Analysis of Surface Roughness of EN AW 2024 and EN AW 2030 Alloys after Micromachining

*Francisco Mata and Issam Hanafi*

## **Abstract**

Micromachining is the most suitable technology for the production of very small components (micro-components) in the industry. It is a high-precision manufacturing process with applications in various industrial sectors, including machine building. This chapter presents the experimental study of the roughness (Ra and Rt) of aluminum alloys using a specific micro-turning process. The roughness measurements carried out show how it is possible to achieve very good surface qualities up to 0.05 mm diameter. For lower diameters, the surface quality worsens and the shape defects increase (conicity) due to the very low rigidity of the workpiece, which makes it very sensitive when passing through the forming process. The fundamental objective of this research is to analyze the surface quality of the finishes obtained in these micromachining processes and to evaluate their suitability to the specifications required by the mechanical industry (roughness, presence of burrs, shape and geometry, etc.). Predictive roughness models are proposed, with a good degree of approximation, to help characterize micromachining processes.

**Keywords:** micromachines, micro-turning, miniaturization, models

## **1. Introduction**

The traditional machine concept, consisting of large mechanical elements with high energy consumption, low precision, and little degree of automation, has given way to much more complex realities in the integration of technologies (mechanical, pneumatic, electronic, etc.), in the reduction of sizes and consumption, and of course, in the possibility of performing high-precision operations with exhaustive controls. In this context, it is possible to speak of micromachines, which are small machines to develop operations of precision and are integrated by mechanisms and components of very small size. Consider, for example, the machinery of a watch or the injection systems used in the automotive industry. It is therefore necessary to manufacture components of very small dimensions, that is, micro-components for applications in the mechanical, biomedical, automotive, or mechatronic industries, among others.

The development of new materials with high performance, their study at micro- and nanotechnological scale, and the continuous attempt to achieve as compact designs as possible support the need to advance manufacturing processes on this scale [1]. The miniaturization of components has become a specialty within the design and micro-manufacturing, a discipline also differentiated, involving machines, tools, and measuring equipment that must necessarily be adapted to the particularities of this type of conformation. This implies a growing demand for the integration needs of microscale components manufactured using different materials, including metals and their alloys [2–5].

Micro-fabrication can be carried out using adapted traditional shaping techniques (microinjection), by chip removal in machine tools (using tools of appropriate geometry), or using other advanced conformation techniques (laser, ultrasound, photochemical forming, thermal diffusion, electric discharge, etc.) [5]. Machining meso (<10 mm) and micro (<1 mm) are the most suitable technologies for the production of very small components in the industry [1–7], especially when high surface finishing and dimensional tolerances are required. These are high-precision manufacturing processes with applications in leading sectors such as the following [7, 8]:


In elements and microelements that have to integrate mechanisms, where there must be contact and relative movement between them, the surface finish becomes critical in addition to the precise dimensional adjustments. The small size of some of these elements and their peculiar shape, together with the specification of a good surface finish that prevents premature wear, requires opting for micro-conforming processes such as turning or milling, essentially. It should be added that the machining of micro-workpieces does not necessarily involve the use of small-volume machine tools ("micro-lathes" or "micro-milling machines"); micromachining operations can be developed in the conventional CNC machines and therefore it is important to carry out experimental studies leading to the characterization of these processes (establishment of limits to ensure the integrity and quality of machined workpieces, definition of appropriate functional cutting parameters, study of the geometry of cutting tools, determination of achievable surface quality levels, etc.)

The study of surfaces is a technique for characterizing materials, which is very useful in practice. Surface roughness is a parameter that has a great influence on the behavior and functionality of mechanical components and on production costs [9, 10], constituting an important quality control variable. Roughness is critical in

### *Analysis of Surface Roughness of EN AW 2024 and EN AW 2030 Alloys after Micromachining DOI: http://dx.doi.org/10.5772/intechopen.93560*

mechanical contacts in addition to other fields such as fluid circulation or biomedical applications. The surface roughness obtained during the machining process is affected by the cutting parameters, tool wear, and material hardness. To achieve the desired roughness, it is necessary to know the mechanisms of the cutting and detachment of the material and the kinetics of machining processes, which affect the performance of the cutting tools [11].

In most applications of the machined micro-workpieces, high quality is required on shaped surfaces, including dimensional accuracy and surface integrity. For this reason, it is necessary to carry out various investigations with the aim of optimizing the cutting parameters in order to obtain a certain roughness [9, 12] and tolerable formal characteristics (cylindricity).

Conventional micromachining is a flexible approach that can use any material that can be machined [13]. However, it has some restrictions on the development of components [14]. It is therefore necessary to investigate, to develop models that allow to optimize the processes, and to improve the quality of the products and to lower the production costs.

In order to reduce the number of tests required for a complete characterization of micromachining processes, statistical nonlinear regression techniques, numerical strategies based on neural networks or other similar techniques can be used [15–19], which will allow us to establish prediction models and help us to better understand cutting mechanisms. Based on these models, the experimental program can be completed in order to know the particularities of the micromachining processes and to define the corresponding physical cutting models.

In recent times, due to environmental requirements, these processes are carried out in the absence of cutting fluids [20]. However, the total suppression of fluids results in very aggressive process conditions [21–23]. Each alloy has its own characteristics of machinability, which will mark the operational limits of the process. Although conventional machining processes for metals and their alloys are therefore well known, it is not possible to make a direct extrapolation and anticipate what the behavior will be in the event of chip removal operations on very small workpieces. In these cases, the geometry of the tool and the stability of the workpiece (lean:stiff ratio) can significantly influence the results and differentiate the behavior pattern from the conventional machining of standard size workpieces.

