The applications of TDLAS have extended to the various industrial fields. Besides the applications mentioned earlier, TDLAS can be applied for the environmental monitoring, plant safety, and so on. It has been demonstrated that the carbon isotopes of CO2 can be detected for the forest air monitoring using TDLAS. The highly reliable laser diodes with high power with a wide continuous single mode tuning range and low frequency drift are very necessary for TDLAS applications. Because of the small size of diode lasers, TDLAS can also be employed as a miniature sensor. It would not be an exaggeration to say that TDLAS at a NIR wavelength region has already had a high-quality finished form for the practical industrial applications.

On the other hand, there have been several challenges to advance the TDLAS applications in a MIR wavelength region. The fiber delivery system is the most notable and desired technology in this wavelength region. However, the silica-based fiber optics cannot be used in this wavelength region and there is no reliable and easy-to-use fiber delivery devise. The development of optical fiber delivery system will make TDLAS much more appealing to various industrial fields. The advancement of lasers and detectors in MIR region is also important to make the TDLAS system reliable and rugged. MIR lasers allow more sensitive detection, whereas the lasers with a broader tuning range make the multiple species detection with a single laser possible. It means that a future developed instrument of TDLAS might be able to selectively detect several different gases using a single laser, or to work as the universal, cost-effective spectrometers.

Other promising applications of TDLAS are 2D and 3D measurements using CT technology. TDLAS combined with CT shows a great potential for the fast and continuous imaging in a measurement area. 2D measurement has been proposed and applied for some industrial applications using CT-TDLAS, which should be further developed, especially 3D measurement. This technique is promising to clarify the basic phenomena in industrial processes and the monitoring and advanced controlling of the industrial systems. The development of fast CT algorisms and CT optical systems is inevitable together with an advanced measurement technology. The improved performance of TDLAS will also open up the new application fields. Simultaneously, the reduced costs of TDLAS system will substitute the conventional sensors by TDLAS-based sensors.

## **Author details**

Zhenzhen Wang1,2, Takahiro Kamimoto2 and Yoshihiro Deguchi1,2\*

\*Address all correspondence to<EMAIL_ADDRESS>
1 State Key Laboratory of Multiphase Flow in Power Engineering, Xi'an Jiaotong University, Xi'an, China

2 Graduate School of Advanced Technology and Science, Tokushima University, Tokushima, Japan

## **References**

**3. Challenges**

64 Temperature Sensing

The applications of TDLAS have extended to the various industrial fields. Besides the applications mentioned earlier, TDLAS can be applied for the environmental monitoring, plant

**Figure 16.** TDLAS product temperature calculation during a SMART freeze dryer run processing 5% (w/w) sucrose (3 mL fill volume/vial, 112 vials total load, 20 mL Wheaton). Symbols represent thick solid line = shelf inlet temperature,

empty circles = Tp-TDLAS, thin solid lines = Tb-TC/center (n = 5), filled diamonds = Tp-MTM [44].

the forest air monitoring using TDLAS. The highly reliable laser diodes with high power with a wide continuous single mode tuning range and low frequency drift are very necessary for TDLAS applications. Because of the small size of diode lasers, TDLAS can also be employed as a miniature sensor. It would not be an exaggeration to say that TDLAS at a NIR wavelength region has already had a high-quality finished form for the practical industrial applications.

can be detected for

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**Chapter 5**

**Provisional chapter**

factorial

**Temperature in Machining of Aluminum Alloys**

**Temperature in Machining of Aluminum Alloys**

DOI: 10.5772/intechopen.75943

The objective this work is to study the effect of the mechanical property of the workpiece (tensile strength) and cutting conditions (cutting speed, feed rate, depth of cut and lubricooling system) over the cutting temperature in turning of aluminum alloys. A 2k

planning was used to determine the machining test conditions. ANOVA and Regression Analysis of the results were performed. The main contribution of this work lies on its efficiency of describing the behavior of the cutting temperature as a function of the input variables. The results found in the present work have considered the interactions of the input variables, describing the cutting temperature in a complete way, not seen previously

**Keywords:** cutting temperature, aluminum alloys, factorial planning, machinability,

Machining of aluminum alloys is an important production activity in the automotive and aeronautical industries, due to the large application of aluminum in the transportation sector [1, 2]. This is because of its great versatility in terms of properties and, among them, its low density and high strength to weight ratio stand out, which makes aluminum, after iron, the materials most used in the manufacture of parts [3–5]. According to Davies et al. [6] the automotive industry is continuously developing technologies to reduce vehicle costs and weights; and with that, reducing the environmental impact with energy consumption. The pressure for reducing vehicle weights has led to the substitution of steel and cast iron for plastic and

> © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

Mário C. Santos, Alisson R. Machado and

Mário C. Santos, Alisson R. Machado and

Additional information is available at the end of the chapter

Marcos A.S. BarrozoAdditional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.75943

Marcos A.S. Barrozo

**Abstract**

in the literature.

aluminum to increase fuel economy [7].

modeling

**1. Introduction**

#### **Temperature in Machining of Aluminum Alloys Temperature in Machining of Aluminum Alloys**

DOI: 10.5772/intechopen.75943

Mário C. Santos, Alisson R. Machado and Marcos A.S. Barrozo Mário C. Santos, Alisson R. Machado and Marcos A.S. BarrozoAdditional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.75943

**Abstract**

The objective this work is to study the effect of the mechanical property of the workpiece (tensile strength) and cutting conditions (cutting speed, feed rate, depth of cut and lubricooling system) over the cutting temperature in turning of aluminum alloys. A 2k factorial planning was used to determine the machining test conditions. ANOVA and Regression Analysis of the results were performed. The main contribution of this work lies on its efficiency of describing the behavior of the cutting temperature as a function of the input variables. The results found in the present work have considered the interactions of the input variables, describing the cutting temperature in a complete way, not seen previously in the literature.

**Keywords:** cutting temperature, aluminum alloys, factorial planning, machinability, modeling

## **1. Introduction**

Machining of aluminum alloys is an important production activity in the automotive and aeronautical industries, due to the large application of aluminum in the transportation sector [1, 2]. This is because of its great versatility in terms of properties and, among them, its low density and high strength to weight ratio stand out, which makes aluminum, after iron, the materials most used in the manufacture of parts [3–5]. According to Davies et al. [6] the automotive industry is continuously developing technologies to reduce vehicle costs and weights; and with that, reducing the environmental impact with energy consumption. The pressure for reducing vehicle weights has led to the substitution of steel and cast iron for plastic and aluminum to increase fuel economy [7].

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Measuring the temperature in the cut region is a complex task due to the difficult access to that region. One of the methodologies that allows its more precise verification is the tool-workpiece thermocouple system, being able to study the variation of the cutting temperature (TC) as a function of many parameters, among them the mechanical strength of the machined alloy and cutting parameters: cutting speed (VC), depth of cut (AP), feed rate (F) and lubri-cooling condition (LUB). With this method, it is possible to determine the variables that most affect the cutting temperature in the secondary shear zone and also generate models to study its behavior.

in the plastic deformation/friction process in the tertiary shear zone (region where the newly formed surface of the workpiece contacts the clearance face of the tool) [11, 12]. According to Machado et al. [13], the tertiary shear zone is important mainly when using small clearance angles and/or a flank wear has developed, which tend to increase the workpiece-tool contact

Temperature in Machining of Aluminum Alloys http://dx.doi.org/10.5772/intechopen.75943 73

The heat generated in zones A and B are highly dependent on the cutting conditions and are assumed to be evenly distributed [11]. The portion of heat generated in zone C depends on the kinetic friction of the lower surface of the chip on the tool rake surface and can be assumed linearly decreasing from the end of the adhesion zone to the end of the slipping zone, where no heat is generated any more [11, 14–16]. The amount of heat generated in zone D depends on the clearance angle, flank wear and kinetic friction of the newly machined surface against

The energy balance relationship between the heat generated in zones A, B, C and D and the heat dissipated for chip, workpiece, environment and tool, allows the understanding of the

The greater part of the heat generated in zone A is dissipated by the chip, and the part dissipated by the workpiece represents a small portion, which tends to increase under low rates of material removal and at small shear angles, and to reduce at high rates of material removal [12, 13]. These authors make it clear that most of the heat generated in zone B (in the flow zone) goes to the chip and to the tool and because the latter is stationary, it develops high temperatures. The tool temperature is not directly affected by the heat generated in the primary shear zone, since

in the flank region. **Figure 1** shows the four heat generation zones (A, B, C and D).

the tool clearance surface [10, 11, 13].

