Friction stir-based additive manufacturing

Abstract

Additive manufacturing (AM) has completely altered the traditional component manufacturing and qualification paradigm. It provides unitisation and topological optimisation opportunities simultaneously. Broadly, the additive manufacturing processes are classified as fusion-based or solid-state. The solid-state additive manufacturing processes are relatively nascent. Among these, friction stir-based processes involve intense shear deformation of material while building. In this review, we focus on friction stir additive manufacturing (FSAM) and additive friction stir deposition (AFSD). These friction stir welding derived techniques have ability to produce microstructures that lead to better mechanical properties than the conventionally processed parent alloys; in many cases overcoming the traditional strength-ductility tradeoff paradigm. The best way to capture this advantage is to conduct materials selection for build which benefit from the attributes of these processes. This review provides a systems approach framework and a conceptual process model to guide researchers. A case is built that the best mechanical properties can be obtained by alloy design for such disruptive and innovative manufacturing processes. The intrinsic and extrinsic limitations are highlighted to guide researchers in the field of FSAM and AFSD. While AFSD is readily applicable to lower melting temperature materials currently, applying it to high-temperature materials requires significant research and development on tool materials. Examples of materials processed by FSAM/AFSD include aluminium alloys, magnesium alloys, titanium alloys, steels and nickel-base superalloy. A physics-based process modelling framework applicable to FSAM/AFSD is provided. To fully validate such models, it is imperative to use machines with appropriate sensors that capture the machine parameters, tool health, and workpiece temperature.

Keywords

Additive manufacturing friction stir additive manufacturing additive friction stir deposition strength-ductility tradeoff alloy design

Introduction

Additive manufacturing (AM) has emerged as one of the most dynamic research areas in the recent years and covers a vast range of activities; from design of machines to multifaceted aspects of materials. The unprecedented topological design and ability to print-on-demand have motivated engineers and opened up new opportunities. Even though the landscape of materials and technologies for AM are vast, there are some organisational principles available for classification. Of course, the materials can be easily classified in polymers, metals, and ceramics, as broader categories. The AM technologies very much depend on which class of materials is of interest. In this review, we have focused on metallic materials. For metallic materials, one can organise the AM processes based on the state of alloys during printing. This gives a simple list of three groups, (a) solid-state processes, (b) liquid-based processes, and (c) semi-solid processes. The friction stir-based AM processes are a sub-set of solid-state AM processes. Palanivel and Mishra [1] have reviewed the technologies for solid-state AM processes. In this review, we want to go deeper into friction stir-based AM processes and emphasise the importance of selecting the right alloys for a specific AM process. Sankaran and Mishra [2] have emphasised that the full potential of a process can be best realised by co-design of alloys and processes.

Fusion vs. plasticity-based solid-state AM processes

The fusion-based AM involves melting and subsequent solidification whereas plasticity-based solid-state AM processes utilise severe plastic deformation [1, 3]. The most popular fusion-based AM techniques involve melting of feed material; powder bed fusion (PBF) and direct energy deposition (DED). In these processes, a high energy laser or electron beam is used to selectively melt the powder particles that are either fed through the nozzle (DED) or pre-deposited on the bed (PBF) [4, 5]. Interaction of these high energy beams with powder particles causes complex physical processes which involves melting, melt flow, and rapid solidification [6]. High cooling rates of the order of 10³–10⁷ K s⁻¹ during PBF and DED processes due to rapid solidification [7] have the prominent impact of the final microstructure [8]. These fusion-based processes have their own pros and cons. Good to reasonable surface finish, capability to print complex geometries, and flexibility in part customisation are some of the advantages of these processes [9]. However, incapability of processing a wide range of non-weldable alloys, very high feed material cost, presence of solidification defects due to liquid–solid phase transformation, low production volume, and high cost of operation [10, 11] currently limit the wide acceptance of fusion-based AM. Furthermore, these processes often result in highly textured columnar grains with anisotropic mechanical properties. As a substitute for fusion-based AM techniques, plasticity-based solid-state AM processes are gaining prominence as they can avoid/eliminate the concerns associated with fusion-based AM techniques. Ultrasonic additive manufacturing (UAM), friction stir additive manufacturing (FSAM), cold spray additive manufacturing [12] and additive friction stir deposition (AFSD) are some of the solid-state additive manufacturing processes [1, 3]. In this review, we mainly focus on friction stir-based additive manufacturing processes.

Friction stir-based AM processes have several advantages over fusion-based AM processes. (1) Solid-state process; Being a solid-state process, the peak temperature achieved during processing generally varies from 60% to 90% of the melting temperature [13]. Parts produced from these processes do not suffer from the issues related with solidification such as hot cracking, high residual stresses, and porosity [4, 14]. Additionally, friction stir-based processes facilitates deposition of non-weldable alloys such as high strength AA 2XXX and AA 7XXX alloys. (2) Feed material; feed material can be plates for FSAM and rods/consolidates for AFSD which can be in either cast or wrought form. Compared to this, the advanced fusion-based AM processes have very restrictive requirements with powder size restrictions [15, 16]. (3) Applicability; friction stir-based AM techniques facilitate manufacturing of wide range of alloys. Friction stir-based techniques also enable manufacturing of dissimilar alloys in a graded fashion. Al alloys, Ti alloys, Mg alloys, and Ni-based super alloys are some of alloys that have been fabricated using this process [3, 13, 17, 18]. Metal matrix composites can also be processed using AFSD which are very difficult to process otherwise. Griffiths et al. [19] processed Al-Mo composite which resulted in uniform distribution of Mo particles in the Al matrix. (4) Microstructure; Friction stir-based processes result in a homogenous recrystallised microstructure. Microstructural features of the fabricated parts are refined, equiaxed, and isotropic [13]. (5) Build volume and speed; Volume of the parts produced by these processes is not size constrained as no vacuum or environment controlled chamber is needed for the process. Parts with dimensions as large as 1.5 m have been deposited. Production rate achieved in AFSD is superior when compared to PBF and DED; for Al alloys, it is 1000 cm³ h⁻¹ [20]. Figure 1 shows the comparison of build rate for friction stir-based processes to other AM processes. Although, friction stir-based AM techniques have superior microstructural and mechanical characteristics, they do have limitations such as, (i) large scale customisation flexibility limited by the bed size, (ii) rate of production limited by the tool traverse speed, (iii) size of features and overall geometrical shapes are limited by the tool size and feedstock size, (iv) tool wear and workpiece clamping issues, (v) necessity of prior weld surface cleaning before the next run, and (vi) presence of significant residual stresses in the build.

