ORIGINAL ARTICLE

Investigation on forming–welding process chain for DC04 tubemanufacturing using experiment and FEM simulation

Alexander Bauer1 & Yupiter H. P. Manurung2& Joeran Sprungk3 &Marcel Graf1 & Birgit Awiszus1 & Keval Prajadhiana2

Received: 15 October 2018 /Accepted: 15 January 2019# Springer-Verlag London Ltd., part of Springer Nature 2019

AbstractA chained forming–welding process is to be investigated and analyzed using experimental verification and numerical simulationin which the material and mechanical properties are fully transferred between processes. The investigated part is in the form of atube with dimension of 300 mm (l) × 20 mm (OD) × 1.5 mm (t) made of a low carbon steel material DC04 commonly used forautomotive parts and support structure. At first, a series of experiment using industrial U-/O-bending machine and fully auto-mated robotic gas metal arc welding (GMAW) process on longitudinal slot were sequentially conducted and analyzed towardsfinal geometrical change, macrostructure, and residual stress. Further, numerical simulation method using specialized FEMsoftware Simufact.Forming and Simufact.Welding is developed to predict the major properties following the actual processparameters during experimental forming and welding process. Throughout the simulation of forming and welding process,additive isotropic hardening plasticity model based on von Mises yield criterion is selected with a wide range of operatingtemperature and Goldak’s double-ellipsoid is defined as welding heat source model. Based on the analysis outcome, it can beconcluded that coupled forming–welding process simulation can be suitably implemented to forecast major material and me-chanical properties of tube manufacturing within accepted range of error under consideration of material history.

Keywords Forming simulation . Welding simulation . Coupled forming–welding . Chained FEM simulation process . U-/O-bending . Robotic welding

1 Introduction

One of the main processing technologies within the metalfabrication industries is tube manufacturing due to high im-portance and wide product applications. There are differentproduction routes which can be applied to produce tube suchas forming, casting, and welding. Because of the permanentlyincreasing demands on quality and quantity, the duration ofdevelopment, trial, and initial periods of product manufactur-ing is essential and expected to be shortened. Furthermore, it iswell known that products and processes remain constantly

changed due to new research and development strategies.This leads numerical simulation of processes and technologiesto become an irreplaceable tool within the manufacturing in-dustry. Due to the mentioned facts, the demands on the qualityresult assessment within the numerical simulations are in-creasing as well. The tendency shows that the simulation ofsingle process steps is more often replaced by analyzing pro-cess chains which consider the process and material history aswell. Since the finite element method (FEM) is the state of theart for the simulation of forming and welding processes, thenumerical simulation of chained forming–welding processesis less popular caused by complex general-purposed and lim-ited specialized FEM software.

Generally, the main topics of actual welding simulationsare the prediction of thermal residual stresses, distortions,and the microstructure [1]. Typical specialized FE tools forthe calculation of welding processes are Simufact.Welding,Sysweld, or DynaWeld which offer different opportunitiesand options for the computational welding processes. As rea-son for the increasing opportunities with the calculation ofwelding processes, actual researches are mainly dealing with

* Yupiter H. P. Manurungyupiter.manurung@salam.uitm.edu.my

1 Professorship of Virtual Production Engineering, ChemnitzUniversity of Technology, Chemnitz, Germany

2 Faculty of Mechanical Engineering, UiTM Shah Alam, ShahAlam, Malaysia

3 University of Applied Sciences, Bochum, Germany

The International Journal of Advanced Manufacturing Technologyhttps://doi.org/10.1007/s00170-019-03320-1

parameter study, calibration, or a deeper understanding of theprocess itself. For example, a study of different laser parame-ters was carried out followed by an optimization [2]. Anotherresearch topic deals with the distortions caused by multi-layerwelding of T-joints or the numerical multi-pass welding com-pared to the reality [3]. Furthermore, multiple research pro-jects deal with the topic of laser welding with special materialsor supporting structures [4–6].