The main objective of this research is to analyze the surface quality of the finishes obtained in these micromachining processes and to evaluate their suitability to the specifications required in micro-components of different devices and machines (roughness, presence of burrs, shape and geometry, etc.). Nonlinear models are proposed in this study that can help in the characterization of micromachining processes, depending on the diameter required for a given application as well as the necessary surface quality.

## **2. Materials**

Aluminum (Al) has a combination of properties that make it very useful in mechanical engineering, such as its low density (2700 kg/m3) and its high resistance to corrosion. Its mechanical strength (up to 690 Mpa) can be significantly increased by suitable alloys. Aluminum alloys are a viable alternative in improving flexibility and competitiveness. The current trend is its gradual incorporation into the definition of industrial cycles incorporating high-speed machines, advanced CNC, and specific aluminum alloys. The intrinsic characteristics of aluminum alloys favor high-speed machining with feed and cut speeds much higher than those achieved with ferrous alloys.


## **Table 1.**

*Chemical composition of tested aluminum alloys.*


#### **Table 2.**

*Mechanical properties of tested aluminum alloys.*

As far as possible, metal carbide tools should be used for turning, as they offer higher productivity and a longer service life.

This type of alloy has applications in dental prostheses, micro-valves, actuators and other instrumentation components, injectors of different motors, precision mechanisms, and in general, components of micromachines.

Commercial EN AW 2024 and EN AW 2030 aluminum alloys are used for the experiments. Chemical composition and some mechanical properties of tested aluminum alloys are given in **Tables 1** and **2**.

## **3. Experimental procedure**

The micro-turning process has been carried out on an Eclipse CNC Lathe, with a power of 1.5 Kw and 4000 rpm maximum rotation speed of the head (**Figure 1**).

To measure roughness (mean roughness: Ra, and maximum roughness: Rt), given the very small diameter of the machined workpieces, a Talysurf CLI roughness meter (**Figure 2**) has been used for topographic exploration, using an inductive contact sensor or noncontact laser meter. A conventional optical microscope (**Figure 2**) has been used for the observation of conicity and cylindricity.

## **Figure 1.**

*Eclipse lathe used in micro-turning tests. Left: Equipment. Right: Example of turning program followed.*

*Analysis of Surface Roughness of EN AW 2024 and EN AW 2030 Alloys after Micromachining DOI: http://dx.doi.org/10.5772/intechopen.93560*

For cutting tools, SDCR2020K-07 and finishing insert have been used, with the characteristics reflected in **Figure 3**.

The cutting parameters used were as follows: cutting speed: 500 rpm, feed rate: 0.002 mm/rev, and depth of cut: 0.001 mm. The diameter of the test pieces ranged from 0.5 to 0.025 mm, with lengths ranging from 10 to 5 mm, in order to keep a minimum value of the L/D ratio (length/diameter). **Figure 4** shows some details of turning tests and shows the relative size of machined workpieces.

**Figure 2.**

*Measuring equipment. Left: Talysurf CLI roughness meter. Right: Optical microscope.*

**Figure 3.** *Cutting tool geometry.*

In certain applications, such as those where precise adjustments have to be made in the component assembly process, it is essential to be able to obtain accurate diameters in accordance with the technical specifications laid down in the relevant project. For this purpose, it is necessary to use techniques to characterize the quality of the parts, including the study of roughness, the determination of the degree, or percentage of conicity-cylindricity and dimensional precision.

## **4. Mathematical models for prediction**

Finally, as regards the treatment of the results, it is possible to establish mathematical models of prediction, which can be very useful to characterize the processes, while serving as a practical guide for the development of the same, setting certain cutting conditions, materials, tools, etc. When measuring the accuracy of the estimate and the predictability, account shall be taken of the following:

The sum of squares of errors (SSE), which is the sum of squares of the deviations of the residue values from their sample mean.

Multiple coefficient determination, R2 , and R2 adjusted, are some common measures in regression analysis, denoting the percentage of variance justified by independent variables. The adjusted R2 takes into account the size of the data set, and its value is slightly lower than its corresponding R2 .

The validation process was performed by comparing the observed values and the estimated values using the different methods through the mean quadratic error (RMSE).

## **5. Results and discussion**

#### **5.1 Analysis of experimental data**

After the micro-turning tests were carried out, the roughness was measured and the cylindrical properties of the machined parts were studied. **Table 3** shows the experimental results of the roughness parameters, Ra and Rt, for the two materials, depending on the diameter of the workpiece.

As can be seen, and especially significantly in the mean roughness (Ra), the roughness is maintained at low and almost constant values as we reduce the diameter of the workpiece, up to 0.2 mm. For lower values, there is an increase in roughness, especially for values of 0.05 mm and below. This increase is due to the low rigidity of the workpieces and the sensitivity to vibrations.


**Figure 5** shows an example of roughness profile obtained.

**Table 3.** *Experimental roughness values.* *Analysis of Surface Roughness of EN AW 2024 and EN AW 2030 Alloys after Micromachining DOI: http://dx.doi.org/10.5772/intechopen.93560*

**Figure 5.** *Example of the obtained roughness profile.*

The appearance of the surface and the machining marks can be seen in **Figure 6**. As regards the preservation of the formal characteristics of the workpieces, the conicity (%) has been calculated with the help of increased images. The conicity, as a function of length and diameter, is calculated using Eq. (1). The results are presented in **Table 4**.

$$\mathcal{L}\left[\%\right] = \mathbf{100}\frac{D}{L} \tag{1}$$

It is observed that the conicity values are generally low, although they may not become manageable in certain applications. The conicity or "cylindricity defect" is increased by reducing the diameter of the workpiece, mainly due to the increased sensitivity of the workpiece as it passes through the machining process. It can also be seen how the conicity values are always lower in the case of titanium alloy, which may be due to its greater rigidity and its greater ease for micromachining (an interaction of the cutting tool with the micro-workpiece is expected to be somewhat more "fluid," which should probably translate into lower values of the cutting forces).