Figure 1

A comparison of typical build rates for different AM techniques. The data used in this figure is a generic representation of literature information.

Introduction of friction stir-based AM processes

Friction stir additive manufacturing (FSAM)

The potential of friction stir joining as an AM technology was proposed by White in his patent in 1999 [21]. Lack of further research in this direction resulted in sluggish progression in the following years until Dilip et al. [22] used friction surfacing and friction welding as possible routes for AM. FSAM is a solid-state AM technology which makes use of the principle of friction stir welding (FSW) where multiple plates are friction stir welded, one on the top of other. It was first demonstrated by Airbus and Boeing [23, 24] which was proposed as a potential solid-state manufacturing alternative with the capability to achieve high throughput at faster build rates with minimum material wastage. Similar to FSW, FSAM makes use of a non-consumable rotating tool introduced into the overlapping/abutting metal sheets which is subsequently traversed along the joint line to generate a weld. The heat generated due to friction between the tool and workpiece contact surfaces plasticises the material, which subsequently flows circumferentially and axially around the rotating tool to generate the weld. The process is repeated until the required build height is achieved. Figure 2 shows FSAM for a stiffener-on-skin with very low buy-to-fly ratio (weight of raw material/weight of the final product) which is traditionally machined from a large block of metal in the aerospace industry. A potential application of multilayered stiffened panels is in aerospace and aviation sectors, where stiffeners/stringers can be manufactured by a combination of FSW/FSAM [25].

Figure 2

Schematic diagram of friction stir additive manufacturing (FSAM) of a stiffened panel. Four layers of build are used for this illustration and note that the post-build machining would remove the unbonded side regions.

Interestingly, no research paper was published on FSAM after the 2006 Aeromat presentation [23] until the work of Palanivel et al. [3], where they successfully implemented FSAM in Mg-WE43 alloy and Al 5083 [25]. FSAM resulted in more uniform and homogenous microstructure along the joints in multiple layers with enhanced mechanical properties compared to the base material for these alloys. For example, FSAM of an Mg–4Y–3Nd resulted in almost 13% improvement in strength and a massive 600% increase in ductility [3]. Similar improvement in mechanical properties has been achieved for FSAM in Al 5083, Al 7050, Ti–6Al–4V, Ti6246 as well as P92 and MA956 grade steels (as presented in later sections). The final build height is a multiple of the individual sheet thickness and hence, height control is linked to the sheet thickness. The use of sheets with different thickness is possible to achieve a reasonable geometric control, but this needs extra tooling and parametric optimisation. Some potential applications of FSAM are graded material manufacturing, microstructural refinement for end-product customisation, surface composite manufacturing, and fabrication of stiffened structure for aerospace and other industries [25 -27].

Additive friction stir deposition (AFSD)

AFSD is a solid-state AM process patented by the US-based MELD™ Manufacturing Corporation [28]. Figure 3 shows the schematic of the AFSD technique where a metal feedstock or metal powder consolidation is fed through the AFSD tool. The feedstock is subsequently plasticised at high temperatures by coupled friction stir heating and plasticity-related adiabatic heating, enabling the material to flow as a thick plasticised layer. This plasticised metal is then additively deposited on the substrate to produce the final geometry. Being a recently developed technology, very limited literature is available on AFSD where successful AM of Al-based alloys, Cu, stainless steel, INCONEL 718, and Ti–6Al–4V have been achieved. Advantages such as equiaxed grain microstructure, superior mechanical performance of the build, low final defect fraction, 100% dense final deposit, exceptionally high build rate, adaptability to large-scale customisation, and lower power per pound of build can place AFSD in a superior spot among AM technologies [20, 29].

Figure 3

Schematic of additive friction stir deposition. While there are similarities with the friction stir welding/processing, the process has significant differences in material flow.

Table 1 lists various attributes of FSAM/AFSD and their potential advantages.

Table 1

Attributes and potential advantages of FSAM/AFSD.

Friction stir-based AM techniques (FSAM/AFSD)
Ability to fabricate large components of simpler or limited geometrical complexity.
Faying surface contamination is not vital for most metallic systems.
Ability to bond a variety of materials that are rendered difficult by fusion welding (wide range of material selection). Good for multi-material or dissimilar material printing.
Weld formation is dictated by process forces and tool geometry.
High degree of reproducibility.
Excellent metallurgical property in joint area.
Ability to produce variable microstructures for specific applications (process flexibility).
Judicious use of materials leading to low buy to fly ratio.