An accurate prediction of deformation of forming pro-cess is necessary in order to avoid excessive cost ofreworking. Distortion and springback prediction is a dif-ficult task to perform especially considering the sensitiv-ity and FEM existed in order to tackle this complexity [7].The FE program for the sheet metal springback experi-ment was carried out with the integration of artificial neu-ral network (ANN). The results obtained at the end of theFE analyses were found to have improved in comparisonto the measured data. Therefore, the current work has ahigh potential to be integrated with the FE software tosimulate sheet metal springback phenomenon accurately.FE analysis of sheet metal springback is often carried outwith ANN integration. The FE produced a result whichimproves the measured data quality. It can be concludedthat FE method has a high potential to simulate the defor-mation of sheet metal such as springback effect [8].

One of the most common problems within the calculationof coupled processes is the connection between the results ofthe different specific simulation tools. Due to the limitation ofnumerical welding simulations mostly for research projects,the coupled processes of forming and welding are a very new

field of interest in the praxis industry. There are few researchprojects dealing with the topic of the coupled forming andwelding technologies. A numerical process chain was suc-cessfully developed for the deep drawing of a previouslylaser-welded two-part circular blank [9, 10]. Another multi-stage coupled forming and welding setup was presented withthe numerical modeling of a crash-box in which the connec-tion between a forming and a laser-welding process was final-ly followed by a crash simulation of the previously weldedstructure [11]. Furthermore, the coupling of an arc weldingprocess was investigated followed by flat rolling with theaim to improve the microstructure of the weld seam in-linewithout intermediate cooling [12].

Generally, the manufacturing of complex structures in-volves various processes that yield the final product.Simulation methods are often used to optimize each singleprocess step. This can be summarized that if the resultproduced by simulation possesses an influence towardsthe simulation of the proceeding steps, it needs to betransferred between possibly dissimilar areas [13]. A com-prehensive finite element simulation of the coupledmanufacturing process is one of the approaches to evalu-ate the manufacturing process and final assembly’s prop-erties. Finite element simulation involvement also couldshorten the development processes by replacing most ofphysical trials; this could be applied in forming processwhere springback behavior is analyzed [14]. The usage ofFE Simulation on investigating coupled manufacturingprocess has become an interest of research on the ad-vanced manufacturing field since the last decade, one of

Fig. 1 Forming tools for U and Obending (top) and three formingsteps of U/O bending (below)

Fig. 2 Robotic welding IRB 1600(left) and clamping device fortube welding (right)

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the researches [15] utilized the FE Model to simulate theprocess chain of forming and welding which resulted in asignificant improvement of distortion result of weldingprocess by considering result from forming process.Other FE simulations of manufacturing process chainsfocusing on supporting the production of frame structuresin the vehicle industry were conducted in [16] which in-cludes forming, material cutting, and welding.

Various researches on wider application of FE simulationon coupled manufacturing process also have been conducted.A simulation of manufacturing process chain is modeled toreduce the level of tensile stresses for aero-engine gas turbine.The research involved casting to forging process chain alongwith heat treatment methods [17]. A finite element model ofthe manufacturing chain for rail was developed in [18] whichsimulated various hot rolling and controlled cooling of whichphase transformation and microstructure evolution of modelswere implemented within FE codes.

The coupled manufacturing simulation demands both akinematic and a force description of the manufacturingprocess. Coupled manufacturing process is able to be sim-ulated which most researchers aims to conduct a researchwhich called first module of the simulation. By means ofthe coupled simulation, machine concepts can be easilyanalyzed and optimized in relation to the machining con-ditions and the workpiece–tool geometry interaction [19].A research on finite element simulation of a chainmanufacturing process was performed using a fine adap-tive meshing model which combines three manufacturingprocesses consisting of forging, heat treatment, and

cutting [20]. All of these researches demonstrate versatileapproach of FEM simulation on a chain manufacturingprocess in order to be an effective way to save more timeand resources rather than manual rebuilding of the actualmodel.

There are some state-of-the-art researches dealing with pro-cess parameters and springback on various manufacturingprocesses of tubular product using simulation and experiment[21–25]. Due to the lack of past investigation on DC04 tubemanufacturing using U-/O-bending followed by longitudinalfusion welding, this research is aimed to validate the devel-oped numerical simulation with experiment of this coupledprocess forming–welding. Furthermore, different parametersand influences on the numerical simulation were studied,which leads to restrictions that have to be considered for amore precise simulation results.