**Figure 6.** *Workpiece (450 magnifications), diameter: 0.2 mm.*


**Table 4.**

*Evolution of conicity according to the diameter of the workpiece.*

**Figure 7** shows the detail of the graphical treatment performed to measure conicity. It is important to use an appropriate "length-to-diameter" ratio to reduce conicity, vibration and improve the surface quality of machined workpieces.

## **5.2 Prediction models**

The mathematical models developed for the prediction of the roughness parameters, Ra and Rt, are presented below.

$$Ra = 2, \mathbf{1} \, \mathbf{8} \, \mathbf{8} \times \mathbf{10}^{\cdot 8} \times \mathbf{d}^{\cdot 5.167} + \mathbf{1}, \mathbf{377} \tag{2}$$

$$Rt = 63,98 \times 10^{10} \times \exp\left(-868,9 \times \text{d}\right) + 22,4 \times \exp\left(0,3462 \times \text{d}\right) \tag{3}$$

$$Ra = \mathbf{1}, \mathbf{35} \star \exp\left(\mathbf{4}, \mathbf{16} \star (\mathbf{-128}, \mathbf{47}) \star \mathbf{d}\right) \tag{4}$$

$$Rt = 21,62 \text{ + } \exp\left(5,45 \text{+} (\text{-}105,037) \text{\textdegree d}\right) \tag{5}$$

**Table 5** reflects the measures of the goodness of the estimate and the predictability, using the parameters SSE, RMSE, R<sup>2</sup> , and R2 adjusted.

As can be seen, the values indicate that the estimates made are generally very good. **Figures 8** and **9** show the experimental roughness values of micromachined

**Figure 7.** *Obtaining conicity.*


*Analysis of Surface Roughness of EN AW 2024 and EN AW 2030 Alloys after Micromachining DOI: http://dx.doi.org/10.5772/intechopen.93560*

**Table 5.**

*Validation of proposed nonlinear models.*

**Figure 8.**

*Experimental and predicted roughness values as a function of the diameter of the workpiece. (a) Ra and (b) Rt for EN AW 2024.*

#### **Figure 9.**

*Experimental and predicted roughness values as a function of the diameter of the workpiece. (a) Ra and (b) Rt for EN AW 2030.*

surfaces (Ra and Rt) for EN AW 2024 and EN AW 2030 as one with the representation of prediction models versus the diameter of the workpiece. In all cases, it is observed how the proposed models adjust the range of the experimental values with great approximation.

## **6. Conclusions**

The roughness of machined surfaces is the best indicator of product quality and provides relevant information on their potential for application in different sectors. This work is part of a research on the micro-turning of these materials with the aim of evaluating up to what diameters it is possible to work with conventional finishing

## *Analysis of Surface Roughness of EN AW 2024 and EN AW 2030 Alloys after Micromachining DOI: http://dx.doi.org/10.5772/intechopen.93560*

tools. Certainly, better behavior is to be expected when specific tools are used for micro-turning. However, low surface roughness values are generally obtained, enabling the specifications of a significant number of practical applications where dimensional accuracy is critical. Among these applications are components and micro-components used in the construction of micromachines (micro-axes, bearing needles, etc.) and, in general, small instrumentation parts, injection systems, etc.

The results obtained allow us to conclude that it is possible to conform by chip removal very small revolution pieces (0.05 mm in diameter) with these alloys, guaranteeing very good surface qualities according to the typical specifications of these applications. It is important to note that the deformation progress used is very low, which has undoubtedly contributed to low roughness values. The use of low values of feed rate and low depths of cut allows cutting forces of very small values in order to guarantee the integrity of the machined workpieces (there is obvious risk of plastic or even fracture if not). On the other hand, the proposed models show very good adjustments as corroborated by the indicators of goodness.

## **Author details**

Francisco Mata1 \* and Issam Hanafi2

1 University of Castilla-La Mancha, Almadén, Spain

2 National School of Applied Sciences Al-Hoceima (ENSAH), Al-Hoceima, Morocco

\*Address all correspondence to: francisco.mcabrera@uclm.es

© 2020 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.

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## **Chapter 8**

## Resistance Welding of Aluminium Alloys with an Electromechanical Electrode Force System

*Zygmunt Mikno*

## **Abstract**

The idea presented in this chapter is an innovative welding machine electrode force system. The operation, advantages of the new solution and the optimisation of the welding process were illustrated by the welding of aluminium bars (5182) (ø 4 mm). The solution involves controlling the force and/or displacement of welding machine electrodes. The modulation of electrode force significantly improves welding, particularly as regards aluminium alloys (requiring a very short welding process). The tests involved the numerical analysis of two electrode force systems, i.e. a conventional Pneumatic Force System (PFS) and an Electromechanical (Servomechanical Force) System (EFS). The numerical tests were performed using SORPAS software. FEM calculation results were verified experimentally. The technological welding tests were conducted using inverter welding machines (1 kHz) equipped with various electrode force systems. The research included metallographic and strength (peeling) tests and measurements of characteristic parameters. The welding process optimisation based on the EFS and the hybrid algorithm of force control resulted in i) more favourable space distribution of welding power, ii) energy concentration in the central weld zone, iii) favourable melting of the material within the entire weld transcrystallisation zone, iv) obtainment of the full weld nugget and v) longer weld nugget diameter.