Friction stir heating + shear assisted extrusion and deposition + friction welding = AFSD

Compared to other friction stir-based processes such as FSW, Friction stir processing (FSP), and FSAM, AFSD is a rather complex process which integrates multiple concepts. To simplify the analogy, the entire AFSD process can be divided into three phases as indicated in Figure 4. The first phase involves heating up the AFSD tool to the required temperature level before the initiation of deposition. During this process, the tool is moved in a downward direction towards the substrate leaving a very small gap between the substrate and the tool bottom surface. Once the axial position is achieved, the actuator is engaged with the feed rod which is fed at a very low feed rate which initiates the heating of the tool and feed rod due to frictional and deformation/adibatic heating. The heating phase I itself can be further divided into two stages. In the first stage of heating, heat is mostly generated due to contact friction between the substrate and the feed rod. The rate of heating is rather low during this stage. Once the feed rod is heated up reasonably well to initiate plastic flow of the material, subsequent feeding of the rod results in extrusion of the material to fill the small gap between the tool and the substrate which initiates the second stage of rapid heating. Once the material is extruded to fill the gap, heating is achieved by virtue of contact friction between the tool surface and the extruded material as well as between the substrate and the feed rod resulting in rapid heating of the tool and feed rod. Hence phase I of AFSD basically involves friction stir heating to heat up the tool and the feed rod to the required temperature.

Figure 4

Various aspects of additive friction stir deposition including friction stir heating, material extrusion, mechanical stirring, shear assisted deposition, and friction welding explained through three phases of the process.

Once phase I is completed and the required temperature is achieved, the tool is raised to the preferred height which defines the deposition layer thickness and is subsequently traversed along a specified path over the substrate, initiating phase II of the process. Phase II involves extrusion of the feed rod material beneath the tool, stirring of the extruded material due to tool rotation, deposition of the sheared material, and physical bonding of the deposited material to the substrate which is usually the same material as the feed rod. Unlike FSW, where the rotating tool is inserted deep into the plates which subsequently gets welded due to mechanical stirring and shearing of material around the tool, the bonding achieved in AFSD can be correlated to the principles of rotary friction welding (RFW) [30] where bonding is achieved due to synergistic activity of axial compressive force and frictional heat between two rods/plates of similar material rubbed against each other. However, there are significant differences between RFW and AFSD. Primary difference is that RFW is a welding technique whereas AFSD is a deposition and manufacturing technique. Second, in RFW the major surface of frictional heating and the location of weld are the same; the weld is formed at the location of primary heat generation. However, in AFSD the major surface of heat generation is different from the location of weld/bond. Heat is mostly generated at the top surface of the layer where the tool contacts the extruded material whereas the bonding is achieved at the bottom layer of the deposit utilising the heat conducted form the top layer and the axial compressive force exerted by the tool and actuator. Hence mechanical bonding in AFSD is achieved by ‘pseudo’ RFW (an element of forge bonding).

Third phase of AFSD involves subsequent layer deposition by retracting the tool in multiple steps and traversing it along the specified path after completion of each layer. During this process, the principle of heating, extrusion, shear assisted deposition, and bonding are the same as explained in phase II of the process. However, during deposition of subsequent layers the bonding is achieved between the newly deposited layers and the penultimate layer rather that the substrate and the deposited layer as in phase II. From the above discussion AFSD process can be defined as follows:

AFSD is a solid state progressive AM technique where the material to be deposited is heated to a high temperature below its solidus temperature by virtue of frictional heating beneath the rotating AFSD tool which facilitates extrusion of the plasticized material through the tool under an axial compressive force and subsequent shear assisted deposition as the tool traverses. Bonding between multiple deposited layers is ensured by pseudo FW.

Although heat generated in AFSD is comparable to other friction stir-based processes, there are major differences when thermal and plastic flow boundary conditions are considered. In FSW/FSP, a rotating tool with a shoulder and protruded pin is spun inside the material (no new material), whereas in AFSD, the material (in stir zone (SZ)) is constrained by the surrounding tool material; majority of heat is dissipated from SZ by conduction as shown in Figure 5. Furthermore, the heat is generated between the end surface of the hollow tool shoulder-metal feedstock and the substrate or previously deposited layer. Also, unlike FSW the deposited layer is not laterally constrained in AFSD and hence the heat dissipation from the deposition zone can be by conduction, free convection, and radiation, Figure 5.

Figure 5

Schematic illustration of mode of heat transfer from different surfaces/regions in FSW/P and AFSD.

Examples of applicability of FSAM and AFSD to various alloys

This section highlights application of FSAM and AFSD to various alloys. The purpose is to bring out guiding principles for selection of alloys that are suitable for these processes. Maximum benefit can be derived by considering the attributes of these processes and cross link with metallurgical aspects of the alloys.

Al alloys

Wrought aluminium alloys are classified into two broad categories, (a) non-age hardenable (alloys in 1XXX, 3XXX, and 5XXX series), and (b) age hardenable (2XXX, 6XXX and 7XXX series) [2]. Strengthening mechanisms for non-age hardenable alloys include grain size strengthening, solid solution strengthening and dislocation density strengthening. Age hardenable alloys have precipitation strengthening as the primary mechanism. Efficacy of FSAM and AFSD depends on the specific alloys. Palanivel et al. [25] successfully performed FSAM on AA 5083-O alloy by successively welding four sheets at a tool rotational rate of 500 rev min⁻¹ and a tool traverse speed of 152 mm min⁻¹. Note that AA 5083-O alloy only uses grain boundary strengthening and solid solution strengthening mechanisms. Macrograph of the weld, hardness profile along the centre line and tensile property of the material are shown in Figure 6. A substantial improvement in hardness can be observed (improved by 18%) over the entire layer thickness compared to the base material (Figure 6(b)). The variation in hardness is attributed to the microstructural variation in the layers due to thermal and strain gradients. Tensile characteristics shown in Figure 6(c) is consistent with hardness increase, where the YS improved from 190 to 267 MPa and the UTS improved from 336 to 362 MPa. However, there is a knockdown in ductility of the material in the welded region, implying a traditional tradeoff of the strength and ductility in this alloy.