2 Experimental process chain of formingand welding

Within the first forming step, a three-step U-/O-bending pro-cess was established for the manufacturing of the longitudinalslotted tubes. For this purpose, commercial DC04 steel sheets,with the dimensions of 300 mm in length, 63 mm in width,and 1.5 mm in thickness, were used to form tube with an outerdiameter of 20 mm. To carry out the forming process, a multi-servo press MSP 200–250 of H&T Productions TechnologyGmbH with a maximum press force of 2000 kN was used.

Fig. 3 CMM Mitutoyo Beyond 707 and clamping device for tube measurement (left) and schematic illustration of measurement point arrangements(right)

Fig. 4 Numerical setup for U bending (left) and O bending (right)

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Within this press, the tools for the U- and O-bending processeswere installed as shown in Fig. 1.

Within the first step, the U-bending process formed theinitial sheet in the shape of the die. A spring controlled counterholder leads to an even surface at the bottom of the workpiecewithout controlled bending during the forming motion of thepunch. The second and third steps were performed by thesemicircular tools (Fig. 1—top left). Within the second step,a distance holder between the two dies ensures that the first O-bending step leads to an oval shape of the tube, while thesecond step, without distance holder, finishes the forming pro-cess to the longitudinal tube with a slight slot gap betweenboth ends of the metal sheet. The three bending steps are seenin Fig. 1 below from left to right.

After the bending process, the slotted tubes were welded bya gas metal arc welding (GMAW) process attached to ABBIRB 1600 which is equipped with Kemppi Promig 540Rwelding control and a ProMig 120R wire feed as shown inFig. 2 (left). The slotted tubes were fixed within a self-fabricated clamping device (Fig. 2—right).

The filler material usedwas a G2Si1 (OKAristoRod 12.57)and the shielding gas was a mixture of argon (82%) and car-bon dioxide (18%). During the welding process, current of88 A and potential of 18 V were applied for a welding speedof 9 mm/s.

In addition to the forming and welding technologies, vari-ous methods were used to evaluate and examine the obtained

results. The general measurements of the length were conduct-ed with a conventional digital caliper, while exact measure-ments of the diameter and the circular shape of the cross sec-tion were performed with a 3D microscope VHX-600 byKeyence. With the connected software VHX-H2MK 3D, athree-point measurement was used to determine the differentdiameters, at different sections, on the in- and outside as wellas close to the weld seam. Additionally, the residual stresses ofthe specimen were detected within the different steps of theforming technology and after the welding process. For the X-ray detection of residual stresses, a Bruker AXS D8 Discoverdiffractometer was used with a cobalt source of radiation and aradiant power of 40 kV and 40 mA. The evaluation of theresults was conducted within the related program LEPTOSprovided by Bruker AXS. Both technologies (X-ray diffraction(XRD) and 3Dmicroscope were applied for the forming prod-ucts (longitudinal slotted tube and intermediate stages) as wellas the welded tubes. To measure the distortion after thewelding process caused by the induced thermal stresses, thetubes were measured before and compared after welding. Forthis reason, an individual designed clamping system was de-signed and fabricated within the coordinate measurement sys-tem (CMM) Mitutoyo Beyond 707 (Fig. 3—left). Within theclamping device, a mechanical stop and a mark on the speci-men were implemented to ensure the measuring positionsremained the same. For the distortion measurements, six sec-tions were defined at different positions over the length of the

Fig. 5 Flow curves of DC04 (plate) and G2Si1 (filler wire)

Fig. 6 Weld seam model (left)and numerical setup (right)

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tube (Nr. 1 to 6) including 11 measuring points each (Fig. 3—right).

Another very important analysis for the evaluation ofwelding processes is the microstructure of the weldment.The specimen was prepared by cutting, embedding in epoxyresin, grinding, polishing, and etching. Afterwards, the spec-imen was analyzed with a Stemi 2000-C with the programAxioVison of the Carl Zeiss AG. The more detailed analysesof the microstructure were carried out with an invert Axiovert200 MAT microscope with a magnification factor of × 100.

3 Numerical simulation setup and procedure

The numerical simulations were divided in two parts formingand welding. The forming simulations were conducted usingFEM tool Simufact.forming 14.0, while the welding simula-tions with Simufact.welding 6.0 from MSC Software

Company. Due to the differences between the processes, thereare different special settings in each program to be considered.The numerical simulation of the U-/O-bending was setup as a2D planar simulation to reduce computational time (Fig. 4).