**Figure 1.** Heat generation zones in machining [13].

energy exchanges involved in the cutting processes [13, 17].

This chapter will present the fundamentals of the cutting temperature in the machining of aluminum alloys with experimental approach using the tool-workpiece thermocouple system. The methodology that includes details of the collection of voltage signals will also be described. A 2k factorial planning is used, allowing the analysis of the influences of the input variables on the cutting temperature.

This work is justified due to the ability of the analysis of variance and factorial analysis to investigate the joint influence (simultaneous) of the mechanical strength and cutting conditions (input variables) on the cutting temperature. In machining, few researches have been conducted in this way, since most of them study the influences of the main input variable isolated and rarely considering their interactions in the way conducted here; for instance, the influence of the cutting speed or the feed rate on the cutting forces; the effect of the hardness on the cutting temperature [4, 8, 9]. This greatly limits the discussion about how interactions between inputs variables can affect the responses.

## **2. Cutting temperature measurement, regression analysis and mathematical modeling**

For a better understanding of the behavior of the cutting temperature in the machining of aluminum alloys, the theoretical fundaments will be presented first.

As for the process of temperature measurement in the cutting region, the focus will be on the tool workpiece thermocouple system, when concepts and adaptation of the thermocouple system in the turning process and measuring devices will be presented.

The cutting temperatures will be studied based on the 2k factorial design, where the input factors will be the mechanical strength of the ALLOYS and cutting parameters: cutting speed (VC), depth of cut (AP), feed rate (F) and lubri-cooling condition (LUB), whose effect on the cutting temperature will be presented based on analysis of variance and factorial effects.

## **2.1. Fundamentals of the temperature when machining aluminum alloys**

The chip formation process involves high deformation rates of the work material (elastoplastic), with almost all the deformation energy converted to heat in the cutting region [10]. This energy can be divided in: (A) – the work to shear the material in the primary shear zone; (B) – the energy needed to plastically deform the chip in the secondary shear zone; (C) – the work required to move the newly formed chip onto the rake surface and (D) – the work involved in the plastic deformation/friction process in the tertiary shear zone (region where the newly formed surface of the workpiece contacts the clearance face of the tool) [11, 12]. According to Machado et al. [13], the tertiary shear zone is important mainly when using small clearance angles and/or a flank wear has developed, which tend to increase the workpiece-tool contact in the flank region. **Figure 1** shows the four heat generation zones (A, B, C and D).

The heat generated in zones A and B are highly dependent on the cutting conditions and are assumed to be evenly distributed [11]. The portion of heat generated in zone C depends on the kinetic friction of the lower surface of the chip on the tool rake surface and can be assumed linearly decreasing from the end of the adhesion zone to the end of the slipping zone, where no heat is generated any more [11, 14–16]. The amount of heat generated in zone D depends on the clearance angle, flank wear and kinetic friction of the newly machined surface against the tool clearance surface [10, 11, 13].

The energy balance relationship between the heat generated in zones A, B, C and D and the heat dissipated for chip, workpiece, environment and tool, allows the understanding of the energy exchanges involved in the cutting processes [13, 17].

The greater part of the heat generated in zone A is dissipated by the chip, and the part dissipated by the workpiece represents a small portion, which tends to increase under low rates of material removal and at small shear angles, and to reduce at high rates of material removal [12, 13]. These authors make it clear that most of the heat generated in zone B (in the flow zone) goes to the chip and to the tool and because the latter is stationary, it develops high temperatures. The tool temperature is not directly affected by the heat generated in the primary shear zone, since

**Figure 1.** Heat generation zones in machining [13].

Measuring the temperature in the cut region is a complex task due to the difficult access to that region. One of the methodologies that allows its more precise verification is the tool-workpiece thermocouple system, being able to study the variation of the cutting temperature (TC) as a function of many parameters, among them the mechanical strength of the machined alloy and cutting parameters: cutting speed (VC), depth of cut (AP), feed rate (F) and lubri-cooling condition (LUB). With this method, it is possible to determine the variables that most affect the cutting temperature in the secondary shear zone and also generate models to study its behavior.

This chapter will present the fundamentals of the cutting temperature in the machining of aluminum alloys with experimental approach using the tool-workpiece thermocouple system. The methodology that includes details of the collection of voltage signals will also be

This work is justified due to the ability of the analysis of variance and factorial analysis to investigate the joint influence (simultaneous) of the mechanical strength and cutting conditions (input variables) on the cutting temperature. In machining, few researches have been conducted in this way, since most of them study the influences of the main input variable isolated and rarely considering their interactions in the way conducted here; for instance, the influence of the cutting speed or the feed rate on the cutting forces; the effect of the hardness on the cutting temperature [4, 8, 9]. This greatly limits the discussion about how interactions

For a better understanding of the behavior of the cutting temperature in the machining of

As for the process of temperature measurement in the cutting region, the focus will be on the tool workpiece thermocouple system, when concepts and adaptation of the thermocouple

factors will be the mechanical strength of the ALLOYS and cutting parameters: cutting speed (VC), depth of cut (AP), feed rate (F) and lubri-cooling condition (LUB), whose effect on the cutting temperature will be presented based on analysis of variance and factorial effects.

The chip formation process involves high deformation rates of the work material (elastoplastic), with almost all the deformation energy converted to heat in the cutting region [10]. This energy can be divided in: (A) – the work to shear the material in the primary shear zone; (B) – the energy needed to plastically deform the chip in the secondary shear zone; (C) – the work required to move the newly formed chip onto the rake surface and (D) – the work involved

factorial design, where the input

**2. Cutting temperature measurement, regression analysis and**

aluminum alloys, the theoretical fundaments will be presented first.

system in the turning process and measuring devices will be presented.

**2.1. Fundamentals of the temperature when machining aluminum alloys**

The cutting temperatures will be studied based on the 2k

factorial planning is used, allowing the analysis of the influences of the input

described. A 2k

72 Temperature Sensing

variables on the cutting temperature.

**mathematical modeling**

between inputs variables can affect the responses.

the temperature of the secondary shear zone is higher than the temperature of the body of the coming chip. However, indirectly, the heat generated in zone A also contributes to raising and affecting the temperature distribution on the tool wedge.