Figure 6

(a) Macrograph of an AA5083 alloy fabricated using FSAM at 500 rev min⁻¹ and 152 mm min⁻¹. The horizontal dashed lines represent the plate interfaces, (b) microhardness profile along the centre line of the build where the dash-dot line represents the hardness of the base material, and (c) engineering stress-strain response of the base material and the build [25].

Later, Yuqing et al. [27] successfully applied FSAM on AA 7075-O plates and obtained a stack of 9 metal layers at weld parameters of 600 rev min⁻¹ and 60 mm min⁻¹. Note that unlike the AA 5083-O alloy, the AA 7075 alloy is designed to take advantage of precipitation strengthening. So, the temper selection of initial material becomes an important criterion. Microstructural analysis revealed a variation in grain size and precipitate morphology along the weld thickness. The top layer was characterised by the presence of recrystallised equiaxed fine grains whereas the successive bottom layers were characterised by slightly coarser grains with subtle changes in grain morphology at the transition layers. Similarly, a visible variation in the morphology of the secondary phases (η and T phases) was also observed at different locations of the build. Locations subjected to tool shoulder heating were characterised by the presence of coarser precipitates, whereas finer precipitates decorated the SZ. The variation in secondary phase distribution in the weld is attributed to local temperature and strain differences as well as the thermal cycles through which each layer goes through, controlling the precipitate evolution at specific locations. Microhardness measurement along the centre line of the weld indicated an increase in hardness form bottom to top of the weld (Figure 7(a)). Such variation in hardness is also reflected as an increase in tensile strength of the weld compared to the base material (Figure 7(b)). Although an increase in tensile strength was observed post welding in AA 5083 and AA 7075 at the expense of tensile ductility, FSAM of cast AA 2050 and T3 tempered alloys indicated a knockdown in tensile strength with an improved ductility (Figure 7(c)) [31]. The difference in mechanical properties in various classes of Al alloys necessitates the requirement of proper choice of material for FSAM and the need for a systematic alloy selection and design strategies.

Figure 7

Microhardness profile along the centre line of the weld in AA 7075 build, (b) corresponding tensile properties at different locations of the build (adopted from data in [27]), and (c) tensile characteristics of AA 2050 material after FSAM (adopted from data in [31]).

The first comprehensive work on AFSD of Al alloy was published in 2018 by Rivera et al. [29]. They correlated the processing-structure–property in a precipitation hardened AA 2219-T851 alloy. Significant grain refinement was observed in the deposited material as compared to the base material (Figure 8(a)). Similar to the trend observed after FSAM of AA 2050 alloy [31], the microhardness along the deposit thickness indicated a gradual increase from bottom to top (Figure 8(a)), whereas the grain size remained more or less similar (2.5 µm) through the build. The occurrence of dynamic recrystallisation was evidenced by the presence of low angle grain boundaries in the deposited microstructure. Additionally, the presence of and { torsional type A texture was observed at the top of the build whereas a combination of type A and type C texture was observed at the middle and bottom of the build (Figure 8(b)). However, the tensile strength of the deposit was inferior (57% reduction) when compared to the T851 tempered alloy whereas the ductility improved by 130%. The loss in strength was due to the dissolution of strengthening θ’ precipitates in the microstructure.

Figure 8

(a) EBSD micrographs indicating the grain size of AA 2219 AFSD rod, deposited AA 2219 material, and microhardness variation along the thickness of the deposit. (b) Microstructural texture at the top, middle and bottom of the deposit (adopted from data in [29]).

Phillips et al. [18] studied the influence of process parameters on the microstructural evolution in AA 6061-T651 Al–Mg–Si alloy and developed a process parameter window for obtaining defect-free runs. Refined microstructures were obtained for both slower and faster runs, but the hardness values of the deposit were almost 20–35% lower than that of T651 tempered alloy. Dissolution of β and β' precipitates because of high strain and temperature conditions that prevail during deposition and re-precipitation as Mg–Si rich clusters resulted in the loss of hardness/strength. Further, Perry et al. [32] studied the microstructural and morphological variations occurring at the interface of successive deposits of AA 2024 and AA 6061 Al alloys. Microstructural analysis revealed a uniform distribution of fully recrystallised microstructure throughout the AA 2024 build which indicates the consistency of temperature and deformation during the build. However, AA 6061 microstructure revealed partially recrystallised regions and a non-uniformity in the microstructure of the deposit. Avery et al. [33] studied the influence of microstructure and grain refinement on fatigue properties of AFSD made AA 7075 alloy. The fatigue specimens were machined along the build direction even though there is a hardness variation along the build axis of the deposit. A knockdown of tensile strength by 50% was observed, indicating a lack of retention of strengthening mechanisms in this alloy after AFSD. The potential of AFSD as a repair process [34] and an alternative for manufacturing of metal-matrix composites [19] were also demonstrated on Al alloys. Furthermore, Jordon et al. [35] utilised compacted machining chips of AA5083 alloy as the feedstock rod for AFSD and illustrated the possibility of AFSD as an efficient recycling technique which leads to sustainable manufacturing, energy conservation, and lower carbon footprints.

Above discussion on FSAM and AFSD of aluminium alloys reveals the importance of alloy selection for such solid-state AM techniques. Studies revealed a knockdown of tensile strength of the deposit compared to the base material in precipitation strengthened aluminium alloys due to dissolution of strengthening precipitates during processing whereas an improvement in strength is observed in certain other class of alloys. Successful demonstration of recycling capability of the AFSD process using aluminium metal chips also points towards a sustainable manufacturing pathway which satisfies the demand for greener technologies.