**Keywords:** resistance welding of aluminium, electromechanical force system, cross-wire welding, projection welding, electrode force, FEM

## **1. Introduction**

Force constitutes one of the most important parameters in the resistance welding process. The remaining parameters include current and current flow time. During cross-wire projection welding (particularly of aluminium alloys) involving the use of a conventional application, i.e. the pneumatic force system (PFS), it is very difficult, nearly impossible, to make a weld containing the full weld nugget. Aluminium, when subjected to welding, gets plasticised very quickly, which is responsible for the formation of the excessively large area of contact between welded elements and, consequently, results in a rapid decrease in current density. These are not favourable conditions for the melting of materials. In addition, the PFS is characterised by high inertia and the impossibility of performing fast changes in force during current flow. For this reason, the value of preset force is usually constant and unfavourably too high. If the aforesaid force is excessively high, the high deformation of welded elements (bars) may occur as a result. The overly low force may lead to the formation of projection joint imperfections (such as expulsion caused by high temperature in contact areas) [1]. In the PFS, force applied during the welding process results from specific force preset by a pneumatic cylinder. The displacement of electrodes results from the action of this force and the changeable mechanical resistance of materials subjected to welding. A significant disadvantage of the above-presented method of control is the fact that neither force nor displacement (during the flow of current) is actually controlled.

An alternative solution requires another method making it possible to carry out faster changes in force during the welding of materials [1–3]. In publication [1], the authors emphasise the growing popularity of the electromechanical (servomechanical) force system (EFS) and an advantage consisting in an increase in an electrode displacement rate during welding. In publication [2] the authors inform about the possible extension of the window of technological parameters, improving the weldability of materials. In work [3, 4] the authors mention the possible modulation of force and its fast changes, particularly at the final stage of the welding process. The authors stress an increase in electrode service life in spot resistance welding and the application of servomotors in the riveting technology [5]. In publications [3, 6] authors state that the EFS has eliminated the dynamic impact of electrodes against a welded material (during the exertion of initial force), which was characteristic of pneumatic actuators. The EFS has enabled a gentle "touch" of an electrode against a material being welded. In work [3] the authors enumerate other advantages of the EFS including (i) superior (faster) operation of a welding gun (servo) in space, (ii) greater repeatability of force, (iii) reduced noise, (iv) shorter welding time and (v) shorter movement during the closing and opening of the electrodes, extending the service life of related mechanisms.

The tests discussed in the article aimed at replacing the PFS with the EFS. It was also important to appropriately control the servomotor in order to perform the controlled movement/shift of electrodes, particularly during the flow of current. The control process has changed considerably, i.e. the displacement of electrodes is a preset parameter and resultant force depends on the displacement of electrodes and the resistance of the deformation of a contact area being heated. Available reference publications do not contain information about such a method of electrode movement control as that presented in this study.

The authors [7, 8] describe a new control system and the results of its operation, particularly noticeable in projection welding. In [7, 9] the authors refer to a new control system applied when welding sheets with an embossed projection. Another use of the new solution, i.e. cross-wire welding, and the welding of nuts are presented in publications [10–12] respectively.

In publications [7–12] the authors present a completely different solution, i.e. the slowing down of the displacement of an electrode during the projection welding of sheets with an embossed projection. This approach is new and characterised by advantages which are definitely worth mentioning. The above-named idea can be used in relation to aluminium alloys as these materials require a very short welding time (50 ms). It is possible to decrease the penetration of bars and to generate more energy in the optimum place, i.e. in the contact area between the bars. The new idea of electrode displacement control significantly alters the previous approach to the course of the resistance welding process (projection cross-wire welding) and considerably influences the development of the entire research area (pressure welding).

*Resistance Welding of Aluminium Alloys with an Electromechanical Electrode Force System DOI: http://dx.doi.org/10.5772/intechopen.93242*

## **2. Characteristics of welding machine electrode force systems (EFS and PFS)**

The essence of the EFS (in comparison with that of the PFS) involves a significantly higher rate of changes, i.e. changes in the force and/or displacement of electrodes. During the resistance welding process, the aforesaid approach is of significant importance because of the fact that the time of welding current flow in typical applications is very short and amounts to 0.2 s (200 ms). The optimisation (improvement) of the welding technology requires the modulation (change) of electrode force during the above-named time. Regrettably, as regards the conventional electrode force system (PFS), common in industrial applications, such modulation is impossible because of the significant inertia (delay) of this solution. **Figure 1** presents exemplary courses of electrode force and displacement in relation to the PFS (dashed line) and EFS (full line). The aforesaid courses refer to two operating modes, i.e. the approach mode and the force mode. The time necessary to obtain previously adjusted electrode force, i.e. electrode force stabilisation time (EFST), by the PFS exceeds 200 ms. The EFST parameter related to the EFS is significantly shorter and restricted within the range of 50–80 ms, depending on the configuration of the EFS (servomotor power, gear etc.). An important characteristic of this solution is the possibility of modulating the course of electrode force during the flow of current, which is nearly impossible as regards the PFS.

The EFS can be controlled in two different manners, i.e. using an algorithm enabling the control of force and an algorithm enabling the control of the (electrode) displacement rate. The first of the algorithms is already used in industrial practice. The time of delay in the stabilisation of preset electrode force is restricted within the range of 50–80 ms. In such an operating mode, it is possible to modulate force and obtain two or three different values (in CFT amounting to 200 ms).

#### **Figure 1.**

*Comparison of the EFS and PFS based on exemplary courses of electrode force and displacement in relation to operating modes: (a) approach mode and (b) force mode [13].*

The aforesaid time (50–80 ms) depends on the configuration of the EFS (motor, gear) and on the preset value of force. In turn, the second algorithm (developed by the author) has been used to weld demanding (in the aforesaid respect) materials, i.e. aluminium alloys. Until today, the author has not come across any information concerning the method of control presented in this chapter.