In the milling of A356 aluminum alloy, the increase in cutting temperature was observed with increasing cutting speed, which increased the amount of material adhered to the workpiece surface and to the cutting edge of the tool [25]. Kiliçkap et al. [26], during turning of Al-pure (5% SiC), also observed the increase of the temperature with the increase of the feed rate, which caused the weakening of the bond between the SiC particles and the aluminum matrix. Simulations by Zaghbani and Songmene [24], during the milling of the 7075-T6 aluminum alloy, showed the increase of the cutting temperature with the increase of the cutting speed and the feed; however, with the latter, the temperature increased asymptotically. This was explained by the increase in the rate of deformation with the increase of the cutting speed and

Temperature in Machining of Aluminum Alloys http://dx.doi.org/10.5772/intechopen.75943 75

Large rake angles, low coefficient of friction at the chip-tool contact and the presence of free cutting elements favor the chip flow on the surface of the tool (smaller cutting forces); and therefore inhibit the excessive elevation of the cutting temperature [16, 21, 27]. In the drilling of the aluminum alloy 319 (with 0.17% Pb), temperatures of the order of 375°C was obtained by infrared images; while in the same alloy without Pb, the level of temperature found was 450°C [28]. Geometric changes, such as those provided by flank wear, increase the cutting forces, which, in turn, increase the cutting temperature. During milling of the 7050-T7451 aluminum alloy, increased cutting forces was noticed with increased flank wear, which the consequent increase in cutting temperature helped to promote [29]. In this respect, Machado et al. [13] consider that if a tool achieves a considerable level of flank wear, the heat generated by zone D becomes

Several methods have been developed for measuring the cutting temperature [13], but the tool-workpiece thermocouple method, according to Da Silva and Wallbank [12] and GrzesiK [30], is the most used to predict the effect of the cutting conditions on the chip-tool interface temperature. The method uses the principle that a metal, subjected to a temperature differential, undergoes a non-uniform free electron distribution, which consequently causes an elec-

The practical use of the Seebeck effect in the measurement of a certain temperature (TJ) requires the use of two metallic materials (A and B), with different Seebeck coefficients, as shown in **Figure 2** (basic thermocouple circuit). In it, numbers 1, 2 and 3 are, respectively, the

Since the connection elements of the voltmeter (1 and 3) are at the same temperature (TT), it can be proved, via a path integral along the circuit of **Figure 2**, that its fundamental electromo-

*TT*

Thus, σab is the difference between the Seebeck coefficients of the thermocouple materials (A) and (B); and EAB is the electromotive force induced by the gradient between the desired

*TJ abdT* (1)

its reduction with the increase of the feed rate.

**2.2. Thermocouple systems**

junctions between the elements of the circuit.

*EAB* = ∫

tive force (EAB) equation is given by:

prominent due to the intense forces that will appear in that region.

tromotive force differential – a phenomenon known as the Seebeck effect [31].

temperature (TJ) (hot junction) and the temperature (TT) (cold junction).

Researchers have attempted to quantify the heat or temperatures generated in the shear zones. According to Dinc et al. [18], the heat generated in zone A and zone B depends on the cutting speed, shear forces and shear rates in the primary and secondary shear planes.

The mechanical and thermal properties of the work material and the tool, the tool geometry and the cutting conditions have great influence on the generation and transfer of the heat in the thermal zones [11, 12]. The higher the cutting speed, the feed rate and the depth of cut (higher material removal rates), the higher are the machining power and the heat generated in zones A and B [10, 14]; and therefore higher are the temperatures in the cut region [16, 19].

Increasing the cutting speed causes the rate of deformation of the material to increase, especially in zones A and B, which raises the rate of heat generation in these regions. However, the higher the cutting speed, in spite of raising the rate of heat generation in these zones, the lower is the heat flowing from zone A to the workpiece; and from zone B to the cutting tool. Higher feed rates tend to cause greater heat flow from zone B to the tool due to increased stresses and chip-tool contact area. However, Saglam et al. [20] consider that the cutting speed has greater effect on the generation of heat in the shear region than the feed rate. Obviously, the higher the mechanical strength of the work material, the greater the heat generation in zones A and B [9] (increase in the deformation resistance of the material). An efficient cooling action of a cutting fluid can also increase the mechanical resistance of the work material in zones A and B [13], therefore demanding more energy to form the chip and generating more heat. The heat generation in zones (A and B) will largely depend on the thermal conductivity of the tool and work materials and the cooling method [21]. The increase of the rake angle tends to reduce the generation of heat in zones A and B, because it favors the decreasing of the undeformed chip thickness and the slipping process of the chip on the rake face of the tool [9, 13].

Although complex, the temperature prediction at the chip-tool interface is very important in determining the maximum cutting speed, which can be applied in order to avoid reaching critical temperature levels. In the drilling of the aluminum Alloy 319 (5.5–6.5% Si), Dasch et al. [22] recorded a carbon coating impairment (DLC: Diamond Like Carbon) of the tool, at shear temperatures greater than 350°C, which caused clogging of the drill channels, due to the softening of the metal.

The great problem of temperature is when machining of aluminum alloy that have hard particles, such as the hypereutectic alloys of Si (17% and 23% Si), whose shear temperatures are quite high due to the constant friction of the large particles of Si precipitates (average diameter 70 μm, melting temperature of 1420°C and hardness greater than 400 HV) on the rake and clearance surfaces of the cutting tools [21]. In the dry turning of the aluminum alloys LM28 (17% Si) and LM13 (12% Si), in the proportion that the cutting speed was increased, higher cutting temperatures were registered in the first, due to their higher Si content and hardness and lower thermal conductivity [23]. In these same alloys, in the cast, cast/refined and thermally treated (T6) conditions, this (higher resistance limit) provided higher temperatures, agreeing with [21, 24].

In the milling of A356 aluminum alloy, the increase in cutting temperature was observed with increasing cutting speed, which increased the amount of material adhered to the workpiece surface and to the cutting edge of the tool [25]. Kiliçkap et al. [26], during turning of Al-pure (5% SiC), also observed the increase of the temperature with the increase of the feed rate, which caused the weakening of the bond between the SiC particles and the aluminum matrix. Simulations by Zaghbani and Songmene [24], during the milling of the 7075-T6 aluminum alloy, showed the increase of the cutting temperature with the increase of the cutting speed and the feed; however, with the latter, the temperature increased asymptotically. This was explained by the increase in the rate of deformation with the increase of the cutting speed and its reduction with the increase of the feed rate.

Large rake angles, low coefficient of friction at the chip-tool contact and the presence of free cutting elements favor the chip flow on the surface of the tool (smaller cutting forces); and therefore inhibit the excessive elevation of the cutting temperature [16, 21, 27]. In the drilling of the aluminum alloy 319 (with 0.17% Pb), temperatures of the order of 375°C was obtained by infrared images; while in the same alloy without Pb, the level of temperature found was 450°C [28].

Geometric changes, such as those provided by flank wear, increase the cutting forces, which, in turn, increase the cutting temperature. During milling of the 7050-T7451 aluminum alloy, increased cutting forces was noticed with increased flank wear, which the consequent increase in cutting temperature helped to promote [29]. In this respect, Machado et al. [13] consider that if a tool achieves a considerable level of flank wear, the heat generated by zone D becomes prominent due to the intense forces that will appear in that region.

## **2.2. Thermocouple systems**

the temperature of the secondary shear zone is higher than the temperature of the body of the coming chip. However, indirectly, the heat generated in zone A also contributes to raising and

Researchers have attempted to quantify the heat or temperatures generated in the shear zones. According to Dinc et al. [18], the heat generated in zone A and zone B depends on the cutting

The mechanical and thermal properties of the work material and the tool, the tool geometry and the cutting conditions have great influence on the generation and transfer of the heat in the thermal zones [11, 12]. The higher the cutting speed, the feed rate and the depth of cut (higher material removal rates), the higher are the machining power and the heat generated in zones A and B [10, 14]; and therefore higher are the temperatures in the cut region [16, 19]. Increasing the cutting speed causes the rate of deformation of the material to increase, especially in zones A and B, which raises the rate of heat generation in these regions. However, the higher the cutting speed, in spite of raising the rate of heat generation in these zones, the lower is the heat flowing from zone A to the workpiece; and from zone B to the cutting tool. Higher feed rates tend to cause greater heat flow from zone B to the tool due to increased stresses and chip-tool contact area. However, Saglam et al. [20] consider that the cutting speed has greater effect on the generation of heat in the shear region than the feed rate. Obviously, the higher the mechanical strength of the work material, the greater the heat generation in zones A and B [9] (increase in the deformation resistance of the material). An efficient cooling action of a cutting fluid can also increase the mechanical resistance of the work material in zones A and B [13], therefore demanding more energy to form the chip and generating more heat. The heat generation in zones (A and B) will largely depend on the thermal conductivity of the tool and work materials and the cooling method [21]. The increase of the rake angle tends to reduce the generation of heat in zones A and B, because it favors the decreasing of the undeformed chip thickness