Ti alloys

Titanium alloys possess higher absolute and specific strength values at temperatures up to about 550°C and they show excellent corrosion and oxidation resistance. Titanium alloys are classified as (a) α alloys, (b) α+β alloys, and (c) β alloys [2]. The primary strengthening mechanisms are solid solution strengthening and interfacial strengthening. Additive manufacturing of Ti alloys is of special interest due to their attractive properties and broader applications, including interest to increase buy-to-fly ratio for aerospace applications. FSAM has been successfully demonstrated to form fully dense, defect-free structures in α+β Ti–6Al–4V (Ti64) alloy and high strength near β Ti–6Al–2Sn–4Zr–6Mo (Ti6246) alloy. Successful FSAM processing conditions for Ti64 are given in Table 2.

Table 2

Successful parameters that produced defect-free FSAM on Ti64 sheets.

Alloy plates	Layer	Rotational speed	Traverse speed	Angle of tilt	Observation
Ti64 on Ti64	First	250 rev min⁻¹	50.8 mm min⁻¹	2.5°	No defect observed
Ti64 on Ti64	Second	400 rev min⁻¹	50.8 mm min⁻¹	2.5°	No defect observed

Three Ti64 sheets were successfully stacked and processed using FSAM resulting in two overlapping weld nuggets. Image of the successful three-stack produced is shown in Figure 9(a) and the cross-section is shown in Figure 9(b) [36]. Tensile tests performed on mini-tensile samples taken from the plane parallel to build direction indicated superior properties compared to the base material (Figure 9(c) and Table 3). The fractograph obtained on the failure surface after the tests showed a dimpled ductile fracture.

Figure 9

(a) Additive manufacture of three sheets of Ti-6-4 over Ti-6-4 (b) cross-section of FSAM plates showing defect-free joints (c) engineering stress-strain curve of FSAM Ti-6-4 from the nugget region (d) fractograph of the tensile samples from FSAM Ti-6-4 [36].

Table 3

FSAM of Ti64: Tensile properties of the samples at different regions.

Sample	Yield Strength	Tensile Strength	Ductility
Ti-6-4 over Ti-6-4	1105 MPa	1168 MPa	16.5%
Ti-6-4 Base	941 MPa	1014 MPa	21.1%

FSAM parameters used for Ti6246 were 250 rev min⁻¹ and 50.8 mm min⁻¹ traverse speed. For this set of parameters, the sheets were stacked with a 4 mm offset to produce a slant-ribbed structure. Baseplate used for the build was Ti64 having a thickness of 3 mm. Figure 10(a) shows the cross-section of the FSAM build. Tensile samples obtained from a plane parallel to build direction showed excellent mechanical properties (Figure 10(b)) indicating the absence of defects in the build. Similar to Ti64 build, the fracture surface of Ti6246 also indicated ductile fracture (Figure 10(c)).

Figure 10

(a) FSAM nuggets in slanted ribbed structure showing fully dense, defect-free structure, (b) engineering stress-strain curve of FSAM Ti-6246 from the nugget region, and (c) fractograph of the tensile samples from FSAM Ti-6246 [36].

A comprehensive study was also performed on AFSD of Ti64. As-deposited material is shown in Figure 11(a). Microstructural analysis was performed on the strip taken out from the plane parallel to build direction. Figure 11(b) shows backscattered images of the as-printed sample. Microstructure consists of both α and β phases with a variation in prior β grain size from top to bottom as shown in Figure 11(b).

Figure 11

(a) Image of additive friction stir deposited Ti64, and (b) backscattered images of Ti64 from the plane parallel to build direction [37].

Ti alloys manufactured by FSAM and AFSD processes showed an excellent combination of mechanical properties as depicted above. Hence solid-state AM can be a potential AM route for manufacturing high performance Ti components.

Mg alloys

Research on Mg-based alloys is on a rise because of interest in light-weight materials. Although several work has been done to establish the possibility of FSW/FSP in Mg alloys [38 -42], the potential of friction-stir-based process as an alternative AM process in Mg alloys have been hardly explored, except the work of Palanivel et al. [3]. They introduced FSAM as a potential AM process for structural performance enhancement by successfully implementing in Mg-based WE43 alloy (Mg–Nd–Y alloy). The WE43 alloy uses solid solution strengthening, precipitation strengthening, and grain boundary strengthening. The builds were made using two different processing parameters, namely, 800 and 1400 rev min⁻¹/102 mm min⁻¹. Although the microhardness exhibited inhomogeneous variation along the thickness, an average hardness of 115 HV was obtained in the as-built condition. The hardness further improved to 135 HV upon aging at 160°C for 60 hr, and this hardness value is comparable to AA 2XXX series Al alloys (Figures 12(a,b)). The build made using parameters of 1400 rev min⁻¹/102 mm min⁻¹ resulted in a strength enhancement of 20% and ductility improvement of a massive 430% (Figure 12(c)) compared to the rolled plates. A closer look at the hardness profile revealed that the lower hardness values were associated with the interface regions and the higher hardness values were associated with the SZ regions. The microstructure was further analysed to correlate the hardness with the precipitate evolution. High strain, temperature, and multiple thermal cycles resulted in different levels of precipitate dissolution, coarsening and/or re-precipitation at different locations (Figure 13). The presence of intermetallics at the interfaces revealed that the temperature and strain were insufficient for their dissolution. The crown region of the weld which was subjected to shoulder related heating and flow were characterised by coarser precipitates due to higher heat input, whereas the pin dominated flow region was characterised by intermetallic dissolution and grain boundary precipitation. The lack of literature on FSAM/AFSD of Mg alloys shows the immense opportunities of advanced research potential on solid-state AM of Mg alloys.