The needed geometries were reconstructed from the exper-imental tools within the computer aided design (CAD) toolSiemens NX 10.0. The mesh was build up with an advancingfront quad mesher and an element edge length of 0.5 mm. Acombined friction model with μ = 0.1 und m = 0.2 was ap-plied. The initial temperatures for workpiece, tools, and envi-ronment were set to 20 °C following the real process. For thefirst computation, the general material data such as YoungModulus and Poisson ratio were taken from the database,while the flow curve was determined with temperature rangefrom 25 to 1500 °C (Fig. 5).

The press stroke was set at 1 mm/s. After the forming mo-tion, the press stroke included the return of the punch or die intothe initial position similar to the actual experimental processes.

To create a coupled simulation of forming and weldingprocesses, the geometry along with other results such as plas-tic strain and residual stresses was transferred from theforming into the welding simulation. Within the first step,the 2D geometry was expanded into a 3D geometry with alength of 100 mm similar to the tube sections used for the realwelding processes. Afterwards, the geometry was transferredas SPR data, under consideration of specific setting such as thematching of the plasticity models for both stages to be additiveplasticity. In simulating the GMAW process, a special weldseam has to be modeled within Simufact.Forming GP 14.0(Fig. 6—left). The weld seam was reconstructed after the ge-ometry of the experimental weld seam with the elements edge

Fig. 7 Weld seam model (top)and numerical setup (bottom)

Table 1 Comparison of the measurements between FEM andexperiment

Measurement Experiment (mm) FEM (mm) Abs. error (%)

Inner diameter 1 17.17 16.7 2.7

Outer diameter 1 19.50 19.6 0.5

Inner diameter 2 16.88 16.74 0.8

Outer diameter 2 19.56 19.38 0.9

Top of the gap (1) 0.67 0.64 4.5

Bottom of the gap (2) 0.34 0.35 2.9

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length of the tube remaining at approx. 0.5 mm. Within thearea of the weld seam at around a distance of 3 mm, a refine-ment box was added which causes element edge lengths of2.5 mm in these areas. The weld seam itself consists of ele-ments with an edge length of 0.2 mm. The setup is calculatedas a thermomechanical process because distortions play a ma-jor role in the comparison with the real process. The wholeprocess time was set to 250 s. This consists of 30 s weldingand holding within the clamping device, followed by 220 s ofcooling released from the clamping device similar to experi-mental procedure. The velocity of the welding robot was9 mm/s, and the selected heat source model was the Goldakdouble ellipsoid with a front length of 2 mm, a rear end of3 mm, and a width and depth of 2 mm. The settings for thewelding parameters are 90 A of current and 18 Vof voltage.An idealization was made due to the clamping of the tube.While in the real process, the used clamping causes a linecontact on the workpiece, a small surface contact was usedas reason for numerical instabilities which appeared for theuse of line contacts. All other geometrical properties weretaken from the experimental process including the use of a

spring controlled clamping. After finishing the welding pro-cess, the tube was released from the dies to enable free distor-tion. The numerical setup is exhibited at Fig. 6—right.

4 Results and discussion

Within the first step of calibration, the numerical formingmodel of the bending process was compared with the resultsof the experimental studies. The comparison of the geometryshowed a very good agreement between experiment andFEM. Hereby FEM and the evaluation software of the 3Dmicroscope used the same evaluation method to calculatethe diameter from a three point section placed on the tubulargeometry (Fig. 7). Therefore, different sections lead to differ-ent diameters and it was ensured that the same points werealways used in FEM and in the microscope.

The values for these measurements are seen in Table 1.Furthermore, it can be seen that the geometrical shape of themetal sheet ends is the same within the experimental formedtubes and the simulated ones.

Fig. 8 Comparison of distortion after welding between experiment and FEM

Fig. 9 Macrograph ofexperimental weld bead (left) andcomparison (right)

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The formation of the gap which is due to the forming pro-cess and the related springback effect is considered as the mostcrucial part in the numerical simulation. Nevertheless, a devi-ation of up to max. 0.03 mm or 4.5% of absolute error withinthe macro-mechanical FEM simulation can be seen as a verygood agreement. It is affected by the formingmotion, the pressstroke, and the friction between workpiece and dies as well asthe geometry andmaterial property. Since it is required to havea defined gap area for the filler material, this is also a goodinitial condition for the ongoing welding experiment andsimulation.