Although complex, the temperature prediction at the chip-tool interface is very important in determining the maximum cutting speed, which can be applied in order to avoid reaching critical temperature levels. In the drilling of the aluminum Alloy 319 (5.5–6.5% Si), Dasch et al. [22] recorded a carbon coating impairment (DLC: Diamond Like Carbon) of the tool, at shear temperatures greater than 350°C, which caused clogging of the drill channels, due to

The great problem of temperature is when machining of aluminum alloy that have hard particles, such as the hypereutectic alloys of Si (17% and 23% Si), whose shear temperatures are quite high due to the constant friction of the large particles of Si precipitates (average diameter 70 μm, melting temperature of 1420°C and hardness greater than 400 HV) on the rake and clearance surfaces of the cutting tools [21]. In the dry turning of the aluminum alloys LM28 (17% Si) and LM13 (12% Si), in the proportion that the cutting speed was increased, higher cutting temperatures were registered in the first, due to their higher Si content and hardness and lower thermal conductivity [23]. In these same alloys, in the cast, cast/refined and thermally treated (T6) conditions, this (higher resistance limit) provided higher temperatures,

speed, shear forces and shear rates in the primary and secondary shear planes.

and the slipping process of the chip on the rake face of the tool [9, 13].

the softening of the metal.

agreeing with [21, 24].

affecting the temperature distribution on the tool wedge.

74 Temperature Sensing

Several methods have been developed for measuring the cutting temperature [13], but the tool-workpiece thermocouple method, according to Da Silva and Wallbank [12] and GrzesiK [30], is the most used to predict the effect of the cutting conditions on the chip-tool interface temperature. The method uses the principle that a metal, subjected to a temperature differential, undergoes a non-uniform free electron distribution, which consequently causes an electromotive force differential – a phenomenon known as the Seebeck effect [31].

The practical use of the Seebeck effect in the measurement of a certain temperature (TJ) requires the use of two metallic materials (A and B), with different Seebeck coefficients, as shown in **Figure 2** (basic thermocouple circuit). In it, numbers 1, 2 and 3 are, respectively, the junctions between the elements of the circuit.

Since the connection elements of the voltmeter (1 and 3) are at the same temperature (TT), it can be proved, via a path integral along the circuit of **Figure 2**, that its fundamental electromotive force (EAB) equation is given by:

$$
\triangle AB = \int\_{T}^{|\gamma|} \sigma ab dT \tag{1}
$$

Thus, σab is the difference between the Seebeck coefficients of the thermocouple materials (A) and (B); and EAB is the electromotive force induced by the gradient between the desired temperature (TJ) (hot junction) and the temperature (TT) (cold junction).

**Figure 2.** A basic thermocouple circuit [31].

It is possible to establish a reference temperature (TR) equal to zero by the arrangement of the electric circuit of thermocouples of **Figure 3**. In this figure, TR and TT are any temperatures; TJ is the desired temperature (hot junction of the thermocouple) – the numbered dark points are the junctions between the elements of the electric circuit, which allow its continuity.

The electromotive forces due to copper wires cancel out. Through a suitable calibration process involving the desired temperature (TJ) and the electromotive force of the circuit (E0J), it is possible to establish a mathematical relationship between these quantities:

$$T\!\!\!/ = \!\!\!/ \!\!G\!\!\/ \!\/ \!\/ = \!\!\!/ \_0 + b\_{1\*}E\_{\!\!\/\/ \_0} + b\_{2\*}E\_{\!\!\/\/ \_0} + \dots + b\_{n}E\_{\!\!\/ \_0} \tag{2}$$

(3) – brushes (7); J5 is the junction brushes (7) – articulating arm (6); J6 is the junction articulating arm (6) – device body (5); J7 is the junction device body (5) – copper wire (9); and J8 is the

Temperature in Machining of Aluminum Alloys http://dx.doi.org/10.5772/intechopen.75943 77

During machining, the electromotive force generated in the tool-workpiece thermocouple circuit is proportional to the temperature gradient between the tool and the room temperature. The metal segments between junctions 1–2 and 4–5, because they are at the same temperature, do not generate electromotive forces. Thus, the only pairs of junctions, which are under temperature gradient and therefore contribute to the electromotive force of the electric circuit are

For cutting temperature measurement in turning with the tool-workpiece thermocouple system, it is necessary to develop a device analogous to the one shown in **Figure 4**. Two important

junction copper wire (9) – multimeter connector.

**Figure 5.** The thermoelectric junctions of the electrical circuit.

**Figure 4.** Schematic draw of the tool-workpiece thermocouple system.

**2.4. The temperature measurement device in turning process**

the pairs of joints 2–3 and 3–4.

## **2.3. The tool-workpiece thermocouple system for measuring the cutting temperature**

**Figure 4** shows a schematic draw of the tool-workpiece thermocouple system used in the process of acquisition of electromotive force (FEM), during the machining. The multimeter (11) and wires (8–9) should be the same as those used in the calibration process of the toolworkpiece thermocouple; the tool holder (13) is isolated from the structure of the CNC lathe with celeron plates (2 mm) around it. Three brushes (7) allow to close the electric circuit of the system, with the workpiece (3) in rotating movement, in the presence of a thin layer of solid Vaseline in their contacts. With the exception of the tool holder/cutting tool and the workpiece, the CNC lathe and accessories are connected to the equipotential earth (14).

**Figure 5** shows schematically the thermoelectric junctions present in the electrical circuit of **Figure 4**, where J1 is the junction copper wire (8) – connector multimeter; J2 is the junction tool (13) – copper wire (8); J3 is junction tool (13) – workpiece (3); J4 is the junction workpiece

**Figure 3.** Thermocouple circuit with a zero reference temperature [31].

**Figure 4.** Schematic draw of the tool-workpiece thermocouple system.

It is possible to establish a reference temperature (TR) equal to zero by the arrangement of the electric circuit of thermocouples of **Figure 3**. In this figure, TR and TT are any temperatures; TJ is the desired temperature (hot junction of the thermocouple) – the numbered dark points are the junctions between the elements of the electric circuit, which allow its continuity.

The electromotive forces due to copper wires cancel out. Through a suitable calibration process involving the desired temperature (TJ) and the electromotive force of the circuit (E0J), it

**2.3. The tool-workpiece thermocouple system for measuring the cutting temperature**

piece, the CNC lathe and accessories are connected to the equipotential earth (14).

**Figure 4** shows a schematic draw of the tool-workpiece thermocouple system used in the process of acquisition of electromotive force (FEM), during the machining. The multimeter (11) and wires (8–9) should be the same as those used in the calibration process of the toolworkpiece thermocouple; the tool holder (13) is isolated from the structure of the CNC lathe with celeron plates (2 mm) around it. Three brushes (7) allow to close the electric circuit of the system, with the workpiece (3) in rotating movement, in the presence of a thin layer of solid Vaseline in their contacts. With the exception of the tool holder/cutting tool and the work-

**Figure 5** shows schematically the thermoelectric junctions present in the electrical circuit of **Figure 4**, where J1 is the junction copper wire (8) – connector multimeter; J2 is the junction tool (13) – copper wire (8); J3 is junction tool (13) – workpiece (3); J4 is the junction workpiece

+ *b*2∗ *E*2 *0J* + …+*bn En*

*0J* (2)

is possible to establish a mathematical relationship between these quantities:

*TJ* = *G*(*E*0*J*) = *b*0 + *b*1∗ *E0J*

**Figure 3.** Thermocouple circuit with a zero reference temperature [31].

**Figure 2.** A basic thermocouple circuit [31].

76 Temperature Sensing

(3) – brushes (7); J5 is the junction brushes (7) – articulating arm (6); J6 is the junction articulating arm (6) – device body (5); J7 is the junction device body (5) – copper wire (9); and J8 is the junction copper wire (9) – multimeter connector.