The unique characteristic of the EFS and of the solution is a special algorithm, where the control of the displacement of electrodes results in the exertion of electrode force. In the above-named algorithm of control, delays between preset and actual values are counted in milliseconds, making it possible to develop a very fast algorithm enabling the exertion of variable (electrode) force [9]. The abovepresented manner of controlling the force of electrodes through the control of their displacement alters previous views on methods enabling the control of force (movement of electrodes) in the resistance welding process.

## **3. Methodology of numerical and experimental tests**

The crosswise projection welding of aluminium bars (Al 5182) performed using the PFS was subjected to numerical analysis verified experimentally and aimed to subsequently optimise the welding process performed using the EFS system. The assumed acceptance criteria included (i) obtainment of the full weld nugget having a diameter of not less than 1.5 mm, (ii) lack of deformation and the penetration of the bars less than 20% of the diameters of elements subjected to welding (ΔlPP = 1.6 mm), (iii) lack of overheating in the area of contact between the electrode and the material being welded (Te-m max ≤ 500°C), (iv) lack of expulsion and (v) maximum current flow time tPP max = 63 ms. An additionally expected result was the reduction of (welding) current flow time.

The material of bars subjected to welding and adopted in FEM-based calculations was aluminium alloy grade 5182 with solidus (temperature) being 577°C and liquidus amounting to 638°C [14]. The chemical composition of the aluminium alloy grade Al 5182 used in the bars is presented in **Table 1**.

#### **3.1 FEM calculations**

The numerical calculations were performed using the SORPAS® 3D software program [15]. The calculations were carried out for ¼ of the model and its mirror reflection in relation to the plane determined by x-z-axes and y-z-axes (**Figure 2**). The mesh in the area of contact between the elements (bars) subjected to welding was concentrated in order to provide the appropriate accuracy of calculations. The lack of proper mesh density resulted in the lack of contact between the elements subjected to welding and, consequently, incorrect calculations.

### **3.2 Numerical (FEM) model**

The numerical model of the crosswise welding of bars is presented in **Figure 2**. The calculations were performed using the 3D model [15].


**Table 1.**

*Chemical composition of the materials subjected to welding, i.e. bars made of aluminium alloy grade Al 5182.*

*Resistance Welding of Aluminium Alloys with an Electromechanical Electrode Force System DOI: http://dx.doi.org/10.5772/intechopen.93242*

**Figure 2.** *Model (3D) of the crosswise welding of aluminium bars (Al 5182).*

The numerical calculations included the analysis of (i) waveforms of dynamic resistance and momentary power, (ii) energy supplied to the weld, (iii) diameter and volume of the molten material of the weld nugget, (iv) displacement of electrodes (penetration of bars), (v) expulsion (if any) and (vi) temperature in the electrode bar contact area (Te-m, point 251—**Figure 2a**). The primary objective included the determination of the most favourable space distribution of welding power enabling the melting of the material in the central zone of the joint (to obtain the full weld nugget). As in all other cases of projection welding, the aspect of particular importance was the beginning of the welding process, i.e. the beginning of welding current flow.

## **3.3 Process parameters**

The assumptions adopted in the numerical model included (i) copper electrodes (A2/2) and (ii) elements subjected to welding, i.e. aluminium (grade Al 5182) bars having a diameter of 4 mm and a length of 12 mm (**Figure 2a**). The 3D model was composed of approximately 9000 elements. To ensure the required accuracy of calculations, it was necessary to concentrate the mesh in the area of contact between the bars (**Figure 2b**).

Data related to the electrodes and materials subjected to welding and used in the FEM calculations were obtained from the SORPAS software program database (**Table 2**) [14]:


Based on the present recommendations and guidelines concerning the crosswise projection welding of bars, the following ranges of parameters were adopted for:



#### **Table 2.**

*Parameters of the SORPAS software program used in numerical (FEM) calculations.*

The numerical calculations were performed in relation to a DC inverter welding machine (1 kHz). The remaining welding cycle parameters are presented in **Table 2**. **Table 5** presents the preset parameters of the welding cycle and the parameters characteristic of variants selected for FEM calculations.

The PFS variants are designated as P1 ÷ P9 (P, pneumatic system), whereas the EFS variants are designated as E1 ÷ E3 (E, electromechanical system). The analysis of the welding process performed in relation to the PFS aimed to investigate and depict the variability of process parameters and determine the most favourable welding conditions (MFWC). The results of the analysis revealed the lack of the monotonicity of the weld nugget growth (**Figure 4a**) visible in relation to a force of 0.75 kN. For this reason it was necessary to perform additional calculations in this area, i.e. for a value of 0.7 kN and that of 0.8 kN. In total, the analysis of the process was focused on 35 points (I = 8/9/10/11/12 kA, F = 1.5/1.25/1.0/0.8/0.75/0.7/0.5 kN).

The numerical optimisation concerning the process involving the use of the EFS was performed for lower values of current than those analysed in relation to the PFS (8.0 ÷ 10.0 kA). The numerical calculations were continued until the occurrence of one (of six) previously adopted boundary conditions.

#### **3.4 Experimental tests**

The experimental tests were performed using inverter welding stations (DC 1 kHz) shown in **Figure 3a** (PFS) and **Figure 3b** (EFS). The welding parameters were recorded using a LogWeld 4 measurement device.

