Nothing Special   »   [go: up one dir, main page]
Next Article in Journal
A Nanoindentation Approach to Investigating Dislocation Density in Additive-Manufactured SS316L-Graded Lattice Structures
Previous Article in Journal / Special Issue
Microstructure, Thermal, and Mechanical Behavior of NiTi Shape Memory Alloy Obtained by Micro Wire and Arc Direct Energy Deposition
You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JMMP
Volume 9
Issue 2
10.3390/jmmp9020058
jmmp-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Parametric Study on Investigations of GMAW-Based WAAM Process Parameters and Effect on Microstructure and Mechanical Properties of NiTi SMA

by
Vatsal Vaghasia
,
Rakesh Chaudhari
,
Vivek K. Patel
and
Jay Vora
*
Department of Mechanical Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar 382007, Gujarat, India
*
Author to whom correspondence should be addressed.
J. Manuf. Mater. Process. 2025, 9(2), 58; https://doi.org/10.3390/jmmp9020058
Submission received: 31 December 2024 / Revised: 21 January 2025 / Accepted: 10 February 2025 / Published: 13 February 2025
(This article belongs to the Special Issue Advances in Additive Manufacturing and Material Characterization Techniques)
Browse Figures
Figure 1
<p>The GMAW-based WAAM experimental setup.</p> "> Figure 2
<p>Determination of bead morphologies, BW and BH.</p> "> Figure 3
<p>Process chart of the HTS algorithm [<a href="#B44-jmmp-09-00058" class="html-bibr">44</a>].</p> "> Figure 4
<p>A 10-layered nitinol specimen fabricated by WAAM at optimized parameters.</p> "> Figure 5
<p>Testing locations of the built structure.</p> "> Figure 6
<p>Single-layer depositions along with cut cross-sections of depositions.</p> "> Figure 7
<p>Influences of WAAM variables on BH response.</p> "> Figure 8
<p>Influences of WAAM variables on BW response.</p> "> Figure 9
<p>Macrostructure of the built WAAM structure.</p> "> Figure 10
<p>Microstructures of (<b>a</b>) HAZ and initial layers, (<b>b</b>) middle layers, and (<b>c</b>) top layers of the built WAAM structure.</p> "> Figure 10 Cont.
<p>Microstructures of (<b>a</b>) HAZ and initial layers, (<b>b</b>) middle layers, and (<b>c</b>) top layers of the built WAAM structure.</p> "> Figure 11
<p>Tensile test specimens (<b>a</b>) after fracture and (<b>b</b>) after fractography.</p> "> Figure 12
<p>Microhardness along the build direction for a WAAM structure of nitinol SMA.</p> ">
Versions Notes

Abstract

:
In the present study, an attempt was made to build a thin-walled structure consisting of 10 layers using nitinol wire on a titanium substrate via a gas–metal arc welding (GMAW)-based wire-arc additive manufacturing (WAAM) process. A thin-walled structure was fabricated by using nitinol wire on a titanium substrate at the optimized parameters of a wire feed speed of 6 m/min, a travel speed of 12 mm/s, and a voltage of 20 V. In a microstructural study, the heat-affected zone was observed to have coarse grains and be columnar in shape, and the first layer exhibited a mix of dendritic structures. The mid-layers demonstrated a mix of coarse and fine columnar grains with dendritic colonies, while the last few layers demonstrated fairly equiaxed grains as well as a finer microstructure, as the cooling rates were very slow. The ultimate tensile strengths (UTSs) obtained at the bottom and top portions were found to be 536.22 MPa and 586.31 MPa. Elongation (EL) degrees of 10.72% and 11.57% were observed in the bottom and top portions, respectively. The fractography of the tensile specimen showed good toughness and ductility of the fabricated nitinol specimen. A microhardness examination showed a minimum value of 236.56 HV in the bottom layer and a maximum value of 316.78 HV in the topmost layer.