With respect to good agreement between experiment andFEM, the simulated geometry was used for the preparation ofthe numerical welding process. The geometry was transferredas described previously. After preparing the simulation withall numerical parameters and constraints, a number of numer-ical calculations were performed to examine particular influ-ences of parameter or property changes on the results. First,the geometrical values are of great importance due to the ther-mal induced influences on the residual stresses. Deformationcan be seen after welding experiments and releasing the tubefrom the clamping device. Two different measuring methods(CMM and 3D microscope) were applied for the geometricalmeasurements. While CMM performed the measurements ofthe shape along the longitudinal axis, over the length of the

specimen, 3Dmicroscope focused on the measurements of thecross section shape of the tube.

For the comparison, similar measurement locations mea-sured with CMM were analyzed in FEM. It is obvious thatthere is a gap between experimental values and FEM. Due tothe fact that the shape of the curves are almost completelyidentical, it could be assumed that there was a slight differencein the structure of the clamping device within the measure-ment system, so all experimental values lie slightly below theones form the FEM in Z-direction. Figure 8 shows the resultsof FEM and measured points.

It can also be seen that there is a noticeable distortion in Z-direction over the length of the specimen, while the distortionin X is rather low. There is good agreement between FEM andexperiment with a maximum deviation of 0.34 mm in Z-direction and 0.33 mm in X-direction from all measurements.The visible distortion is mainly caused by the thermal influ-ences from the welding process. A faster cooling on bothedges of the sample can lead to the effect that different stressesoccur during the cooling process. These stresses, which willbe described later, will lead to the visible deformation behav-ior of the welded specimen. There are major influences, whichcould have an impact on this geometrical change during andafter welding. The main influences are the welding parameters(intensity of heat impact), the welding speed (duration of heatimpact), the weld seam with the thermal material properties(distribution of heat effect), and the clamping devices (con-strain of material).

Fig. 10 Comparison of principal stress without and with forming history

Fig. 11 Measurement sections for XRD on the welded tubes

Fig. 12 Comparison of residual stresses between FEM (blue) and XRD(red)

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Apart frommeasurements of the distortion along the wholespecimen, the cross section of the welded tube was measuredwith 3D microscope. The shape of the cross section showed agood agreement between experiment and numerical simula-tions. The maximum average deviation of eight measuringsections was 6%. Another very important parameter for thecalibration of the numerical welding simulation is the devel-opment of the weld bead. Various macrographs were made(Fig. 9—left) and compared with the numerical results(Fig. 9—right).

Within Fig. 9, it is obvious that the areas of the numericalsimulation possess distinct borders while the transitions in theexperiment are mixed and smoother. Within the transitionzone, a mixed area of weld metal and rough grain can be seen,while the numerical simulation shows a uniform field of weldmetal (1). The detection of a straight cut (2) for the transitionfromweldmetal (1) to the heat affected basematerial (3) is notthat clear, whereby the experimental weld gives a hint for this.Next to the heat affected base material, the unaffected basematerial can be seen clearly in Fig. 9—left but also at theedges of Fig. 9—right. Furthermore, the measurement of thewidth of the weld seam was determined with 3.32 mm for theexperimental approach and 3.41 mm for the numerical simu-lation. The extension of the heat influenced zone starting at (2)up to the base material (4) was measured with 1.5 mm for themicroscope view and 1.68 mm for the FEM, which makes amaximum difference of 0.18mm. This comparison shows thatthere is a good agreement for the heat influenced zone and theweld seam too, even though the FEM is not able to show amore detailed structure with fluent limits.

Finally, a measurement of the residual stresses was con-ducted since these are considered as influencing factor leadingto distortion caused by the thermal cycle during the weldingprocess. In the initial phase, a comparison between the simu-lation without and with forming history shows that there issignificant influence on the development of residual stresses,as it is seen in Fig. 10. Hence, this leads to the conclusion thatthe forming history has to be considered for a detailed analysisof the numerical simulation.

A scatter of the X-ray beam in an area of approx. 5 mm2

was to be defined for the measurement of residual stress asshown in Fig. 11.