During machining, the electromotive force generated in the tool-workpiece thermocouple circuit is proportional to the temperature gradient between the tool and the room temperature. The metal segments between junctions 1–2 and 4–5, because they are at the same temperature, do not generate electromotive forces. Thus, the only pairs of junctions, which are under temperature gradient and therefore contribute to the electromotive force of the electric circuit are the pairs of joints 2–3 and 3–4.

## **2.4. The temperature measurement device in turning process**

For cutting temperature measurement in turning with the tool-workpiece thermocouple system, it is necessary to develop a device analogous to the one shown in **Figure 4**. Two important

**Figure 5.** The thermoelectric junctions of the electrical circuit.

connection components are required for completing the electric circuit and capture the electromotive forces, the tool (13) and the 03 brushes device of **Figure 4**.

## *2.4.1. The three brushes device*

**Figure 6** shows details of the three brush device, element (5) of **Figure 4**: (1) body of the device; (2) tailstock gulf; (3) articulating arm, with central bore; (4) workpiece bar; (5) wire connectors; (6) aluminum brush. With the exception of the springs inside the articulating arms and screws, all the elements were made of aluminum alloy.

## *2.4.2. The tool and tool holder*

**Figure 7** shows an image of the cutting tool ((13) in **Figure 4**), adapted for measuring the cutting temperature (TC) in the turning process: (1) is the cemented carbide bit (310 × 10 × 4 mm); (2) is the tool holder (25 × 20 × 150 mm) made of steel; (3) are the fastening screws of the carbide bar in the tool holder; (4) is the lateral electrical insulation; (5) is the upper electrical insulation; (6) is the lower electrical insulation; (7) is the copper connector. Through this element the tool was connected to the multimeter through a copper wire.

## *2.4.3. Machinery, tools and consumables*

The cutting temperature tests were carried out on a CNC lathe, model Multiplic 35D, manufactured by ROMI. The cutting tool was a rectangular carbide bar (13 × 4 × 310 mm) K15 grade, with 93% WC + 7% Co, grain size 1.0 μm and hardness of 1580 HV (TASK, 2009). Its geometry was ground in one of its ends, as presented in **Figure 8**.

**2.5. The 2k factorial design**

superior view of the opposite end.

*2.5.1. The levels of the input variables*

**Figure 8.** Tool bit geometry.

In this case study, the effect of five (k = 5) input parameters (Tensile strength of the workpiece – ALLOY, cutting speed (VC), depth of cut (AP), feed rate(F) and lubri-cooling condition (LUB) on the cutting temperature collected with the methodology of the tool-workpiece

**Figure 7.** Photos of the cutting tool: (a) lateral view; (b) superior view; (c) lateral view of the mid of the tool holder; (d)

Temperature in Machining of Aluminum Alloys http://dx.doi.org/10.5772/intechopen.75943 79

**Table 1** shows the levels of the factors that combined, resulted in 32 treatments (tests) for

thermocouple system presented in **Figure 4** will be considered.

studying the cutting temperature in turning of aluminum alloys.

The cutting fluid applying by flooding was the water miscible (Vasco 1000 – Blaser Swisslube) – high performance biodegradable oil, recommended for machining non-ferrous materials, with 45% vegetable oil (no mineral based oil), 0.1% H2 O, density of 950 kg/m3 (20°C), viscosity of 56 mm2 /s (40°C) and flash point of 180°C (BLASER SWISSLUBE, 2010). The fluid was applied at the cutting region with a concentration of 6% in water (frequently checked with an ATAGO refractometer) and a flow rate of 360 L/h.

**Figure 6.** The three brushes device used for temperature measurement in turning.

**Figure 7.** Photos of the cutting tool: (a) lateral view; (b) superior view; (c) lateral view of the mid of the tool holder; (d) superior view of the opposite end.

## **2.5. The 2k factorial design**

connection components are required for completing the electric circuit and capture the electro-

**Figure 6** shows details of the three brush device, element (5) of **Figure 4**: (1) body of the device; (2) tailstock gulf; (3) articulating arm, with central bore; (4) workpiece bar; (5) wire connectors; (6) aluminum brush. With the exception of the springs inside the articulating

**Figure 7** shows an image of the cutting tool ((13) in **Figure 4**), adapted for measuring the cutting temperature (TC) in the turning process: (1) is the cemented carbide bit (310 × 10 × 4 mm); (2) is the tool holder (25 × 20 × 150 mm) made of steel; (3) are the fastening screws of the carbide bar in the tool holder; (4) is the lateral electrical insulation; (5) is the upper electrical insulation; (6) is the lower electrical insulation; (7) is the copper connector. Through this element

The cutting temperature tests were carried out on a CNC lathe, model Multiplic 35D, manufactured by ROMI. The cutting tool was a rectangular carbide bar (13 × 4 × 310 mm) K15 grade, with 93% WC + 7% Co, grain size 1.0 μm and hardness of 1580 HV (TASK, 2009). Its geometry

The cutting fluid applying by flooding was the water miscible (Vasco 1000 – Blaser Swisslube) – high performance biodegradable oil, recommended for machining non-ferrous materials,

applied at the cutting region with a concentration of 6% in water (frequently checked with an

/s (40°C) and flash point of 180°C (BLASER SWISSLUBE, 2010). The fluid was

O, density of 950 kg/m3

(20°C), viscos-

motive forces, the tool (13) and the 03 brushes device of **Figure 4**.

arms and screws, all the elements were made of aluminum alloy.

the tool was connected to the multimeter through a copper wire.

was ground in one of its ends, as presented in **Figure 8**.

with 45% vegetable oil (no mineral based oil), 0.1% H2

**Figure 6.** The three brushes device used for temperature measurement in turning.

ATAGO refractometer) and a flow rate of 360 L/h.

*2.4.1. The three brushes device*

78 Temperature Sensing

*2.4.2. The tool and tool holder*

*2.4.3. Machinery, tools and consumables*

ity of 56 mm2

In this case study, the effect of five (k = 5) input parameters (Tensile strength of the workpiece – ALLOY, cutting speed (VC), depth of cut (AP), feed rate(F) and lubri-cooling condition (LUB) on the cutting temperature collected with the methodology of the tool-workpiece thermocouple system presented in **Figure 4** will be considered.

## *2.5.1. The levels of the input variables*

**Table 1** shows the levels of the factors that combined, resulted in 32 treatments (tests) for studying the cutting temperature in turning of aluminum alloys.

**Figure 8.** Tool bit geometry.

**Table 1.** Level of the factors of the 2k factorial design.

The workpiece was extruded round bars (Ø 101 × 2000 mm) of the following aluminum alloys: 1350-O and 7075-T6; manufactured by Alcoa. **Table 2** shows the chemical composition, highlighting the main chemical elements present in the aluminum alloys.

**Figure 9a** and **9b** show micrographs for the 1350-O and 7075-T6 alloys, respectively. Intermetallic precipitates of FeAl3 , AlFeSi, and Mg2 Al due to the annealing process can be identified (**Figure 9a**), while the matrix of the 7075-T6 alloy (**Figure 9b**) exhibits a high density of

fine MgZn2

alloys and elongation of the alloys, respectively.

as input variables: ALLOY, VC, AP, F and LUB.

**2.6. Temperature measurement**

alloys; (d) elongation of the alloys.