1. Introduction

Over the past few years, shape memory alloys (SMAs) have gained popularity in various fields, including robotics, micro-electro-mechanical systems, sensors, automotive, aerospace, automobiles, medicine, actuators, and other industrial applications [1,2,3,4]. SMAs return to their initial shape and size even after plastic deformation when heated to their defined transformation temperature [5,6,7]. Nickel–titanium, commonly known as nitinol SMA, is widely referred to as SMA owing to its high deformation recovery, biocompatibility, pseudo-elastic nature, shape memory effect, higher work density, and high thermo-mechanical performance [8,9,10]. Conventional processes pose several difficulties in the fabrication of the complex structures of nitinol SMA owing to their higher costs, elasticity, and hardening effects [11,12,13,14]. Thus, additive manufacturing (AM) is the most suitable technique for the manufacturing of the complex geometries of nitinol components. AM methods have gained a lot of attention in recent decades in regard to the fabrication of complex metal parts. The AM technique is suitable for mass production, via the fabrication of intricately shaped parts with a reduced processing time [15,16]. It does not require additional special features for fixtures or tooling, thereby minimizing the cost in comparison with conventional techniques. Direct energy deposition and powder bed fusion are the two broad categories of AM methods. They are differentiated by the feedstock material and heat source used. Powder-based AM has certain limitations in relation to high-cost materials due to it lower level of material utilization [17,18]. The powder-based AM method makes use of high-intensity laser beams as the heat source [19]. Thus, it is operated inside of gas chambers to defeat oxide formations and contaminations. A wire-based direct energy deposition approach technique of wire arc additive manufacturing (WAAM) utilized wire as the feedstock material and an electric arc as a heat source. Thus, the WAAM method has higher efficiency in terms of material utilization [20]. The WAAM technique offers advantages like higher deposition efficiency, no size limit for the fabrication of parts, a lower cost of equipment, and reduced operating costs [21,22]. Gas–metal arc welding (GMAW), plasma arc welding, and gas tungsten arc welding are the different electric arc sources used in the WAAM process to melt the feedstock wire material [23]. Among these sources, the GMAW method offers a higher rate of deposition as compared to other arc sources. The GMAW-based WAAM technique has also shown appropriate mechanical characteristics favorable for the production of larger parts, and a lower cost of equipment [24,25]. It also offers a higher deposition rate of around 4 kg/h to build nitinol structures [26]. During the deposition of the wire material on the substrate, it becomes crucial to investigate the influence of input parameters on bead morphologies. The process variables include voltage (V), the type of shielding gas, gas–mixture ratios, the wire feed speed (WFS), the torch angle, the stand-off distance, the direction of deposition, and the travel speed (TS). It is essential to control process variables to fabricate a thin multi-layered structure. Bead width (BW) and bead height (BH) are the most important output variables during the fabrication of a thin-walled structure. Also, for the fabrication of a thin-walled structure, optimal process variables govern the quality of the built structure [27,28]. A heat transfer search (HTS) algorithm is a metaheuristic optimization technique that is easy to implement and can be used for solving complex problems [29,30,31]. The HTS algorithm is straightforward and involves basic heat transfer principles. HTS is a simple, fast, parameterless, and effective technique that creates enhanced convergence for the preferred response. It can handle various types of optimization problems, including continuous, discrete, and multi-objective problems, without requiring domain-specific modifications. Considering this, the authors aimed to explore the application of the HTS algorithm in the WAAM process.
GMAW-based WAAM has been widely used for the deposition of steels and other alloys [32,33,34,35,36]. However, very limited studies have been conducted on the deposition of nitinol SMA using the GMAW-based WAAM technique. A study conducted by Wang et al. [37] used nitinol SMA wire for deposition on a titanium substrate using GMAW-based WAAM. They investigated the mechanical properties of the built structure, and observed that the ultimate tensile strength (UTS) decreased to 613.8 MPa from 927.9 MPa, while elongation also decreased to 5.6% from 8.7%, owing to the influence of grain size and defects obtained in deposition. Also, an increment in current has shown the coarsening of B2 grains. Resnina et al. [26] deposited five layers of nitinol SMA on the titanium substrate by using a GMAW-based WAAM process. In between the deposited layers, B2 ↔ B19′ martensitic transformation was observed. Jun et al. [38] studied the microstructure and mechanical characteristics of a nitinol structure built by the WAAM process through the GTAW process, using the elemental wires of Ni and Ti. A distinct anisotropic microstructure was obtained, along with a rise in Ni4Ti3 and a drop in Ni3Ti from the bottom to top section. The use of separate Ni and Ti wires can explain the heterogeneous structure of the product. To overcome this limitation, Zheng et al. [39] used nitinol wire, and carried out mechanical and microstructural studies of the nitinol parts produced by the WAAM process. Five layers were deposited, and the built structure showed a superplastic behavior. The microstructural study showed columnar and equiaxed structures in the first and last layers of the depositions.
The current study focusses on establishing the parameters and further structure–property relationships in the context of the WAAM-based approach. The technique encompasses the benefits and advantages of additive manufacturing vis à vis conventional manufacturing practises. However, the current study is more relevant due to the fact that nitinol is a heat-sensitive material, and the conventional route of manufacturing often poses challenges. The thin-walled structure fabricated in the study offers confidence to manufacturers, especially in the repair and maintenance of components made of this alloy, such as in the medical field (orthodontic devices, implants, stents, tools etc.), structural engineering (dampers), and in other applications such as heat engines, resilient glass frames, retractable antennas, surgical implants, and self-bending spoons. Any structural damage can be compensated for by applying this technique. In addition to this, the study also focusses on presenting a viable option to the manufacturing of new components.
To the best our knowledge, a parametric study on the use of bead morphologies to build a thin-walled structure using nitinol SMA wire has not yet been undertaken. In the present study, an attempt has been made to prepare a thin-walled structure consisting of 10 layers using nitinol wire on a titanium substrate via the GMAW-based WAAM process. The first aim of the study was the identification of optimal process variables for fabricating a thin-walled multi-layer structure; the second was fabricating a thin-walled nitinol structure by use of the optimized process variables, and the final aim was to study the microstructural mechanical characteristics of the built structure. On the basis of the literature studied and preliminary experimental trials, WFS, TS, and voltage were identified as the process variables, with BW and BH as the output responses. The Box–Behnken design (BBD) approach was used to perform single-layer depositions. Statistical analysis was carried out by use of analysis of variance (ANOVA). Non-linear regressions were generated and optimal process parameters were obtained by using the multi-objective HTS algorithm. A thin-walled structure was fabricated by using nitinol wire on a titanium substrate at the optimized parameters. The built structure was then subjected to microstructural, mechanical, and fractographical studies. The author believes that the present study will be useful in the context of designing and fabricating a thin-walled structure made of nitinol SMA.

2. Materials and Methods

2.1. Experimental Plan

In the present work, nitinol wire was used as the feedstock material and deposited on a Ti substrate using the GMAW-based WAAM process. Ni55.8Ti alloy wire with a diameter of 1.2 mm was utilized in the single- and multi-layered depositions on the substrate. A pure titanium plate was utilized as the substrate due to the compatibility of its composition with nitinol, and the greater ease of debonding this structure from the surface of the plate. The conventional GMAW machining setup (make and model: Miller continuum 250) was used, which has a built volume of 220 mm × 220 mm × 500 mm. Figure 1 shows the experimental setup employed. The GMAW torch can move on the x, y, and z axes for the deposition of the wire material onto substrate. A program with a computer interface was utilized as the controller. A power source of COLTON iFLEX 350 was utilized to heat and melt the material.
The first aim of the study included the identification of optimal process variables to fabricate a thin-walled multi-layer structure, and the second was to fabricate a thin-walled nitinol structure at the optimized process variables; the final aim was to determine the microstructural mechanical characteristics of the built structure. To obtain optimal process conditions, single-layer depositions were carried out after planning the experiments using the BBD method. Based on the studied literature and preliminary experimental trials, WFS, TS, and voltage were identified as the process variables, and BW and BH as the output responses [26,40,41]. A constant flow rate of 15 L/min was maintained throughout. Table 1 displays the input process conditions employed for the layer-by-layer, single-layer depositions of nitinol SMA. An experimental design matrix of 15 trials was prepared by following the BBD design, using the Minitab v17 software. The BBD technique eliminates a large number of experimental runs, thereby reducing costs and time [42,43]. More importantly, BBD illustrates the interrelationship between the input and output responses. All the experimental runs were performed three times to ensure better accuracy and repeatability, and their average values were taken for analytical purposes.

2.2. Testing and Characterization

2.2.1. Evaluation of Responses

To determine the output parameters of BH and BW, all 15 depositions were cut at their smallest cross-sections using the Wire-EDM process. For each sample, three readings were taken across the depositions to produce reliable and accurate results, and their averages were taken into account for the final analysis. Various grades of abrasive papers were used to clean and polish the cut specimens, and they were then assessed by use of optical microscopy. Figure 2 shows the process of determining the bead morphologies of the BW and BW responses.

2.2.2. Optimization Using HTS Algorithm

Based on the results obtained regarding bead morphologies, the heat transfer search (HTS) algorithm was employed to determine optimal process parameters for building a thin-walled structure. For thin-walled structures, BH was considered a maximization response, and BW a minimization response. HTS is a simple, fast, parameterless, and effective technique that creates enhanced convergence for the preferred response. HTS, a metaheuristic optimization technique developed by Patel and Savsani [44], is capable of solving complex engineering problems. The HTS technique uses three modes of heat transfer—conduction, convection, and radiation—to attain thermal equilibrium in an unbalanced system. The HTS algorithm assigns equal probability to each of the three methods of heat transfer (conduction phase, convection phase, and radiation phase). This balanced approach ensures that each mode contributes equally to the search process, promoting diversity and robustness when exploring the solution space. The HTS algorithm initiates with a randomly generated population, whereby the system has “n” number of molecules (i.e., population size) and a set temperature level (i.e., design variables). The population gets updated in subsequent stages via the random selection of any of the modes of heat transfer. The algorithm then accepts the solutions with better functional values and rejects the poorest solutions. Figure 3 shows a flow chart of the HTS algorithm’s technique.
  • Conduction mode
The solutions of the conduction mode were enhanced using Equations (1) and (2).
X j , i ′ = X k , i + − R 2 X k , i ,   i f   f X j > f X k X j , i + − R 2 X j , i ,   i f   f X j < f X k ; i f   g ≤ g m a x C D F    
X j , i ′ = X k , i + − r i X k , i ,   i f   f X j > f X k X j , i + − r i X j , i ,   i f   f X j < f X k ; i f   g > g m a x C D F  
  • Convection mode
The solutions of the convection mode were enhanced using Equations (3) and (4).
X j , i ′ = X j , i + R × X s − X m s × T C F
T C F = a b s R − r i ,                             i f   g ≤ g m a x C O F r o u n d 1 + r i ,                     i f   g > g m a x C O F
  • Radiation mode
The solutions of the radiation mode were enhanced using Equations (5) and (6).
X j , i ′ = X j , i + R × X k , i − X j , i ,   i f   f X j > f X k X j , i + R × X j , i − X k , i ,   i f   f X j < f X k   ; i f g ≤ g m a x R D F
X j , i ′ = X j , i + r i × X k , i − X j , i ,   i f   f X j > f X k X j , i + r i × X j , i − X k , i ,   i f   f X j < f X k   ; i f g > g m a x R D F