Figure 12

Microhardness profile along the centre line of the weld for (a) 800 rev min⁻¹ and 102 mm min⁻¹, (b) 1400 rev min⁻¹ and 102 mm min⁻¹ and, and (c) stress-strain distribution of the material before and after AM [3].

Figure 13

BSE images showing distribution of precipitates in (a) layer 4, (b) layer 3–4 interface, (c) two-pass region in layer 3, and (d) one pass region in layer 3. (The examined regions have been annotated in the schematic at the center of the figure (adapted from data in [3]).

Steels

Steels have overwhelming dominance in the materials world because of their innumerable varieties of microstructure and properties. The classification of steels is more complicated than the aluminium, titanium, and magnesium alloys. The strengthening mechanisms, of course, depend on the specific steel used. A number of studies have been published on FSP/FSW of steels. FSAM was performed for P92 grade steel (9Cr–2W) and MA956 steel (oxide dispersion strengthened steel) with the goal of creating a synergistically designed creep-resistant component/structure [43]. Polycrystalline cubic boron nitride (PCBN) tool was used for processing of P92 steel and the parameters used for processing were tool rotation speed of 500 rev min⁻¹ and linear traverse speed of 1 inch per minute (denoted as 500/1). Three P92 steel plates were joined with a total height of 12 mm, shown in Figures 14(a,b). A clearly defined nugget and heat-affected zone (HAZ) were observed in the as-built P92 steel (Figure 15(a)). Figures 15(b,c) shows a magnified view of the nugget region. The microstructure of the nugget region is characterised by refined grain structure with a very fine lath structure inside the grains.

Figure 14

(a) Three P92 plates stacked by FSAM measuring 12 mm thick, and (b) final FSAM structure with a total seam measuring 280 mm [43].

Figure 15

(a) The etched steel sample showing the nugget, heat affected zone and the base regions, (b) refined grain structure with a fine interior lath structure, and (c) unaltered base microstructure with finely tempered martensite [43].

Stress–strain curves of specimens from the nugget region, tested at a strain rate of 10⁻³ s⁻¹ at room temperature and 500°C, are shown in Figure 16(a). The yield strength of the processed region was roughly two times (1235 MPa) the base material (610 MPa) (Figures 16(a,b)) while retaining similar ductility; therefore overcoming the traditional strength-ductility tradeoff. The high strength achieved after processing is attributed to microstructural refinement as well as the presence of fine lath structures. A similar increase was observed in microhardness (Figure 16(c)), i.e. hardness values obtained in the nugget are roughly two times that of the base material. This is a critical observation! FSAM can produce a microstructural condition that can significantly outperform conventionally processed alloy. It opens a strategy of designing components where layers can be added by FSAM in critical areas needing high performance. Such an approach can provide design flexibility without changing the composition of alloy and lead to very high structural efficiency.

Figure 16

(a) Stress-strain curves of P92 FSAM structures at room temperature as well as 500°C, (b) summary of tensile test results, and (c) hardness mapping of P92 steel [43].

Recently, successful AFSD of SS316 has been achieved using a Lanthanated Tungsten tool on a MELD machine. A 10 mm high hollow cylinder of SS316 was deposited using MELD (Figure 17(I)). Figures 17(a), (b), and (c) show inverse pole figure (IPF), image quality (IQ), and misorientation angle distribution, respectively, for SS316 base material. Microstructure of the base material consisted of equiaxed grains of austenitic phase with an average grain size of ∼50 µm and a high density of annealing twins was observed in the base material. Grain structure of the base material was dominated by high angle boundaries (90%). Figures 17(d), (e), and (f) are inverse pole figure, image quality map, and misorientation angle distribution, respectively, for MELD deposited SS316. Average grain size in MELD deposited SS316 was reduced to ∼8 µm and the misorientation angle was changed to a low angle boundary fraction of 45%. Twin boundary fraction was reduced in MELD deposited SS316 as twin boundaries disintegrate due to severe plastic deformation and recrystallisation [44, 45]. Similar observations were made for the friction stir processed SS316 [46].

Figure 17

AFSD of SS316 (I) Image of SS316 deposit, (a) IPF map, (b) IQ map, and (c) misorientation angle distribution of SS316 base material and corresponding (d) IPF map, (e) IQ map, and (f) misorientation distribution of the deposited material [47].

Ni-based alloys

Ni-based superalloys are used in aerospace, marine, and chemical industries which demand high-temperature mechanical stability, including strength, ductility, and creep resistance. The primary strengthening mechanisms include precipitate strengthening (coherent γ’ precipitates) and solid solution strengthening. AM using fusion-based processes of Ni-based superalloys have been widely reported [48 -50] and there are a few studies available on AFSD as well. Rivera et al. [13] reported successful AFSD of INCONEL 625 (Figures 18(a,b)). Significant grain refinement was observed in the case of the AFSD samples. Also, EBSD microstructure (Figure 18(c)) revealed the presence of equiaxed and finer grains in the deposit and the grain refinement was superior at the interface. Tensile testing of AFSD INCONEL 625 showed that the AFSD process resulted in higher YS and UTS for INCONEL 625 when compared to fusion-based AM, cast, and wrought data reported in the literature. Difference in grain morphology and microstructure between the AFSD IN625 and other AM processed INCONEL 625 contribute to the difference in the mechanical properties. Table 4 presents the YS and UTS of INCONEL 625 built using different manufacturing processes. Again, a significant increase in strength with very good ductility is noted for AFSD specimens. INCONEL 625 alloy uses only grain boundary strengthening and solid solution strengthening. It shows the potential of overcoming traditional strength-ductility tradeoff!

