutting power. In comparison to CGI-A, the end milling of the CGIB and CGI-C presented, respectively, average

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



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maximum cutting temperatures 27% and 43% higher. No statistical differences were observed according to the Ra parameter between the CGIB and CGI-C for the machining conditions investigated. Both CGI-B and CGI-C showed Ra values around 20% lower than the CGI-A when machined in the same conditions. As expected, increasing the cutting speed improved the surface finish, and increasing the feed rate worsened the surface roughness.

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