2.2.3. Microstructure and Mechanical Characterizations

A thin-walled structure with 10 layers of deposition, as shown in Figure 4, was characterized by mechanical and microstructural examinations. A built structure with effective dimension of 150 mm × 11 mm × 30 mm was cut from the substrate plate using the Wire-EDM process. A schematic representation of the testing locations of the built structure is shown in Figure 5. Wire-EDM was preferred for use in preparing the specimens for micro, macro, tensile, and hardness tests. The specimens were cleaned, polished, and etched using a solution of HF + 4HNO3 + 5H2O. A section of the built structure was also tested for chemical composition, and found to have a composition within the limits set for nitinol wire. For the macrostructural and microstructural examinations, an optical microscope (RAD ICAL instrument, Radical Scientific Equipments Private Limited, Haryana, India) and an optimal macroscope (IMS-300-TNC, Sinowon Innovation Metrology Manufacture Limited, Guangdong, China) were used, respectively. The tensile test was carried out as per the ASTM E8M standard using a universal testing machine. The ESEWAY EW-150 (Bowersgroup company, Camberley, UK) machine was preferred for use in determining the hardness with a 150 gf load and a dwell time of 15s. Multiple readings were taken across the depositions to ensure reliable and accurate results, and their average was taken into account in the final analysis. Lastly, a fractographic assessment of tensile specimens was carried out using a Zeiss Ultra-55, which is a type of scanning electron microscope.

3. Results and Discussions

Having followed the BBD design matrix for RSM, the results obtained regarding the bead morphologies for BH and BW are depicted in Table 2. For thin-walled structures, BH was considered as a maximization response, while BW was considered a minimization response. Figure 6 shows the single-layer depositions along with the cross-sections of bead morphologies according to the BBD design matrix, as displayed in Table 2.
On the basis of the results shown in Table 2, empirical equations were generated for the output responses in terms of the input factors of the WAAM process. Equations (7) and (8) are empirical equations for the BH and BW responses, respectively. These equations were validated using statistical analysis.
B H = − 33.4 + 0.14 · W F S − 2.743 · T S + 5.17 · V + 0.259 · W F S · W F S − 0.1451 · V · V − 0.0955 · W F S · V + 0.1184 · T S · V
B W = 69.8 − 6.80 · W F S − 1.690 · T S − 3.62 · V + 0.3588 · W F S · W F S + 0.0973 · V · V + 0.2479 · W F S · T S

3.1. ANOVA for Output Responses

The results obtained in Table 2 via the BBD technique were further analyzed using a statistical technique called analysis of variance (ANOVA). It was employed to check the most important factors for use in improving the quality of a product or process. The Minitab software was utilized to analyze the data for response variables of BH and BW. During the regression study, 95% CI was considered. It was determined that the P-value of the input variable should not be more than 0.05 in order to show the significant impact on the elected output response [45,46].
Table 3 is an ANOVA table of BH and BW responses. The statistical outcomes for both responses were observed to be highly significant, as the entire regression model term, including the linear, square, and two-way interactions, were found to be significant. In the case of the BH response, all three WAAM variables were found to have a significant impact. WFS showing the highest F-value suggests that changes in the level of WFS had a significant effect on BH values, with the largest contribution of 68.83%. Regarding the BW response, all three WAAM variables were also found to have a significant impact, with the largest impact represented by voltage (81.58%), trailed by WFS and TS. The R2 values were found to be 98.50% and 98.62% for BH and BW models, respectively, while the Adj. R2 values for the BH and BW models were 96.99% and 97.58%, respectively. The accuracy and predictability of the ANOVA were also confirmed by the lack-of-fit, which was required to be insignificant [47,48]. For both output responses, the lack-of-fit was observed to be insignificant, which suggests the appropriateness and accuracy of the regression models. Thus, both the models of BH and BW successfully validated the entire selected design space. As such, the regression equations, as shown in (7) and (8) for BH and BW, respectively, can be effectively used to predict the response values within the defined range of WAAM variables.

3.2. Influence of WAAM Variables on Output Responses

Main effect plots have been established to illustrate the impacts of WAAM parameters on output characteristics. For the fabrication of a thin-walled structure, BH was considered a maximization response, while BW was considered a minimization response. Figure 7 depicts the influence of WAAM variables on the BH response. An increment in WFS levels yielded an increased response in the BH value. At a higher value of WFS, the speed of the wire increased, and it deposited greater material [41,49]. For this reason, BH also increased at higher values of WFS. BH was reduced with enhancements in TS levels. A higher travel speed does not allow sufficient time for molten metal deposition. Thus, BH was reduced with increased TS values [50,51]. Intensifications of voltage value showed a tendency to reduce BH value. This is because, with increased voltage, arc length also increases [52,53]. Therefore, to attain higher BH values, a higher level of WFS of 7 m/min, a lower level of TS of 10 mm/min, and a lower level of voltage of 20 V are desirable.
The influences of WAAM factors on BW response are represented in Figure 8. An increased value of WFS has a negative impact on BW response, which was observed to be increased with the increase in WFS levels. At a higher value of WFS, the speed of the wire increased, and the wire deposited a larger amount of material on the substrate [54]. For this reason, BW also increased at higher values of WFS. BW was slightly decreased with increases in TS levels. A higher travel speed does not permit sufficient time for molten metal deposition [51,55]. Thus, BW reduces with increased TS values. An increment in BW response has been shown with the intensification of the voltage value from 20 to 24 V. The reason for this is that, with increased voltage, the arc length also increases [56,57]. Therefore, to attain lower BW values, a lower level of WFS of 5 m/min, a higher level of TS of 14 mm/s, and a lower level of voltage of 20 V are desirable.