Figure 18

Optical micrograph comparing the microstructure between (A) as-received INCONEL 625 filler material, (B) as-build AFS INCONEL 625, and (C) Euler EBSD maps of 5 locations along build direction, all images are at the same magnification and same location in the corresponding axis [13].

Table 4

Comparison of INCONEL 625 microstructure, yield strength and ultimate tensile strength of different manufacturing processes [13].

Condition	Grain morphology	Yield Strength (MPa)	Ultimate tensile Strength (MPa)	Elongation (%)
Cast		350	710	48
Wrought		490	965	30–50
AFSD	Equiaxed	730	1072	32
Electron beam melting	Columnar	410	750	44
Selective laser melting	Dendritic	380	900	58
Friction stir welding	Equiaxed	–	1152	35

Fatigue tests were reported for AFSD INCONEL 625 samples (Figure 19) [51]. Fatigue results revealed the advantage of higher strength-ductility combination. The as-deposited INCONEL 625 material exhibited improved fatigue properties compared to the feedstock material. However, for some of the specimens, delamination of interface layers might have initiated fatigue cracks resulting in a lower number of cycles to failure. As deposited INCONEL 625 shows higher crack growth resistance which is attributed to the refined microstructure with abundant grain boundaries, non-preferred crystallographic orientation, and refined carbides. Clearly, further improvement in AFSD has the potential to push the fatigue properties higher and eliminate the premature crack nucleation at the layer interfaces.

Figure 19

Stress-life fatigue results comparing as-deposited INCONEL 625 to the feedstock, cast, and laser consolidation materials [51].

Compilation of all the AFSD data

Table 5 lists alloys deposited via AFSD till date along with the process parameters used, mechanical properties, and microstructure. It provides a quick assessment of the progress made with this new technology in a short time with only a few group of researchers working.

Table 5

List of alloys deposited by AFSD available in the literature till date.

Material	Rotational rate (RPM)	Travel speed (inch min⁻¹)	Microstructure	Hardness (HV)	Yield Strength (MPa)	Ductility (%)	Reference
Al-Mg-Si	200	1	Fine-grained structure with an average grain size of 10 µm and LABs fraction of 32.2%.	45.4	–	–	[52]
	600	1	Fine flattened elongated grains observed, with average grain size of 16 µm.	53.3	–	–
	600	3	Fine flattened elongated grains observed, with much coarser grains.	67.3	–	–
Cu	300	1	Equiaxed grains with heterogeneous grain structure, large grains intermixed with smaller grains	72.7	–		[52]
	600	1	Equiaxed heterogeneous grain structure with peak grain size of 10 µm.	59.6	–	–
	600	3	Wide grain size distribution and shows high grain size as compared to base material	38	–	–
Al-2024	300	4.7	Equiaxed grains with an average grain size of 4.7 µm	–	–	–	[32]
AA-7075	250	3.4	Fine equiaxed grains with average grain size of 3.5 ± 1 µm	180	477	8.2	[53]
Al-SiC	–	–	Fully dense crack or pore free deposit with uniform distribution of reinforcement particles.	–	–	–	[19]
Al 6061-Mo	–	–	Fully dense crack or pore free deposit with uniform distribution of reinforcement particles.	–	–	–	[19]
Al 6061-W	–	–	Fully dense crack or pore free deposit with uniform distribution of reinforcement particles.	–	–	–	[19]
IN 625	–	–	Fine equiaxed grains with average grain size of 0.5 µm.	–	730	32	[13]
AA-2219	–	–	Fine equiaxed grains with average grain size of 2.5 µm, reducing from top to bottom along the build direction.	80	159	25	[29]
Al-Si-Mg	300	5	93% reduction in grain size observed compared to feed material, nanoscale Mg-Si clusters observed.	73.6 ± 3.2	–	–	[18]
	300	9	Fine equiaxed grains with size 15 ± 4 µm and 5 nm Mg-Si clusters observed.	91.0 ± 7.0	–	–
AA-7050	225	2	S – phase particles at the grain boundary and centre, precipitate size is smaller at final layers as compared to initial layers of the deposit	∼155–55	∼225	–	[54]
AA-5083	–	–	Fine equiaxed grains with grain size 1.5 µm	57.7 ± 6	170.4 ± 7.5	18	[35]
AA 7075	225	2	Zn-Mg-Cu precipitates at the grain boundaries and centre in the Al matrix with average grain size of 4.77 µm.	∼105–60	140	16	[33]
SS316	–	–	Fine equiaxed grains with grain size 8 µm and a high fraction of low angle grain boundaries.	225 ± 2	520	40	To be published
Ti64	–	–	Fine equiaxed prior β grains with grain boundary α and lamellar α/β colonies inside	335 ± 5	1050 ± 25	7 ± 1	[37]

Process variable-microstructure-strength correlations

Framework of a systems approach for AFSD

AFSD is a disruptive manufacturing technology. As highlighted in Section 4 of this paper, AFSD uses multiple concepts and has some unique process attributes. Sankaran and Mishra [2] have highlighted the need to select material appropriately for advanced manufacturing processes. In particular, they have pointed to the need for new alloy development for taking the fullest advantage of the capabilities of new manufacturing processes. As demonstrated through the P92 steel example in FSAM, the improvements in performance can be extraordinary! Olson's [55] system approach creates a good processing-microstructure-properties-performance framework. This is slightly modified in Figure 20 to explicitly include the ‘alloy chemistry’ column. The suitability of alloys for AFSD and FSAM depends on what happens to the alloying effect during processing. For example, will the HAZ in between two AFSD layers be weaker because of adverse microstructural features? For conventional precipitation strengthened alloys (2XXX or 7XXX) in T6 or T8 temper, that would be the case because of dissolution/coarsening of strengthening precipitates. So, designing aluminium alloys that have coarsening resistance at the AFSD processing temperature would be one way to avoid the knockdown in properties in the HAZ. In general, designing alloys that improve properties due to intense shear deformation and controlled thermal cycle would provide very high structural efficiency in components built by AFSD and FSAM.