While the numerical calculation always provides three re-sidual stresses (σMax, σInt, σMin), the XRD is just able to eval-uate two stress components (σ1, σ2).Within the comparison ofthe results, no values for σMax can be found for the evaluationof the measured XRD values. This could be due to the tensororientation since XRD is not able to measure stresses directedperpendicular to the surface. The stresses of σInt and σMin fromFEM were compared with σ1 and σ2 from experiments. Theexperimental values were gained from two different tubes andaveraged afterwards for the comparison with simulation.Furthermore, it has to be considered that the XRD

measurements can show a variance of approx. ± 20 MPa foreach of the measured points. Figure 12 shows a summary ofthe measured values for each of the measured sections from 1to 6.

It can be seen that there is a good agreement between theevaluated stresses except for one value in Sect. 4, whichshows a strong deviation compared to the other values. Thecomplicated measuring device for the XRD, with a maximummeasuring depth of 10 μm, combined with the fact that thewelding process can lead to strong influences around the weldseam especially at the surface of the specimen, could cause adeviation as it can be seen for area 4. The measured stressesusing simulation which includes the forming history indicatealso good agreement on the distortion based on experimentalverification. Areas 3 and 6 (at bottom part of tube) show hightensile stresses, which interact with the upwards bending ofthe edges in Z-direction. In contrast to that, the areas 1 and 4(on upper part of tube) show compressive stresses as com-monly found in bending processes which show tensile stresseson the outside and compressive stresses on the inside of a bentgeometry. As a main reason for good agreement between ex-periment and numerical simulation is the consideration of theforming history which without this will lead to different stressvalues (see Fig. 10).

5 Conclusion and further recommendation

An experimental and simulation study on chained welding–forming process of tube manufacturing was carried out suc-cessfully within this research. In the experiment, industrialU/O bend and automated welding process were applied tomanufacture tube with material DC04. In the simulation,two specialized FEM software developed under MSCSoftware were used to model and simulate the process withmaterial history transfer. To be compared between experimentand simulation are weld bead size, distortion, and residualstress after last process by using advanced measurement sys-tems. As final conclusions, following points can be drawn:

& Specialized FEM software Simufact.Forming andSimufact.Welding provide the functionality to simulatechained process withmaterial history transfer and compre-hensive flow curves with additive plasticity solution con-sidering thermal, elastic, and plastic strain.

& A good agreement between experimental and numericalresults was found for tube manufacturing.

& The percentage error ranges generally below 12% for weldbead size and residual stress and less than 0.35 mm fordistortion.

& Some slight deviations were detected for the geometricalmeasurements over the length of the tube which might be

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caused by positioning of tube before and after weldingprocess.

& The trend and the shape of geometrical change can beobserved as similar.

& Numerical chained simulation of the forming to weldingprocess can be used for parameter variations or adjust-ments of the actual process settings to reduce experimentaleffort and shorten number of trials.

& U/O bending and robotic welding can be an alternative tomanufacture tube made of DC04.

With the gained knowledge on coupled process and gener-ated model, it is easier to calculate similar process with othergeometries and the developed numerical setup can be used foradvanced computation. Further, the analysis and estimationcan be enhanced into the microstructure during forming andthe phase transformation of the weld seam and heat-affectedzone. The transformed phase can be also observed using ex-periment and simulation-based CCT diagram. For optimiza-tion of the tube welding process, further investigations have tobe conducted according to the single influences as well as theinteraction between them.

Acknowledgements The internationally collaborating authors wouldlike to express their gratitude to Advanced Manufacturing TechnologyExcellence Centre (AMTEx) and Research Interest Group: AdvancedManufacturing Technology (RIG: AMT) at Faculty of MechanicalEngineering, Universiti Teknologi MARA (UiTM) in Malaysia as wellas Professorship Virtual Production Engineering at Chemnitz Universityof Technology (CUT) in Germany for encouraging this research andproviding the equipment. The simulation and advanced equipment areimplemented at CUT.

Funding information This research is financially supported by interna-tional research grant of DAAD (Ref. Nr.: 57347629) and Geran InisiatifPenyeliaan (GIP) from Phase 1/2016 with Project Code: 600-IRMI/GIP5/3 (0019/2016).

Publisher’s note Springer Nature remains neutral with regard to jurisdic-tional claims in published maps and institutional affiliations.

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