3.3. Optimization Using HTS Algorithm

The individual values of WAAM parameters obtained for the maximization of BH and the minimization of BW suggest the necessity of finding out the optimum levels of input factors, as both these factors were observed at different values. Thus, the HTS algorithm was employed during the study to determine the optimal process conditions. During the implementation of the HTS technique, the empirical Equations (7) and (8) were used, and all the integers were kept positive. The ranges of WAAM factors considered were 5 ≤ WFS ≥ 7; 10 ≤ TS ≥ 28, and 20 ≤ V ≥ 24. By considering the equal levels of importance of both responses, an equal weighting of 0.5 was assigned to the BH and BW responses. The simultaneous optimization carried out using the HTS technique yielded optimal process parameters as follows: WFS at 6 m/min, TS at 12 mm/s, and voltage at 20, with output response values of BH at 6.16 mm and BW at 6.05 mm. To validate the results obtained by use of the HTS algorithm, a verification trial was conducted with the optimal process parameters. The bead morphologies of the BH and BW responses were observed to show acceptable deviation of less than 4%, suggesting the accuracy and adequacy of the HTS algorithm for use in generating regressions.

3.4. Fabrication of Thin-Walled Structure

The optimal process parameters of WFS at 7 m/min, TS at 13 mm/s, and voltage at 23 V were obtained by use of the HTS algorithm. The optimal process conditions were used for the fabrication of a thin-walled structure. Figure 5 shows the 10 layers of the nitinol structure fabricated on a titanium substrate. A dwell time of 15 s was kept between the deposited layers to preclude the occurrence of excessive residual strains and deformation. By use of the Wire-EDM process, the built structure was removed from the substrate. The dwell time applied also enabled the solidification of the deposited layers. The built structure was observed to be uniform, with small metal lumps on the deposition sides. The excess lumps were removed during post-processing using the Wire-EDM process.

3.5. Macrostructure and Microstructure Study

Macrostructural examinations were carried out by cutting a section from the fabricated thin-walled structure, as shown in Figure 6. The specimens were cleaned, polished, and etched by use of a solution of HF+4HNO3+5H2O. Figure 9 shows a macro image of the 10 deposited layers. The cross-sectional view shows the as-deposited NiTi wall without cracks or pores. This establishes that the parameters, as well as the manufacturing techniques, were sufficient for deriving defect-free layers. The layers are marked with dashed red lines.
Figure 10a–c depicts the microstructures obtained in different regions of the built structure. A total of 10 layers was deposited, one upon the other. The initial two or three layers were deposited on a comparatively colder substrate. However, after depositing each subsequent layer, a build-up of heat can be expected, and a pursuant change in the microstructure can be observed. Figure 10a depicts the change in the granular structure from the HAZ to the first layer. The HAZ comprises coarse grains, and is columnar owing to the stringent cooling rate; however, the first layer here shows a mix of dendritic structures [58]. Furthermore, the mid layers shown in Figure 10b exhibit a mix of coarse and fine columnar grains with dendritic colonies, as shown in the circle. Different pools of such colonies were found as the cooling rates reduced gradually, owing to the subsequent deposition of layers [59]. Furthermore, the heat gradually built up until the 10th layer was deposited, and hence, the last few layers demonstrate fairly equiaxed grains as well as a finer microstructure, as the cooling rates were very slow; these areas have been highlighted with arrows in the image. The results agree with those from studies by Lin et al. [60] and Zeng et al. [39].

3.6. Mechanical Properties

3.6.1. Tensile Testing

Investigations into mechanical properties were carried out via tensile tests at two locations, i.e., at the bottom and top portions of the built structure. The tensile test samples were cut using the Wire-EDM method, and were assessed as per the ASTM E8M standard using a universal testing machine. Figure 11a and b show the tensile test specimen after fracturing and fractography, respectively. The tensile specimens showed elastic and plastic deformations prior to their fracturing. The ultimate tensile strength (UTS) obtained in the bottom portion was observed to be 536.22 MPa, while the top portion showed a UTS of 586.31 MPa, with greater strength along the building direction. Similar observations were recorded for elongation (EL), which was observed at 10.72% and 11.57% in the bottom and top portions, respectively. The deviations in the results for UTS and EL were observed to be in accordance with the Hall–Petch relationship [37,61]. Other reasons for the lower strength and elongation observed in the bottom portion in comparison with the top include the presence of a few defects, such as residual thermal stress, oxides, and slag in the bottom portion of the built structure [61]. The recording of an EL of more than 10% for both the specimens suggests that the built structure matches the wrought metal [60]. Thus, the tensile properties obtained clearly suggest the internal superiority of the thin-walled structure built from nitinol SMA via the GMAW-based WAAM process.
A scanning electron microscopy (SEM) image of the fractography of the tensile specimen is shown in Figure 11b. It shows that the fracture spread along the gauge length. The fracture’s surface shows a higher amount of dimples formed with identical circulation patterns. It shows the good toughness of the nitinol specimen fabricated via the GMAW-based WAAM process. The presence of larger dimples adjacent to each other also suggests the good ductility of the nitinol parts produced by WAAM [62]. Similar results were obtained for other tensile specimens as well, which proves the suitability of the built structure.

3.6.2. Microhardness Testing

Microhardness testing (Brinell hardness testing) was carried out on the thin-walled built structure of nitinol SMA following the ASTM E-10 standard. A microhardness examination was carried out by cutting a section from the bottom to the top portion of the fabricated thin-walled structure, as shown in Figure 6. At each location, four readings were taken to ensure reliable and accurate results, and their average was taken into for the final analysis. The mode of evaluation of microhardness is shown in Figure 12, starting from the bottom-most layer and moving to the top layer of the deposited nitinol structure. The bottom portion of the structure, i.e., HAZ, showed the lowest value of 236.56 HV. The initial layers were observed to have lower hardness values, from 242 HV to 263 HV. In the top layers of deposition, the hardness value was observed to increase gradually, reaching a maximum value of 316.78 HV. This was due to the different grain morphologies and precipitation effects [60]. The lower regions of the built structure show columnar grains, with reduced hardness, while the higher values of microhardness in the top layers are related to the finer morphology [63,64]. This is because the finer microstructure contains greater numbers of grain boundaries and dislocations, which gives rise to greater microhardness [60]. The results obtained are in line with results produced by Zeng et al. [39].

4. Conclusions

In the present study, the GMAW-based WAAM process was used to build a thin-walled structure consisting of 10 layers, using nitinol wire on a titanium substrate. The study was divided into two sections, as follows: the first sought to identify optimal process variables, and the second sought to fabricate a thin-walled nitinol structure with optimized parameters and study the microstructural mechanical characteristics of the built structure. The following conclusions could be drawn from the obtained results:
➢
The statistical outcomes for bead morphologies were observed to be highly significant, as is validated by the ANOVA, R2, and Adj. R2 values. All three WAAM variables were found to be significant for both responses of BH and BW, showing the largest contributions of WFS (68.83%) for BH and V for BW;
➢
The simultaneous optimization carried out using the HTS technique yielded optimal process parameters of WFS of 6 m/min, TS of 12 mm/s, and voltage of 20 V. A thin-walled structure with 10 layers was successfully fabricated at these optimized conditions;
➢
The macrostructural examination showed an as-deposited NiTi wall without cracks or pores. This established that the parameters, as well as the manufacturing techniques, were sufficient to derive defect-free layers;
➢
In the microstructural study, the HAZ was observed to have coarse grains that were columnar in shape, and the first layer contained a mix of dendritic structures. The middle layers demonstrated a mix of coarse and fine columnar grains with dendritic colonies, while the last few layers demonstrated fairly equiaxed grains as well as a finer microstructure, as the cooling rates here were very slow;
➢
The microhardness examination yielded the lowest value of 236.56 HV in the bottom layer, while the maximum value of 316.78 HV was found in the topmost layer;
➢
The UTS obtained in the bottom portion was observed to be 536.22 MPa, while the top portion showed a UTS of 586.31 MPa, showing increasing strength along the building direction. Similar observations were recorded for elongation (EL), which showed values of 10.72% and 11.57% in the bottom and top portions, respectively. Fractography of the tensile specimens showed the good toughness and ductility of the fabricated nitinol specimen;
➢
The thin-walled structure fabricated in the study should enhance the confidence of manufacturers, especially as regards the repair and maintenance of components made of this alloy, such as in the medical field (orthodontic devices, implants, stents, tools, etc.) and structural engineering (dampers), and in other applications such as the building of heat engines, resilient glass frames, retractable antennas, surgical implants, and self-bending spoons.