The results obtained in the numerical calculations were verified experimentally. The experimental tests involved nine variants (P1–P9) from **Table 5** (PFS). All of the variants (**Figure 6**) were subjected to destructive tests (peeling), confirming the



*Resistance Welding of Aluminium Alloys with an Electromechanical Electrode Force System DOI: http://dx.doi.org/10.5772/intechopen.93242*


*Advanced Aluminium Composites and Alloys*

**Table 4.**

 *Material parameters of electrodes ISO 5182 A2–2 electrode CuCrZr [14].*


 **5.** *weldingcycleparametersandparameterscharacteristicofselectedvariantsintheFEMcalculationsrelatedtothePFSandEFS*

**Table**

*Preset* 

 *(FEM).*

*Resistance Welding of Aluminium Alloys with an Electromechanical Electrode Force System DOI: http://dx.doi.org/10.5772/intechopen.93242*

#### **Figure 3.**

*Welding machine stations: (a) SPD: (1a) inverter welding power source Harms & Wende (25 kA, 1 kHz), (2a) welding machine housing ASPA (5.5 kN), (3a, 4a) measurement device LogWeld 4, (5a) pneumatic actuator, (6a) head for measurements of electrode force, (7a) laser sensor for displacement measurements, (8a) welding current measurement sensor and (9a) leads for measurements of welding voltage. (b) SED: (1b) electromechanical welding machine F = 2 kN, (2b) servomotor, (3b) linear gear, (4b, 5b) measurement device LogWeld 4 and (6b) electrode force measurement module.*

#### **Figure 4.**

*Variability of characteristic parameters in relation to the PFS (Al 5182, ϕ = 4 mm, MES) [11]: (a) weld nugget diameter, (b) current flow time, (c) displacement (of electrodes - penetration of bars), (d) energy (of welding).*

*Resistance Welding of Aluminium Alloys with an Electromechanical Electrode Force System DOI: http://dx.doi.org/10.5772/intechopen.93242*

formation of the ring weld. However, none of the PFS variants satisfied the previously assumed criteria. Nonetheless, in spite of the exceeding of the previously assumed value of bar penetration and the obtainment of the ring weld, variant P5 was adopted as the reference variant for further optimisation-related activities. The reason for such a choice resulted from the fact that the aforesaid variant (P5) enabled the obtainment of the longest weld nugget diameter. Parameters similar to those used with reference to variant P5 were used in additional technological welding tests (**Table 6**, PE1–PE3). The results related to the preset parameters of the technological cycle and characteristic parameters of selected welding tests involving the use of the PFS and variants PE1–PE3 are presented in **Table 6**.

The welding cycle parameters used in relation to variants PE1–PE3 included electrode force F = 1.0 kN, welding current I = 9.0–10 kA and welding time tPP = 43–63 ms. The metallographic tests involving the above-named variants confirmed the results obtained in the numerical calculations, e.g. the ring-like shape of the weld nugget.

Key: Irms, root-mean-square current; PE, pneumatic experiment.

## **4. Process optimisation**

The optimisation of the crosswise projection welding of bars was performed using the EFS. The primary criterion of the optimisation process involved the obtainment of the full weld nugget having a diameter of not less than 1.5 mm. The optimisation process assumed the use of the EFS and, in addition, the adjustment of the lowest possible value of welding current.

The optimisation process also aimed to adjust appropriate and lower electrode force than that applied initially in the process performed using the PFS and to control the displacement of the electrodes so that it could be possible to obtain the most favourable space distribution of welding power, i.e. ensuring the emission of appropriately more heat (energy) in the central part of the contact area between elements being welded (in order to melt the material of these elements) [10, 11].

The preset welding cycle parameters (grey) and the parameters characteristic of the technological welding tests performed using the EFS are presented in **Table 7**. The technological welding tests were performed using a current of approximately 8.0 kA, i.e. the lowest value analysed in relation to the welding process performed using the PFS. The aforesaid value of current applied in the PFS, within the entire range of analysed values of electrode force (0.5 kN ÷ 1.5 kN), was insufficient to melt the material of the elements subjected to welding. The welding process was optimised using the EFS and a welding current of 8.0 kA and that of 8.5 kA as well as the appropriate profile of electrode force (variants EE1 and EE2, **Table 7**).

## **5. Results**

#### **5.1 FEM calculation results**

The PFS-related numerical calculation results are presented in **Figure 4** and **Table 8**. The results are presented in spatial diagrams developed using the Statistica software program [19]. **Figure 4** presents (in the form of a spatial diagram) the formation of the weld nugget diameter (**Figure 4a**), welding time (**Figure 4b**), bar


**Table 7.** *Preset and* 

*characteristic*

 *parameters*

 *of the EFS* 

*(experiment)*

 *[11].*

## *Advanced Aluminium Composites and Alloys*

**234**

*Resistance Welding of Aluminium Alloys with an Electromechanical Electrode Force System DOI: http://dx.doi.org/10.5772/intechopen.93242*

penetration depth (electrode displacement) (**Figure 4c**) and welding energy (**Figure 4d**). The correlations are presented in relation to various values of welding current and electrode force.

Numerical values related to the graphic representation of the results presented in **Figure 4** are presented in **Table 8(a-d)**, containing, in addition, information about the following:

	- a. current flow time
	- b. displacement (of electrodes penetration of bars)
	- c. welding energy.

The results presented in **Table 8** supplement the information concerning the (course of) variability of the characteristic parameters from **Figure 4**.

**Table 8** also contains the numerical calculation results obtained for the EFS (green). In relation to all of the previously assumed parameters, the conditions concerning the optimised method of control were satisfied.

The comparison of the FEM calculation results (in the form of the distribution of temperature) related to the two (i.e. PFS and EFS) electrode force systems, different values of welding current (8.0 and 10.0 kA) and various ranges of temperature (20–638°C and 577–638°C) is presented in **Figure 5**.

#### **5.2 Experimental test results**

The PFS-related technological welding tests involving the aluminium bars were performed in relation to all of the nine variants P1–P9 from **Table 5**. The results after the peeling tests are presented in **Figure 6**.