**2.7. Temperature results analysis**

*2.7.1. Analysis of variance (ANOVA)*

to the ANOVA.

precipitates as a result of the artificial aging process that provides a high mechani-

factorial design using

Temperature in Machining of Aluminum Alloys http://dx.doi.org/10.5772/intechopen.75943 81

cal strength relative to the 1350-O alloy. **Figure 9c** and **9d** show mechanical strength of the

**Figure 9.** (a) Microstructure of the 1350-O alloy; (b) microstructure of the 7075-T6 alloy; (c) mechanical strength of the

**Table 3** presents the results of the chip-tool temperatures (TC) measured (average of two rep-

**Table 4** presents the statistic analysis (ANOVA) of the chip-tool interface temperature considering the 32 tests, where the effects of the main significant input parameters are identified (p value <0.05) with 95% of confidence level. Observe that ALLOY, VC, and AP either individually or in interactions appear with significant influences on the temperature according

licates) by the tool workpiece thermocouple system according to the 2k

**Table 2.** Chemical composition (wt %) of the aluminum alloys.

**Figure 9.** (a) Microstructure of the 1350-O alloy; (b) microstructure of the 7075-T6 alloy; (c) mechanical strength of the alloys; (d) elongation of the alloys.

fine MgZn2 precipitates as a result of the artificial aging process that provides a high mechanical strength relative to the 1350-O alloy. **Figure 9c** and **9d** show mechanical strength of the alloys and elongation of the alloys, respectively.

## **2.6. Temperature measurement**

The workpiece was extruded round bars (Ø 101 × 2000 mm) of the following aluminum alloys: 1350-O and 7075-T6; manufactured by Alcoa. **Table 2** shows the chemical composition, high-

**Level Alloy VC (m/min) F (mm/rot) AP (mm) LUB** Low (−1) 1350-O 300 0.2 1 Dry High (+1) 7075-T6 600 0.3 3 Flood

**Figure 9a** and **9b** show micrographs for the 1350-O and 7075-T6 alloys, respectively.

tified (**Figure 9a**), while the matrix of the 7075-T6 alloy (**Figure 9b**) exhibits a high density of

Al due to the annealing process can be iden-

, AlFeSi, and Mg2

lighting the main chemical elements present in the aluminum alloys.

**Elements 1350-O 7075** Cu 0.05 1.20–2.00 Fe 0.40 0.05 Mg 0.03 2.10–2.90 Mn 0.10 0.30 Ni 0.03 0.05 Si 0.10 0.40 Ti 0.03 0.20 Zn 0.05 5.10–6.10 Bi 0.03 0.05 Cr 0.01 0.18–0.28 Pb 0.03 0.050 Sn 0.03 0.05 Be 0.03 0.05 Ca 0.03 0.05 Ga 0.03 0.05 Li 0.03 0.05 Na 0.03 0.05 Sr 0.03 0.05 Zr 0.03 0.05 Others 0.10 0.15 Al Rem. Rem.

**Table 2.** Chemical composition (wt %) of the aluminum alloys.

factorial design.

Intermetallic precipitates of FeAl3

**Table 1.** Level of the factors of the 2k

80 Temperature Sensing

**Table 3** presents the results of the chip-tool temperatures (TC) measured (average of two replicates) by the tool workpiece thermocouple system according to the 2k factorial design using as input variables: ALLOY, VC, AP, F and LUB.

## **2.7. Temperature results analysis**

## *2.7.1. Analysis of variance (ANOVA)*

**Table 4** presents the statistic analysis (ANOVA) of the chip-tool interface temperature considering the 32 tests, where the effects of the main significant input parameters are identified (p value <0.05) with 95% of confidence level. Observe that ALLOY, VC, and AP either individually or in interactions appear with significant influences on the temperature according to the ANOVA.

*2.7.2. Verification of the suitability of the ANOVA models of the 2K factorial design*

**Figure 10.** (a) Residues vs. predicted values; (b) predicted values (Ypred) vs. observed values (Yobs).

factorial design.

ALLOY 541359.56 1.00 541359.56 130.07 966.73 0.00 VC 41034.95 1.00 41034.95 35.81 73.28 0.00 AP 4311.41 1.00 4311.41 −11.61 7.70 0.01 ALLOY×AP 3917.59 1.00 3917.59 11.06 7.00 0.01 AP×LUB 4694.76 1.00 4694.76 12.11 8.38 0.01 Error 14559.77 26.00 559.99 'GLR' 5.00 —

Total 609878.03 31.00 'SQR' 595318.27 'MQR' 119063.65

shows close proximity to each other.

*2.7.3. Effects of the input variables*

**Table 4.** Analysis of variance of the 2k

**Source of variation**

Analysis of the residues of the models used in the analysis of variance (ANOVA) of the factorial planning was carried out, by verifying the expected value of the residue (**Figure 10a**), which showed them randomly distributed around zero, which indicates the suitability of the ANOVA models. **Figure 10b**, compare observed value (Yobs) e predicted value (Ypred) which

**R2 0.97 FStat 212.617 pValModel 3.20E-20**

Temperature in Machining of Aluminum Alloys http://dx.doi.org/10.5772/intechopen.75943 83

**SQ GL MQ Coef Fstat p Value**

**Figures 11** and **12** show the graphics of tendencies of the effects of the input variables on the cutting temperature. When increasing the depth of cut from 1 mm (low level) to 3 mm (high level) the chip-tool interface temperature decreases (**Figure 11a**). Although increasing the depth of cut tends to increase the machining forces, a better heat dissipation could have occurred with the increase of the cutting area, which caused a reduction of the cutting

**Table 3.** Average results of the chip-tool interface temperature of the 2k factorial design.

**Table 4.** Analysis of variance of the 2k factorial design.

 Average results of the chip-tool interface temperature of the 2k

factorial design.

#### *2.7.2. Verification of the suitability of the ANOVA models of the 2K factorial design*

Analysis of the residues of the models used in the analysis of variance (ANOVA) of the factorial planning was carried out, by verifying the expected value of the residue (**Figure 10a**), which showed them randomly distributed around zero, which indicates the suitability of the ANOVA models. **Figure 10b**, compare observed value (Yobs) e predicted value (Ypred) which shows close proximity to each other.

#### *2.7.3. Effects of the input variables*

**Figures 11** and **12** show the graphics of tendencies of the effects of the input variables on the cutting temperature. When increasing the depth of cut from 1 mm (low level) to 3 mm (high level) the chip-tool interface temperature decreases (**Figure 11a**). Although increasing the depth of cut tends to increase the machining forces, a better heat dissipation could have occurred with the increase of the cutting area, which caused a reduction of the cutting

**Figure 10.** (a) Residues vs. predicted values; (b) predicted values (Ypred) vs. observed values (Yobs).

**3. Conclusions**

condition (LUB); (b) ALLOY and depth of cut (AP).

**Acknowledgements**

**Conflict of interest**

The measurement of the cutting temperature with the tool-workpiece thermocouple system with the 03 brushes device allowed the investigation of the influences of the cutting conditions (VC, AP, and LUB) and the mechanical strength of the aluminum alloy (ALLOY) over the cutting temperature (TC). It was verified that the cutting temperature was greatly affected by the individual variation of the factors (ALLOY, VC, AP, LUB), as well as by their interactions. It was observed an increase in the cutting temperature with increasing cutting speed and mechanical strength of the ALLOY. The cutting temperature decreased with increasing depth of cut. The interaction of increasing ALLOY strength and depth of cut also increased the cutting temperature. The effect of the application of a cutting fluid depended on the depth of cut used. With the lower level of doc (1 mm) the cutting fluid reduced the cutting temperature when compare to dry cutting. This did not occur when using the high level of doc (3 mm), where the cutting fluid increased the chip-tool interface temperature, probably because it increased the shear strength of the work material by cooling the cutting region. The direction of growth of the cutting temperature occurred with the increase of the depth of cut,

**Figure 12.** Effect of the interaction of input variables in the cutting temperature: (a) depth of cut (AP) and lubri-cooling

Temperature in Machining of Aluminum Alloys http://dx.doi.org/10.5772/intechopen.75943 85

The authors are grateful to CNPq, CAPES and FAPEMIG for usual financial support to LEPU

The authors declare that no 'conflict of interest' whatsoever exists in publishing this book chapter.

the advance and the cutting speed, having this greater effect.