Author Contributions

Conceptualization, V.V., R.C. and J.V.; methodology, V.V., R.C. and J.V.; software, V.K.P. and R.C.; validation, V.V., R.C., V.K.P. and J.V.; formal analysis, V.V.; investigation, V.V., R.C., V.K.P. and J.V.; resources, V.V., R.C. and J.V.; data curation, V.V., R.C. and J.V.; writing—original draft preparation, V.V., R.C. and J.V.; writing—review and editing, R.C. and J.V.; visualization, V.V., R.C., V.K.P. and J.V.; supervision, R.C. and J.V.; project administration, R.C. and J.V.; funding acquisition, R.C. and J.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The data presented in this study are available in this article.

Acknowledgments

The authors would like to acknowledge the project funded by “The Institution of Engineers (India), R&D Grant-in-aid Scheme (Project I.D. DR2023005)”.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
AMAdditive manufacturing
ANOVAAnalysis of variance
BBDBox–Behnken design
BHBead height
BWBead width
EDMElectrical discharge machining
ELElongation
GMAWGas–metal arc welding
HTSHeat transfer search
SMAShape memory alloy
TSTravel speed
UTSUltimate tensile strength
WAAMWire arc additive manufacturing
WFSWire feed speed

References

  1. Jani, J.M.; Leary, M.; Subic, A.; Gibson, M.A. A review of shape memory alloy research, applications and opportunities. Mater. Des. 2014, 56, 1078–1113. [Google Scholar] [CrossRef]
  2. Vatanparast, S.; Boschetto, A.; Bottini, L.; Gaudenzi, P. New trends in 4D printing: A critical review. Appl. Sci. 2023, 13, 7744. [Google Scholar] [CrossRef]
  3. Tareq, S.; Rahman, T.; Poudel, B.; Chung, H.; Kwon, P. Heat treatment protocol for additively manufactured nitinol shape memory alloys in biomedical applications. Mater. Sci. Eng. A 2024, 897, 146274. [Google Scholar] [CrossRef]
  4. Böttcher, F.; Schaarschmidt, I.; Edelmann, J.; Schubert, A. Simulation-Assisted Tool Design for Pulsed Electrochemical Machining of Magnetic Shape-Memory Alloys. J. Manuf. Mater. Process. 2024, 8, 46. [Google Scholar] [CrossRef]
  5. Shafeeq, M.M.; Hirshikesh; Gupta, G.; Mondal, D. Influence of Mn on the Mechanical and Shape Memory Transformation Behaviours of Powder Metallurgy Processed Cu–Al–Ni SMAs. Met. Mater. Int. 2024, 30, 211–219. [Google Scholar] [CrossRef]
  6. Rodinò, S.; Maletta, C. Design Considerations and Applications of Shape Memory Alloy-Based Actuation in Morphing Structures: A Systematic Review. Prog. Eng. Sci. 2024, 1, 100021. [Google Scholar] [CrossRef]
  7. Ahmad, S.; Hashmi, A.W.; Singh, J.; Arora, K.; Tian, Y.; Iqbal, F.; Al-Dossari, M.; Khan, M.I. Innovations in Additive Manufacturing of Shape Memory Alloys: Alloys, Microstructures, Treatments, Applications. J. Mater. Res. Technol. 2024, 32, 4136–4197. [Google Scholar] [CrossRef]
  8. Sathishkumar, M.; Kumar, C.P.; Ganesh, S.S.S.; Venkatesh, M.; Radhika, N.; Vignesh, M.; Pazhani, A. Possibilities, performance and challenges of nitinol alloy fabricated by Directed Energy Deposition and Powder Bed Fusion for biomedical implants. J. Manuf. Process. 2023, 102, 885–909. [Google Scholar] [CrossRef]
  9. Parimanik, S.R.; Mahapatra, T.R.; Mishra, D. A systematic literature review on laser welding of NiTi SMA. Lasers Manuf. Mater. Process. 2023, 10, 77–117. [Google Scholar] [CrossRef]
  10. Wei, S.; Zhang, J.; Zhang, L.; Zhang, Y.; Song, B.; Wang, X.; Fan, J.; Liu, Q.; Shi, Y. Laser powder bed fusion additive manufacturing of NiTi shape memory alloys: A review. Int. J. Extrem. Manuf. 2023, 5, 032001. [Google Scholar] [CrossRef]
  11. Muniraju, M.; Talla, G. Exploring sustainable machining processes for nitinol shape memory alloy: A review of eco-friendly EDM and other techniques. J. Braz. Soc. Mech. Sci. Eng. 2024, 46, 85. [Google Scholar] [CrossRef]
  12. Kulkarni, V.N.; Gaitonde, V.; Jangali, S.G.; Petkar, P.M. A review on machinability aspects of binary and ternary Nitinol (NiTi) shape memory and super elastic alloys. AIP Conf. Proc. 2024, 3007, 100024. [Google Scholar]
  13. Martínez, R.Z.; Bose-Bandyopadhyay, S.; Burl, A.; Contreras-Almengor, Ó.; Vega, C.A.; Saleeby, K.; Kurfess, T.; Lantada, A.D.; Molina-Aldareguia, J. Comparative analysis of machining and electropolishing for surface quality improvement of shape memory nitinol samples additively manufactured by laser powder bed fusion. Addit. Manuf. Lett. 2025, 12, 100261. [Google Scholar] [CrossRef]
  14. Kundiya, R.R.; Kadam, M.; Jadhav, P.; Pawade, R. A review on high speed micro-milling of shape memory alloy (NiTinol): Process and post perspective. Int. J. Interact. Des. Manuf. (IJIDeM) 2024, 1–17. [Google Scholar] [CrossRef]
  15. El-Husseiny, M.M.; Baraka, A.A.; Oraby, O.; El-Danaf, E.A.; Salem, H.G. Fabrication of Bimetallic High-Strength Low-Alloy Steel/Si-Bronze Functionally Graded Materials Using Wire Arc Additive Manufacturing. J. Manuf. Mater. Process. 2023, 7, 138. [Google Scholar] [CrossRef]
  16. Khanna, N.; Salvi, H.; Karaş, B.; Fairoz, I.; Shokrani, A. Cost modelling for powder bed fusion and directed energy deposition additive manufacturing. J. Manuf. Mater. Process. 2024, 8, 142. [Google Scholar] [CrossRef]
  17. Özel, T.; Shokri, H.; Loizeau, R. A review on wire-fed directed energy deposition based metal additive manufacturing. J. Manuf. Mater. Process. 2023, 7, 45. [Google Scholar] [CrossRef]
  18. Rahman, M.; Islam, K.S.; Dip, T.M.; Chowdhury, M.F.M.; Debnath, S.R.; Hasan, S.M.M.; Sakib, M.S.; Saha, T.; Padhye, R.; Houshyar, S. A review on nanomaterial-based additive manufacturing: Dynamics in properties, prospects, and challenges. Prog. Addit. Manuf. 2024, 9, 1197–1224. [Google Scholar] [CrossRef]