Parameters similar to those used with reference to variant P5, i.e. in relation to which the longest weld nugget diameter was obtained, were used in additional technological welding tests performed in relation to a wider welding current range of 9.0–10.0 kA. Results (in the form of metallographic structures) related to the above-presented parameters are presented in **Figure 7**. The preset



*Resistance Welding of Aluminium Alloys with an Electromechanical Electrode Force System DOI: http://dx.doi.org/10.5772/intechopen.93242*

#### **Table 8.**

*FEM calculation results concerning the crosswise projection welding of bars in relation to the PFS and EFS (AL 5182) [11].*

welding cycle parameters in relation to variants PE1 and PE3 are presented in **Table 6**.

In terms of the EFS, the technological welding tests were performed in relation to a current of 8.0 kA and that of 8.5 kA (**Table 7**, variants EE1 and EE2). The comparative results in the form of the metallographic structures of the joints are presented in **Figure 8a1**–**a2** and **b1**–**b2** (in relation to the PFS and EFS, respectively).

## **6. Discussion**

## **6.1 FEM calculations**

The PFS-related conclusions based on the analysis of the results presented in **Figure 4** and **Table 8** are the following:

**Figure 5.**

*Distribution of temperature in the welding area (FEM) in relation to: (a/b) PFS (I = 8 kA, F = 1.0 kN), (c) PFS (I = 10 kA, F = 1.0 kN) and (d) EFS (I = 8.0 kA, force exerted by the servomotor).*


*Resistance Welding of Aluminium Alloys with an Electromechanical Electrode Force System DOI: http://dx.doi.org/10.5772/intechopen.93242*

**Figure 6.** *Specimens after the peeling tests (PFS, variants P1–P9).*

**Figure 7.** *Results of the metallographic tests for the PFS (F = 1 kN, I = 9.0/10.0 kA).*

### **Figure 8.**

*Metallographic test results in relation to [11]: (a) PFS, (a1) variant PE1 and (a2) variant PE3; (b) EFS, (b1) variant EE1 and (b2) variant EE2.*


The crucial aspect which remained was the failure to satisfy the principal criterion, i.e. the obtainment of the full weld nugget having a diameter of 1.5 mm. The analysis of the FEM-based calculation results, presented in **Figure 5**, is as follows:

• In relation to the PFS, a welding current of 8.0 kA and a force of 1.0 kN, **Figure 5** presents the distribution of temperature within the entire range of temperature subjected to analysis, i.e. from ambient temperature to the melting point (liquidus) (**Figure 5a**). In such an approach, within the range of temperature, the melting of the material did not take place, and the weld nugget diameter calculated by the SOPRPAS software program amounted to a mere 0.2 mm. **Figure 5b** presents the distribution of temperature within the range of *solidus* (577°C) to *liquidus* (638°C). In the above-presented approach, within the entire range of welding time, it was impossible to obtain the melting of the material. As a result, the solid-state joint was formed within the entire area of contact.

*Resistance Welding of Aluminium Alloys with an Electromechanical Electrode Force System DOI: http://dx.doi.org/10.5772/intechopen.93242*


## **6.2 Experimental tests**

In relation to the EFS and variants EE1 and EE2 from **Table 7**, it was possible to obtain the melting of the material within the entire area of the weld. Importantly, the melting of the material took place in the central (most favourable) part of the welded joint. The obtained weld nugget diameter exceeded the previously assumed value amounting to 1.5 mm (**Figure 8b1**–**b2**).

#### **6.3 Comparison of results**

The comparative metallographic test results concerning the PFS and EFS are presented in **Figure 8**. In relation to the PFS (**Figure 8a1**–**a2**), it was possible to observe the formation of the ring-shaped weld nearly within the entire range of technological cycle parameters (**Figures 6** and **7**). In terms of the EFS, the material subjected to welding was melted in the central part of the joint, and the weld nugget "grew" from inside towards outside.

## **7. Optimisation of the projection welding process illustrated with an example of the crosswise projection welding of bars**

Based on the FEM calculation and experimental test results, the optimisation of the crosswise projection welding of (aluminium) bars could be characterised as presented below. The process of optimisation was performed on the basis of characteristic courses/waveforms of related parameters (electrode force, momentary power, electrode displacement and the weld nugget diameter) in relation to the two (i.e. pneumatic and electromechanical) electrode force systems (**Figure 9**).

To present the issue in a more convenient manner, the comparison was based on the same value of welding current, i.e. 8.0 kA. It should be emphasised that in relation to the PFS, the aforesaid value was insufficient to obtain a proper joint. The melting of the material was nearly invisible (**Figure 5b**). In turn, as regards the EFS, it was possible to obtain the full weld nugget having the previously assumed diameter exceeding a minimum of 1.5 mm (**Figure 5d**).

Curves 1 and 3 in **Figure 9** refer to the PFS, whereas curves nos. 2 and 4 are related to the EFS. Curves 3 and 4 present the welding current waveform in relation to the PFS and EFS, respectively.

There was a strict correlation between the characteristic process parameters, where the change of one of them immediately led to changes in the remaining parameters. To explain the existing correlations, it was necessary to divide the analysis of the process into stages.

The PFS-related process could be described as follows. After adjusting the preset constant electrode force (**Figure 9a**, curve 1) as well as the specific value of welding current and the time of current flow (**Figure 9a**, curve 3), during the first stage subjected to analysis (K1), specific welding energy was generated (**Figure 9b**, curve 1). The waveform of the welding power (stage K2) had a direct effect (ultimately) on the specific displacement of the electrodes (**Figure 9d**, curve 1). At the subsequent stage (K3), the effect of the above-named factors led to the obtainment of the weld nugget characterised by a specific shape and the diameter of a mere 0.2 mm (**Table 5**, variant P4; **Figure 9c**, curve 1).

As regards the use of the PFS, the value of welding current amounting to 8.0 kA was overly low, only enabling the plasticisation of the material and resulting in an excessive increase in the area of contact between the elements subjected to welding.