– Laboratory for Education and Research in Machining – UFU.

**Figure 11.** Behavior of the cutting temperature when changing the: (a) depth of cut (AP); (b) ALLOY; (c) cutting speed (VC).

temperature. **Figure 11b** shows that when changing the aluminum alloy from the high ductile 1350-O to the less ductile 7075-T6, the chip-tool interface temperature raised. This is because the higher shear strength of the 7075-T6 alloy, as compared to the 1350-O. **Figure 11c** shows that increasing the cutting speed increased the cutting temperature because it increased the shear rate in the cutting region.

**Figure 12a** shows effect of the interaction between the depth of cut (AP) and lubri-cooling condition (LUB) on the cutting temperature. When using flood cooling (LUB+1) and the depth of cut of 1 mm (level −1) the average temperature at the chip-tool interface was about 10°C lower than dry condition. However, when the depth of cut of 3 mm (level +1) was used, the temperature was higher (about 40°C) when using the flood cooling than when cutting dry. This is, perhaps, because the cooling action of the cutting fluid was more important than its lubricating action, thereby increasing the shearing strength of the work material in the cutting region, which was also favored by the increase in the areas of these planes (AP level +1), which in turn has improved the heat dissipation in the cutting region. In **Figure 12b**, the interaction between the ALLOY (strength) and the depth of cut (AP) is illustrated. When changing from 1350-O ALLOY (level -1) to ALLOY 7075-T (level +1) there was a great increase in shear strength in the shear planes and thus an increase of the heat generation and cutting temperature.

**Figure 12.** Effect of the interaction of input variables in the cutting temperature: (a) depth of cut (AP) and lubri-cooling condition (LUB); (b) ALLOY and depth of cut (AP).

## **3. Conclusions**

temperature. **Figure 11b** shows that when changing the aluminum alloy from the high ductile 1350-O to the less ductile 7075-T6, the chip-tool interface temperature raised. This is because the higher shear strength of the 7075-T6 alloy, as compared to the 1350-O. **Figure 11c** shows that increasing the cutting speed increased the cutting temperature because it increased the

**Figure 11.** Behavior of the cutting temperature when changing the: (a) depth of cut (AP); (b) ALLOY; (c) cutting speed (VC).

**Figure 12a** shows effect of the interaction between the depth of cut (AP) and lubri-cooling condition (LUB) on the cutting temperature. When using flood cooling (LUB+1) and the depth of cut of 1 mm (level −1) the average temperature at the chip-tool interface was about 10°C lower than dry condition. However, when the depth of cut of 3 mm (level +1) was used, the temperature was higher (about 40°C) when using the flood cooling than when cutting dry. This is, perhaps, because the cooling action of the cutting fluid was more important than its lubricating action, thereby increasing the shearing strength of the work material in the cutting region, which was also favored by the increase in the areas of these planes (AP level +1), which in turn has improved the heat dissipation in the cutting region. In **Figure 12b**, the interaction between the ALLOY (strength) and the depth of cut (AP) is illustrated. When changing from 1350-O ALLOY (level -1) to ALLOY 7075-T (level +1) there was a great increase in shear strength in the

shear planes and thus an increase of the heat generation and cutting temperature.

shear rate in the cutting region.

84 Temperature Sensing

The measurement of the cutting temperature with the tool-workpiece thermocouple system with the 03 brushes device allowed the investigation of the influences of the cutting conditions (VC, AP, and LUB) and the mechanical strength of the aluminum alloy (ALLOY) over the cutting temperature (TC). It was verified that the cutting temperature was greatly affected by the individual variation of the factors (ALLOY, VC, AP, LUB), as well as by their interactions. It was observed an increase in the cutting temperature with increasing cutting speed and mechanical strength of the ALLOY. The cutting temperature decreased with increasing depth of cut. The interaction of increasing ALLOY strength and depth of cut also increased the cutting temperature. The effect of the application of a cutting fluid depended on the depth of cut used. With the lower level of doc (1 mm) the cutting fluid reduced the cutting temperature when compare to dry cutting. This did not occur when using the high level of doc (3 mm), where the cutting fluid increased the chip-tool interface temperature, probably because it increased the shear strength of the work material by cooling the cutting region. The direction of growth of the cutting temperature occurred with the increase of the depth of cut, the advance and the cutting speed, having this greater effect.

## **Acknowledgements**

The authors are grateful to CNPq, CAPES and FAPEMIG for usual financial support to LEPU – Laboratory for Education and Research in Machining – UFU.

## **Conflict of interest**

The authors declare that no 'conflict of interest' whatsoever exists in publishing this book chapter.

## **Appendices and nomenclature**

**Author details**

Mário C. Santos1

Brazil

Brazil

**References**

São Mateus, ES, Brazil

\*, Alisson R. Machado2,3 and Marcos A.S. Barrozo4

1 Mechanical Engineering Department, Federal Institute of Technology of Espírito Santo,

Temperature in Machining of Aluminum Alloys http://dx.doi.org/10.5772/intechopen.75943 87

3 Faculty of Mechanical Engineering, Federal University of Uberlandia, Uberlandia, MG,

4 Faculty of Chemical Engineering, Federal University of Uberlandia, Uberlandia, MG,

[1] Hovsepian PE, Luo Q, Robinson G, Pittman M, Howarth M, Doerwald D, Tietema R, Sim WM, Deeming A, Zeus T. TiAlN/VN superlattice structured PVD coatings: A new alternative in machining of aluminium alloys for aerospace and automotive components.

[2] Demir H, Gündüz S. The effects of aging on machinability of 6061 aluminium alloy.

[3] Figueiredo KM. Mapeamento dos modos de transferência metálica na soldagem de alumínio [thesis]. Uberlância: Universidade Federal de Uberlândia, Uberlândia; 2000

[4] Hamade RF, Ismail F. A case for aggressive drilling of aluminum. Journal of Materials

[5] Roy P, Sarangi SK, Ghosh A, Chattopadhyay AK. Machinability study of pure aluminium and Al–12% Si alloys against uncoated and coated carbide inserts. International

[6] Davies RW, Vetrano JS, Smith MT, Pitman SG. Mechanical properties of aluminum tailor welded blanks at superplastic temperatures. Journal of Materials Processing Technology.

[7] Miller WS, Zhuang L, Bottema J, Wittebrood AJ, De Smet P, Haszler A, Vieregge A. Recent development in aluminium alloys for the automotive industry. Materials Science and

Journal of Refractory Metals & Hard Materials. 2009;**27**:535-544

\*Address all correspondence to<EMAIL_ADDRESS>
2 Universidade Católica do Paraná—PUCPR, Curitiba, PR, Brazil

Surface and Coating Technology. 2006;**201**:265-272

Journal Materials and Design. 2009;**30**:1480-1483

Processing Technology. 2005;**166**:86-97

2002;**128**:38-47

Engineering. 2000;**280**:37-49

## **Author details**

**Appendices and nomenclature**

Aα relief surface Aγ rake surface

86 Temperature Sensing

Cu copper

AP depth of cut (mm) Coef model coefficients IC confidence interval

F feed rate (mm/rev)

GL degree of freedom

Fstat statistics F of the coefficient

FEM electromotive force (V)

LUB lubri-cooling condition

MQR quadratic mean of the model

p-value statistic p of the coefficient

pValModel statistic p of the model

R2 determination coefficient

SQ quadratic sum of the coefficient

SQR quadratic sum of the model

TR reference temperature (°C)

TT cold junction temperature

TA room temperature (°C) TC cutting temperature (°C)

TJ junction temperature

VC cutting speed (m/min)

χ'r approach angle

αo relief angel γo rake angle

Mário C. Santos1 \*, Alisson R. Machado2,3 and Marcos A.S. Barrozo4

\*Address all correspondence to<EMAIL_ADDRESS>
1 Mechanical Engineering Department, Federal Institute of Technology of Espírito Santo, São Mateus, ES, Brazil

2 Universidade Católica do Paraná—PUCPR, Curitiba, PR, Brazil

3 Faculty of Mechanical Engineering, Federal University of Uberlandia, Uberlandia, MG, Brazil

4 Faculty of Chemical Engineering, Federal University of Uberlandia, Uberlandia, MG, Brazil

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[9] Vernaza-Pefia KM, Mason JJ, Li M. Experimental study of the temperature field generated during orthogonal machining of an aluminum alloy. Experimental Mechanics.