  19. Sanjeeviprakash, K.; Kannan, A.R.; Shanmugam, N.S. Additive manufacturing of metal-based functionally graded materials: Overview, recent advancements and challenges. J. Braz. Soc. Mech. Sci. Eng. 2023, 45, 241. [Google Scholar] [CrossRef]
  20. Shah, A.; Aliyev, R.; Zeidler, H.; Krinke, S. A review of the recent developments and challenges in wire arc additive manufacturing (WAAM) process. J. Manuf. Mater. Process. 2023, 7, 97. [Google Scholar] [CrossRef]
  21. Sinha, A.K.; Pramanik, S.; Yagati, K.P. Research progress in arc based additive manufacturing of aluminium alloys-A review. Measurement 2022, 200, 111672. [Google Scholar] [CrossRef]
  22. Aldalur, E.; Suárez, A.; Veiga, F. Thermal expansion behaviour of Invar 36 alloy parts fabricated by wire-arc additive manufacturing. J. Mater. Res. Technol. 2022, 19, 3634–3645. [Google Scholar] [CrossRef]
  23. Srivastava, M.; Rathee, S.; Tiwari, A.; Dongre, M. Wire arc additive manufacturing of metals: A review on processes, materials and their behaviour. Mater. Chem. Phys. 2023, 294, 126988. [Google Scholar] [CrossRef]
  24. Vora, J.; Parmar, H.; Chaudhari, R.; Khanna, S.; Doshi, M.; Patel, V. Experimental investigations on mechanical properties of multi-layered structure fabricated by GMAW-based WAAM of SS316L. J. Mater. Res. Technol. 2022, 20, 2748–2757. [Google Scholar] [CrossRef]
  25. Dhinakaran, V.; Ajith, J.; Fahmidha, A.F.Y.; Jagadeesha, T.; Sathish, T.; Stalin, B. Wire Arc Additive Manufacturing (WAAM) process of nickel based superalloys—A review. Mater. Today Proc. 2020, 21, 920–925. [Google Scholar] [CrossRef]
  26. Resnina, N.; Palani, I.; Belyaev, S.; Prabu, S.M.; Liulchak, P.; Karaseva, U.; Manikandan, M.; Jayachandran, S.; Bryukhanova, V.; Sahu, A. Structure, martensitic transformations and mechanical behaviour of NiTi shape memory alloy produced by wire arc additive manufacturing. J. Alloys Compd. 2021, 851, 156851. [Google Scholar] [CrossRef]
  27. Kumar, A.; Maji, K. Selection of process parameters for near-net shape deposition in wire arc additive manufacturing by genetic algorithm. J. Mater. Eng. Perform. 2020, 29, 3334–3352. [Google Scholar] [CrossRef]
  28. Baghel, P.K.; Gupta, T. Optimization of parameters of pulse current gas tungsten arc welding using non conventional techniques. J. Adv. Join. Process. 2022, 6, 100124. [Google Scholar] [CrossRef]
  29. Chaudhari, R.; Vora, J.J.; Mani Prabu, S.; Palani, I.; Patel, V.K.; Parikh, D.; de Lacalle, L.N.L. Multi-response optimization of WEDM process parameters for machining of superelastic nitinol shape-memory alloy using a heat-transfer search algorithm. Materials 2019, 12, 1277. [Google Scholar] [CrossRef]
  30. Ranjan, A.; Das, R.; Pal, S.; Majumder, A.; Deb, M. Performance analysis of porous-based taper-shaped fin for enhanced heat transfer rate using cuckoo search algorithm. Proc. Inst. Mech. Eng. Part E J. Process Mech. Eng. 2024, 238, 1372–1384. [Google Scholar] [CrossRef]
  31. Chen, X.; Wang, S.; He, K. Parameter estimation of various PV cells and modules using an improved simultaneous heat transfer search algorithm. J. Comput. Electron. 2024, 23, 584–599. [Google Scholar] [CrossRef]
  32. Wu, B.; Pan, Z.; Ding, D.; Cuiuri, D.; Li, H. Effects of heat accumulation on microstructure and mechanical properties of Ti6Al4V alloy deposited by wire arc additive manufacturing. Addit. Manuf. 2018, 23, 151–160. [Google Scholar] [CrossRef]
  33. Shen, C.; Reid, M.; Liss, K.-D.; Pan, Z.; Ma, Y.; Cuiuri, D.; van Duin, S.; Li, H. Neutron diffraction residual stress determinations in Fe3Al based iron aluminide components fabricated using wire-arc additive manufacturing (WAAM). Addit. Manuf. 2019, 29, 100774. [Google Scholar] [CrossRef]
  34. Shen, C.; Pan, Z.; Ma, Y.; Cuiuri, D.; Li, H. Fabrication of iron-rich Fe–Al intermetallics using the wire-arc additive manufacturing process. Addit. Manuf. 2015, 7, 20–26. [Google Scholar] [CrossRef]
  35. Dong, B.; Pan, Z.; Shen, C.; Ma, Y.; Li, H. Fabrication of copper-rich Cu-Al alloy using the wire-arc additive manufacturing process. Metall. Mater. Trans. B 2017, 48, 3143–3151. [Google Scholar] [CrossRef]
  36. Chaudhari, R.; Parikh, N.; Khanna, S.; Vora, J.; Patel, V. Effect of multi-walled structure on microstructure and mechanical properties of 1.25 Cr-1.0 Mo steel fabricated by GMAW-based WAAM using metal-cored wire. J. Mater. Res. Technol. 2022, 21, 3386–3396. [Google Scholar] [CrossRef]
  37. Wang, J.; Pan, Z.; Wang, Y.; Wang, L.; Su, L.; Cuiuri, D.; Zhao, Y.; Li, H. Evolution of crystallographic orientation, precipitation, phase transformation and mechanical properties realized by enhancing deposition current for dual-wire arc additive manufactured Ni-rich NiTi alloy. Addit. Manuf. 2020, 34, 101240. [Google Scholar] [CrossRef]
  38. Wang, J.; Pan, Z.; Yang, G.; Han, J.; Chen, X.; Li, H. Location dependence of microstructure, phase transformation temperature and mechanical properties on Ni-rich NiTi alloy fabricated by wire arc additive manufacturing. Mater. Sci. Eng. A 2019, 749, 218–222. [Google Scholar] [CrossRef]
  39. Zeng, Z.; Cong, B.; Oliveira, J.; Ke, W.; Schell, N.; Peng, B.; Qi, Z.; Ge, F.; Zhang, W.; Ao, S. Wire and arc additive manufacturing of a Ni-rich NiTi shape memory alloy: Microstructure and mechanical properties. Addit. Manuf. 2020, 32, 101051. [Google Scholar] [CrossRef]
  40. Chaudhari, R.; Bhatt, R.; Vaghasia, V.; Raja, B.D.; Patel, V.K.; Khanna, S.; Vora, J.; Patel, V.V. A parametric study and experimental investigations of microstructure and mechanical properties of multi-layered structure of metal core wire using wire arc additive manufacturing. J. Adv. Join. Process. 2023, 8, 100160. [Google Scholar] [CrossRef]