#### **Figure 9.**

*FEM calculation results: (a) electrode force, (b) momentary power, (c) weld nugget diameter, (d) displacement of electrodes (bar penetration depth): —Curves 1 and 3, PFS (variant P1, I = 8.0 kA, F = 1.0 kN); —Curves 2 and 4, EFS (variant E1, I = 8.0 kA, force exerted by the servomotor).*

## *Resistance Welding of Aluminium Alloys with an Electromechanical Electrode Force System DOI: http://dx.doi.org/10.5772/intechopen.93242*

The foregoing led to a decrease in current density and, consequently, precluded the melting of the material subjected to welding. The material in the contact area was only heated and plasticised, whereas the maximum welding time amounting to 63 ms was exceeded.

The starting point for the optimisation of the crosswise projection welding of bars involved a *proper* change in the course of the displacement of electrodes (bar penetration depth) (**Figure 9d**, curve 2) resulting from the use of the EFS and the application of an appropriate algorithm enabling the control of the electrodes [9]. The essence of the new method of control, i.e. a change in the course of the displacement of electrodes, consisted in the direct control of the aforesaid parameters, particularly during the flow of welding current. The new method of control involved the exertion of lower electrode force at the beginning of current flow and a decrease (slowing down) in the rate of displacement (of electrodes) aimed to obtain, at the subsequent stage (K4), the more favourable distribution of power density as well as to generate higher welding power (**Figure 9b**, curve 2) in comparison with those accompanying the use of the PFS [10]. The slowed down displacement of the electrodes combined with constant welding current led to an increase in resistance in the contact area between the elements (materials) subjected to welding and, consequently, an increase in welding power.

At the subsequent stage (K5), the above-presented method of control translated into the more favourable course of electrode force (**Figure 9a**, curve 2). The obtained values of electrode force were lower than those accompanying the use of the PFS. It should be noted that electrode force directly affected the value of resistance in the contact area (particularly in the *welded bar-welded bar* configuration), which, in turn, led to the proper space distribution of welding power and energy. As a result, the area of contact between the elements subjected to welding was smaller, the resistance in the aforesaid contact area was higher, and the distribution of temperature in the welding area was more favourable. All of the abovepresented factors made it possible (at the final stage (K6)) to obtain the full wed nugget having the nominal diameter exceeding 1.5 mm (**Figure 9c**, curve 2). The aforesaid favourable outcome resulted from the more favourable distribution of temperature in the welding area, ultimately leading to the melting of the material and the formation of the weld nugget having the appropriately longer diameter.

The summary of the above-presented analysis concerning a welding current of 8.0 kA identified as overly low to obtain a proper joint using the PFS should contain a statement saying that the use of the EFS and the application of the appropriate control of electrode force and/or displacement (after satisfying the remaining requirements (quality-related criteria)) made it possible to significantly improve the welding process and obtain the full weld nugget having the diameter of a previously assumed length (> 1.5 mm).

## **8. Summary**

The adjustment of the most favourable parameters in the crosswise projection welding of bars performed using the PFS is extremely difficult, if not impossible, particularly as regards soft materials such as aluminium alloys. Electrode force is unfavourably excessively high in relation to necessarily short welding time (bars Al 5182 – 40–60 ms) and high welding current. Such conditions are mutually exclusive and constitute a significant obstacle when adjusting welding parameters. The primary limitation is the dynamics of the electrode force system, i.e. the impossibility of quickly controlling electrode force in short time, particularly during the flow of current.

A characteristic of the PFS is the fact that the preset parameter is (electrode) force and the resultant parameter is the displacement (of electrodes), not controlled in any way.

The improvement of the welding process (extension of the window of parameters) requires the use of the EFS. In the operating mode involving the displacement of electrodes, it is possible to set a more convenient trajectory of electrode movement, enabling the obtainment of the more favourable distribution of current density and the more favourable space distribution of welding power. This, in turns, translates into the generation of higher energy in the central area of the joint and, as result, the generation of higher temperature in the aforesaid area and, consequently, the obtainment of the full weld nugget having larger dimensions that those obtainable using the PFS.

The use of the EFS makes it possible to control the displacement of the electrodes during the flow of current, reach the final, previously assumed, position of the electrodes and exert lower final pressure (force) by the electrodes.

The FEM calculation results indicate the possibility of successful welding using even lower welding current than that used in the experimental verification (8.0 kA).

## **Acknowledgements**

This work was supported by the Polish National Centre for Research and Development (NCBR) under project no. TANGO1/267374/NCBR/2015 and co-funded by Łukasiewicz – Instytut Spawalnictwa, Poland.

## **Acronyms**


## **Glossary**

*Weld nugget* is a part of the spot, projection or seam weld molten during the welding process [20].

*Expulsion* signifies the expulsion (during welding) of the molten metal from the area of contact between elements subjected to welding or from the area of contact between the electrode and a given element subjected to welding [21]. *Welding area* in spot or projection welding (e.g. of sheets with an embossed projection) is the area including the weld nugget, heat affected zone (HAZ) as well as the area of contact between the electrode and the material subjected to welding along with adjacent areas.

*Resistance Welding of Aluminium Alloys with an Electromechanical Electrode Force System DOI: http://dx.doi.org/10.5772/intechopen.93242*

## **Author details**

Zygmunt Mikno Research Network ŁUKASIEWICZ, Institute of Welding, Gliwice, Poland

\*Address all correspondence to: zygmunt.mikno@is.gliwice.pl

© 2020 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.

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*Resistance Welding of Aluminium Alloys with an Electromechanical Electrode Force System DOI: http://dx.doi.org/10.5772/intechopen.93242*

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Section 3