[10] Seker U, Korkut İ, Turgut Y, Boy M. The Measurement of Temperature During Machining.

[11] Abukhshim NA, Mativenga PT, Sheikh MA. Heat generation and temperature prediction in metal cutting: A review and implications for high speed machining. International

[12] Da Silva MB, Wallbank J. Cutting temperature: Prediction and measurement methods—

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[14] Boothroyd G. Fundamentals of Metal Machining and Machine Tools. London: McGraw-

[15] Diniz AE, Marcondes FC, Coppini NL. Tecnologia da Usinagem dos Metais. 3nd ed. São

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88 Temperature Sensing

## *Edited by Ivanka Stanimirović and Zdravko Stanimirović*

Temperature is the most often-measured environmental quantity and scientists are continuously improving ways of sensing it. To present their work in the field of temperature sensing, researchers from distant parts of the world have joined their efforts and contributed their ideas according to their interest and engagement. Their articles will give you the opportunity to understand concepts and uses of fiber-optic sensing technology. The optical fiber Mach-Zehnder interferometer for temperature sensing is presented, as well as the optical fiber-distributed temperature sensor and fiber Bragg grating-based sensor. You can learn about tunable diode laser absorption spectroscopy and its various industrial applications. Last but not least, cutting temperature measurements during the machining of aluminum alloys provides us with an insight into the correlation between cutting conditions, mechanical strength of the aluminum alloy, and the cutting temperature measured using the tool-workpiece thermocouple system. The editors hope that the presented contributions will allow both professionals and readers not involved in the immediate field to understand and enjoy the topic.

Published in London, UK © 2018 IntechOpen © AVNphotolab / iStock

Temperature Sensing

Temperature Sensing

*Edited by Ivanka Stanimirović*

*and Zdravko Stanimirović*


**About the Editor**

**Laszlo Erdos** graduated from the University of Szeged (Hungary) as a biologist in 2005. He earned his PhD in vegetation ecology at the University of Pecs (Hungary). His main area of ´ interest is the vegetation ecology of Eurasian forest-steppes. Currently, he is a research fellow at the Centre for Ecological Research (Vacr ´ at´ ot) and at the University of Debrecen (Debrecen). He also ´ serves as visiting lecturer at the Eotv ¨ os Lor ¨ and University (Budapest). ´

#### **Preface to "Spatial Heterogeneity of Forest-Steppes"**

Situated between the closed-canopy forests and the open steppes, forest-steppes feature a highly complex mosaic of woody and herbaceous habitats. Though forest-steppes exits in North and South-America, the largest forest-steppes are found in Eurasia, where they extend as an almost continuous belt from the Carpathian Basin in Eastern Central Europe to the Far East in China and Russia. Despite its tremendous biogeographical, ecological and even economic importance, the forest-steppe zone has received surprisingly little scientific attention. As forest-steppe landscapes are composed of a high variety of different forest, scrub and grassland communities and the ecotones among them, spatial heterogeneity is a key issue if we are to understand how forest-steppe ecosystems work and how they may react to environmental changes at the local, regional, and global scales.

Forest-steppes exist in a transitional semi-humid to semi-arid climate that enables the long-term coexistence of forests and grasslands, as these have roughly equal chances to develop. The competition outcome at every given site depends on minor differences in terrain, soil and microclimate characteristics. Once established, grassland species probably modify the environment to favor the continued existence of the grassland patch, while trees and shrubs support the persistence of woody vegetation. This seems to stabilize forest-steppe mosaics, though modifications in climate, herbivore pressure or fire frequency and intensity may alter the balance. Unfortunately, it is not known how strong these feedbacks are, thus we do not know if and where the current patterns are able to resist natural and anthropogenic changes.

Forest-steppes host exceptional taxonomic diversity from local to landscape to regional scales. In addition, they harbor a large number of rare, nationally protected, and internationally threatened species. Moreover, the functional diversity of forest-steppes is very high, with a large variety of life-forms.

Forest-steppes provide us with a number of vital ecosystem services, including a large carbon sequestration capacity, protection from soil erosion, and aesthetic value.

Unfortunately, large forest-steppe areas, especially in the most populous regions, have been destroyed and replaced with (mostly non-native) tree plantations or arable fields, while the remaining near-natural areas are threatened by the spread of invasive species, fragmentation, and overexploitation. Thus, preserving forest-steppe ecosystems presents a great challenge to conservationists. May we hope that a better understanding of this unique ecosystem will contribute to its more efficient conservation.

> **Laszlo Erdos** *Editor*


**3.2. New sickle cell disease research shows improved patient outcomes**

Sickle cell disease (SCD) is one of the most frequent inherited genetic disorders in the world. It predominantly affects people of African descent as well as individuals from the Middle East, India, and Mediterranean regions [28]. It is an autosomal-recessive disease caused by a point mutation in the hemoglobin beta gene found on chromosome 11p15.5, Hb S (HBB: c.20A>T) along with or without any other abnormal Hb gene, and results in a number of health problems, for example, anemia, acute and chronic pain, infection, acute chest syndrome, pulmonary hypertension, cardiac, CNS, gastrointestinal involvement, and so on, leading to significant morbidity and mortality. Significant advances in prophylactics and therapy achieved improved survival among children with sickle cell disease, with the majority of children attaining adulthood [29]. However, the median age at death of 39 years with only 35.0% surviving beyond age 35 years was reported by the Centers for Disease Control (CDC). Sickle cell disease substantially alters renal structure and function leading to nephropathy which is not only a chronic comorbidity but is also one of the leading causes of mortality in patients with sickle cell disease [30]. Knowledge of the natural progression of the disease, as well as identification of persons at risk, allows for timely intervention and improved outcomes. The search for biomarkers for the early diagnosis of the disorder and its outcomes is an area of intense contemporary research [31]. The current understanding of the presentation, diagnostic, and therapeutic challenges in sickle cell nephropathy is presented in detail by Inusa Baba et al. in the chapter 8. Risk factors for renal impairment and acute kidney injury are reviewed in detail. In addition, data coming from established mouse models are invaluable to elucidate the pathogenesis of SCD-associated multiple organ complications and to identify targets for prevention and therapy.

The continuous and rather extensive influx of new information regarding the key features and underlying mechanisms as well as treatment options of blood disorders requires a frequent updating of this topic. The primary objective of this book is to provide the specialists involved in the clinical management and experimental research in hematological diseases with comprehensive and concise information on some important theoretical and practical developments in the biology, clinical assessment, and treatment of patients, as well as on some molecular and pathogenetic mechanisms and the respective translation into novel therapies. Specific clinical scenarios such as myeloid sarcoma or sickle cell nephropathy are also within the scope of this book. An international panel of experts provides novel insights of various aspects of hematology and contributes their experience to an update of the field.

Each chapter is a separate publication that reflects each author's views and concepts. However, this book presents an update and introduces novel insights in our current understanding of the biology and clinical presentation, the risk assessment, and therapeutic challenges in patients with hematological diseases.