  41. Vora, J.; Parikh, N.; Chaudhari, R.; Patel, V.K.; Paramar, H.; Pimenov, D.Y.; Giasin, K. Optimization of bead morphology for GMAW-based wire-arc additive manufacturing of 2.25 Cr-1.0 Mo steel using metal-cored wires. Appl. Sci. 2022, 12, 5060. [Google Scholar] [CrossRef]
  42. Chahdoura, S.; Bahloul, R.; Tlija, M.; Tahan, A. Multi-objective optimization of PLA-FDM parameters for enhancement of industrial product mechanical performance based on GRA-RSM and BBD. Prog. Addit. Manuf. 2024, 10, 1355–1383. [Google Scholar] [CrossRef]
  43. Zhao, Z.; Chen, W.; Xie, X.; Ma, T.; Huang, S.; Xiao, J.; Liang, Z. Wear resistance of Cronidur 30 steel enhanced by optimizing the strengthened grinding process (SGP) parameters using a Box-Behnken design (BBD) method. J. Manuf. Process. 2024, 122, 7–20. [Google Scholar] [CrossRef]
  44. Patel, V.K.; Savsani, V.J. Heat transfer search (HTS): A novel optimization algorithm. Inf. Sci. 2015, 324, 217–246. [Google Scholar] [CrossRef]
  45. Rojas, H.; Vargas, Z.; Valdez, S.; Serrano, M.; del Pozo, A.; Alcántara, M. Taguchi, Grey Relational Analysis, and ANOVA Optimization of TIG Welding Parameters to Maximize Mechanical Performance of Al-6061 T6 Alloy. J. Manuf. Mater. Process. 2024, 8, 246. [Google Scholar] [CrossRef]
  46. Kumar, P.K.; Lokeshwar, G.; Reddy, C.U.K.; Jyotis, A.; Shetty, S.; Acharya, S.; Shetty, N. Effect of drilling parameters on surface roughness and delamination of Ramie–Bamboo-reinforced natural hybrid composites. J. Manuf. Mater. Process. 2024, 8, 195. [Google Scholar] [CrossRef]
  47. Bouloumpasi, E.; Skendi, A.; Christaki, S.; Biliaderis, C.G.; Irakli, M. Optimizing conditions for the recovery of lignans from sesame cake using three green extraction methods: Microwave-, ultrasound-and accelerated-assisted solvent extraction. Ind. Crops Prod. 2024, 207, 117770. [Google Scholar] [CrossRef]
  48. Akritas, M.G.; Papadatos, N. Heteroscedastic one-way ANOVA and lack-of-fit tests. J. Am. Stat. Assoc. 2004, 99, 368–382. [Google Scholar] [CrossRef]
  49. Xu, W.; Lin, S.; Fan, C.; Yang, C. Prediction and optimization of weld bead geometry in oscillating arc narrow gap all-position GMA welding. Int. J. Adv. Manuf. Technol. 2015, 79, 183–196. [Google Scholar] [CrossRef]
  50. Thakur, P.; Chapgaon, A. A review on effects of GTAW process parameters on weld. Int. J. Res. Appl. Sci. Eng. (IJRASET) 2016, 4, 136–140. [Google Scholar]
  51. Kumar, V.; Mandal, A.; Das, A.K.; Kumar, S. Parametric study and characterization of wire arc additive manufactured steel structures. Int. J. Adv. Manuf. Technol. 2021, 115, 1723–1733. [Google Scholar] [CrossRef]
  52. Mistry, P. Effect of process parameters on bead geometry and shape relationship of gas metal arc weldments. Int. J. Adv. Res. Mech. Eng. Technol. 2016, 2, 24–27. [Google Scholar]
  53. Lee, H.-k.; Kim, J.; Pyo, C.; Kim, J. Evaluation of bead geometry for aluminum parts fabricated using additive manufacturing-based wire-arc welding. Processes 2020, 8, 1211. [Google Scholar] [CrossRef]
  54. Chaudhari, R.; Parmar, H.; Vora, J.; Patel, V.K. Parametric study and investigations of bead geometries of GMAW-based wire–arc additive manufacturing of 316L stainless steels. Metals 2022, 12, 1232. [Google Scholar] [CrossRef]
  55. Chaturvedi, M.; Scutelnicu, E.; Rusu, C.C.; Mistodie, L.R.; Mihailescu, D.; Subbiah, A.V. Wire arc additive manufacturing: Review on recent findings and challenges in industrial applications and materials characterization. Metals 2021, 11, 939. [Google Scholar] [CrossRef]
  56. Wu, B.; Pan, Z.; Ding, D.; Cuiuri, D.; Li, H.; Xu, J.; Norrish, J. A review of the wire arc additive manufacturing of metals: Properties, defects and quality improvement. J. Manuf. Process. 2018, 35, 127–139. [Google Scholar] [CrossRef]
  57. Vora, J.; Pandey, R.; Dodiya, P.; Patel, V.; Khanna, S.; Vaghasia, V.; Chaudhari, R. Fabrication of Multi-Walled Structure through Parametric Study of Bead Geometries of GMAW-Based WAAM Process of SS309L. Materials 2023, 16, 5147. [Google Scholar] [CrossRef]
  58. Dutkiewicz, J.; Rogal, Ł.; Kalita, D.; Węglowski, M.; Błacha, S.; Berent, K.; Czeppe, T.; Antolak-Dudka, A.; Durejko, T.; Czujko, T. Superelastic effect in NiTi alloys manufactured using electron beam and focused laser rapid manufacturing methods. J. Mater. Eng. Perform. 2020, 29, 4463–4473. [Google Scholar] [CrossRef]
  59. Kelly, S.; Kampe, S. Microstructural evolution in laser-deposited multilayer Ti-6Al-4V builds: Part II. Thermal modeling. Metall. Mater. Trans. A 2004, 35, 1869–1879. [Google Scholar] [CrossRef]
  60. Yu, L.; Chen, K.; Zhang, Y.; Liu, J.; Yang, L.; Shi, Y. Microstructures and mechanical properties of NiTi shape memory alloys fabricated by wire arc additive manufacturing. J. Alloys Compd. 2022, 892, 162193. [Google Scholar] [CrossRef]
  61. Bae, J.; Lee, H.; Seo, D.; Yun, S.; Yang, J.; Huh, S.; Jeong, H.; Noh, J. Grain size and phase transformation behavior of TiNi shape-memory-alloy thin film under different deposition conditions. Materials 2020, 13, 3229. [Google Scholar] [CrossRef]
  62. Chaudhari, R.; Khanna, S.; Vora, J.; Patel, V. Experimental investigations on microstructure and mechanical properties of wall structure of SS309L using wire-arc additive manufacturing. J. Adv. Join. Process. 2024, 9, 100172. [Google Scholar] [CrossRef]
  63. Qi, Z.; Qi, B.; Cong, B.; Sun, H.; Zhao, G.; Ding, J. Microstructure and mechanical properties of wire+ arc additively manufactured 2024 aluminum alloy components: As-deposited and post heat-treated. J. Manuf. Process. 2019, 40, 27–36. [Google Scholar] [CrossRef]
  64. Wang, L.; Xue, J.; Wang, Q. Correlation between arc mode, microstructure, and mechanical properties during wire arc additive manufacturing of 316L stainless steel. Mater. Sci. Eng. A 2019, 751, 183–190. [Google Scholar] [CrossRef]
Jmmp 09 00058 g001
Figure 1. The GMAW-based WAAM experimental setup.
Figure 1. The GMAW-based WAAM experimental setup.
Jmmp 09 00058 g001
Jmmp 09 00058 g002
Figure 2. Determination of bead morphologies, BW and BH.
Figure 2. Determination of bead morphologies, BW and BH.
Jmmp 09 00058 g002
Jmmp 09 00058 g003
Figure 3. Process chart of the HTS algorithm [44].
Figure 3. Process chart of the HTS algorithm [44].
Jmmp 09 00058 g003
Jmmp 09 00058 g004
Figure 4. A 10-layered nitinol specimen fabricated by WAAM at optimized parameters.
Figure 4. A 10-layered nitinol specimen fabricated by WAAM at optimized parameters.
Jmmp 09 00058 g004
Jmmp 09 00058 g005
Figure 5. Testing locations of the built structure.
Figure 5. Testing locations of the built structure.
Jmmp 09 00058 g005
Jmmp 09 00058 g006
Figure 6. Single-layer depositions along with cut cross-sections of depositions.
Figure 6. Single-layer depositions along with cut cross-sections of depositions.
Jmmp 09 00058 g006
Jmmp 09 00058 g007
Figure 7. Influences of WAAM variables on BH response.
Figure 7. Influences of WAAM variables on BH response.
Jmmp 09 00058 g007
Jmmp 09 00058 g008
Figure 8. Influences of WAAM variables on BW response.
Figure 8. Influences of WAAM variables on BW response.
Jmmp 09 00058 g008
Jmmp 09 00058 g009
Figure 9. Macrostructure of the built WAAM structure.
Figure 9. Macrostructure of the built WAAM structure.
Jmmp 09 00058 g009
Jmmp 09 00058 g010aJmmp 09 00058 g010b
Figure 10. Microstructures of (a) HAZ and initial layers, (b) middle layers, and (c) top layers of the built WAAM structure.
Figure 10. Microstructures of (a) HAZ and initial layers, (b) middle layers, and (c) top layers of the built WAAM structure.
Jmmp 09 00058 g010aJmmp 09 00058 g010b
Jmmp 09 00058 g011
Figure 11. Tensile test specimens (a) after fracture and (b) after fractography.
Figure 11. Tensile test specimens (a) after fracture and (b) after fractography.
Jmmp 09 00058 g011
Jmmp 09 00058 g012
Figure 12. Microhardness along the build direction for a WAAM structure of nitinol SMA.
Figure 12. Microhardness along the build direction for a WAAM structure of nitinol SMA.
Jmmp 09 00058 g012
Table 1. Process condition variables for the deposition of nitinol SMA.
Table 1. Process condition variables for the deposition of nitinol SMA.
Input VariablesSymbolValues with Levels
Wire feed speed (m/min)WFS5; 6; 7
Travel Speed (mm/s)TS10; 12; 14
Voltage V20; 22; 24
Shielding gas-Argon gas with 15 L/min
Feedstock material-Nitinol wire with 1.2 mm diameter
Substrate -Pure titanium
Table 2. Results of bead morphologies as per the BBD design matrix.
Table 2. Results of bead morphologies as per the BBD design matrix.
Std
Order		Run
Order		WFS
(m/min)		TS
(mm/s)		Voltage
(V)		BH
(mm)		BW
(mm)
11510225.637.78
102614205.705.52
113610244.679.20
154612226.076.89
125614245.218.57
146612225.977.03
37514224.835.93
138612226.206.80
29710228.067.87
710512244.218.42
411714227.488.00
812712245.899.32
913610207.056.41
614712207.736.89
515512205.296.06
Table 3. Analysis of variance for bead morphologies of BH and BW responses.
Table 3. Analysis of variance for bead morphologies of BH and BW responses.
SourceDFAdj. SSAdj. MSFP
ANOVA for BH
Model718.02302.574765.55<0.001
Linear315.39125.1304130.61<0.001
WFS110.594310.5943269.70<0.001
TS10.60200.602015.330.006
V14.19494.1949106.79<0.001
Square21.58790.793920.21<0.001
2-Way Interaction21.04390.522013.290.004
Error70.27500.0393--
Lack-of-Fit50.24850.04973.760.223
Pure Error20.02650.0132--
Total1418.2980---
ANOVA for BW
Model619.27353.212295.15<0.001
Linear317.31785.7726170.98<0.001
WFS11.87481.874855.53<0.001
TS11.31461.314638.94<0.001
V114.128314.1283418.48<0.001
Square20.97220.486114.400.002
2-Way Interaction10.98350.983529.13<0.001
Error80.27010.0338--
Lack-of-Fit60.24210.04042.880.280
Pure Error20.02800.0140--
Total1419.5435---
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Vaghasia, V.; Chaudhari, R.; Patel, V.K.; Vora, J. Parametric Study on Investigations of GMAW-Based WAAM Process Parameters and Effect on Microstructure and Mechanical Properties of NiTi SMA. J. Manuf. Mater. Process. 2025, 9, 58. https://doi.org/10.3390/jmmp9020058

AMA Style

Vaghasia V, Chaudhari R, Patel VK, Vora J. Parametric Study on Investigations of GMAW-Based WAAM Process Parameters and Effect on Microstructure and Mechanical Properties of NiTi SMA. Journal of Manufacturing and Materials Processing. 2025; 9(2):58. https://doi.org/10.3390/jmmp9020058

Chicago/Turabian Style

Vaghasia, Vatsal, Rakesh Chaudhari, Vivek K. Patel, and Jay Vora. 2025. "Parametric Study on Investigations of GMAW-Based WAAM Process Parameters and Effect on Microstructure and Mechanical Properties of NiTi SMA" Journal of Manufacturing and Materials Processing 9, no. 2: 58. https://doi.org/10.3390/jmmp9020058

APA Style

Vaghasia, V., Chaudhari, R., Patel, V. K., & Vora, J. (2025). Parametric Study on Investigations of GMAW-Based WAAM Process Parameters and Effect on Microstructure and Mechanical Properties of NiTi SMA. Journal of Manufacturing and Materials Processing, 9(2), 58. https://doi.org/10.3390/jmmp9020058

Article Metrics

Back to TopTop