Figure 20

A systems approach that includes the alloy chemistry, which can effectively incorporate the integrated computational material engineering (ICME) framework for alloy design or alloy selection for additive friction stir deposition.

Microstructural control framework for AFSD and FSAM

Friction stir-based AM techniques such as FSAM and AFSD involve the synergistic activities of high temperature, strain rate and plastic flow of material to obtain a sound weld between multiple layers [1, 56]. Each of the above-mentioned process variables depends on external factors such as rate of tool rotation, tool traverse speed, as well as the tool material and design [56]. In the case of AFSD, the metal rod feed rate is an additional factor [20]. The influence of process parameters on the weld microstructure and mechanical properties in FSW/FSP for different classes of materials has been very-well studied before [57, 58]. Additionally, for FSAM/AFSD of alloys prone to oxidation (e.g. Ti-based alloys), provision of an inert gas supply is desired to eliminate oxide layer formation at interfaces. Process parametric optimisation is the method by which optimum combination of process parameters, tool material and tool design are developed for a specific material to obtain a defect-free weld with a desired microstructure and enhanced mechanical properties, while minimising microstructural contamination from external atmosphere and tool. For process parametric optimisation, a process variable-microstructure-strength correlation is required. Figure 21 shows the flow diagram for the microstructural design framework aimed to achieve a process variable-microstructure-mechanical performance correlation for friction stir-based AM techniques.

Figure 21

Microstructural design framework guiding high-temperature structural performance by FSAM/AFSD.

Process modelling driven parametric optimisation

In FSAM/AFSD, an alloy undergoes microstructural modification in the SZ as well as the HAZ by means of plastic flow at high temperatures achieved by frictional heating [59]. Specific modifications in the microstructure such as grain refinement, evolution of secondary phases and precipitates improve the mechanical properties in SZ and HAZ in certain alloys (e.g. Ti-based alloys [60]) whereas they deteriorate the mechanical properties in some other alloy groups (e.g. precipitation hardened Al-alloys [61]). Mechanical properties of the post-processed alloy heavily depend on the thermal and plastic flow cycles, which directly relates to the initial microstructure of the alloy, friction stir process parameters, tool geometry as well as the method of heat extraction from SZ [59]. Process parameters and rate of heat extraction must be optimised for each material to achieve a defect-free build and maximise performance.

Development of a successful process model demands understanding of the interplay between multiple process parameters during FSAM and AFSD. Since FSAM is based on the principle of FSW, the conceptual model proposed by Colligan and Mishra [62] provides the right direction to understand the influence of multiple process parameters on FSAM. Although AFSD is based on the principles of friction stir heating and plastic deformation, the process differs from FSAM in terms of heat transfer and mode of operation. An additional parameter, namely, feed rate of feed rod has a prominent influence on obtaining a successful deposit. A case study has been carried out for AFSD of SS 316 using a Lanthanated Tungsten tool having specifications provided in Table 6. Actuator force and spindle torque were recorded during the runs and Figure 22 shows the variation of actuator force, spindle torque, power, and specific energy as a function of tool rotational rate. Both actuator force (force required to push the feed rod downward through the tool) and spindle torque were observed to reduce with spindle rotation rate for a constant feed rate of feed rod and tool traverse speed. However, power and specific energy monotonously increased with an increase in spindle rotation rate. Observations in Figure 22 were correlated with the process parameters through a conceptual model shown in Figure 23. In the figure, the upward influence of a process parameter on a performance variable is indicated by a solid black arrow and downward influence of a process parameter on a performance variable is indicated by a solid grey arrow. A black dashed line indicates a neutral influence.

Figure 22

Variation of spindle torque, power, actuator force, and specific energy as a function of spindle rotation rate for AFSD of SS316 using a Lanthanated Tungsten tool.

Figure 23

A conceptual model indicating the interplay between multiple variables as a function of spindle rotation rate in AFSD.

Table 6

AFSD tool specifications and process parameters used for deposition of SS 316.

Tool material	Lanthanated Tungsten
Tool diameter	25.4 mm
Tool contact face features	None
Feed rate of feed rod	25.4 mm min⁻¹
Tool rotational speed	400, 600, and 800 rev min⁻¹
Tool travel speed	254.0 mm min⁻¹

Following inferences can be drawn from the conceptual model.

Figure 22 illustrates that the spindle torque reduces with an increase in spindle rotation rate whereas the power and specific energy reduce accordingly. Hence, the conceptual model specifies the spindle torque to have a downward influence on power and specific energy.

Additional inference from Figure 22 is the increase in power and specific energy as a function of spindle rotation rate for a constant feed rate of feed rod and traverse speed. Hence Figure 23 conceptualises the upward influence of spindle rotation rate on power and specific energy. With an increase in power and specific energy, an increase in peak temperature and overall temperature distribution in the deposit is expected since the thermal boundary conditions and the mode of heat transfer remain the same. However, experimental validation of temperature during deposition is lacking.

The model further envisages that an increase in the overall temperature of the deposited layer exerts a downward trend on flow stress of the deposited layer and the coefficient of friction between contact face of the tool and the deposited layer. Microstructural variations in the deposits are expected due to change in temperature and plastic flow conditions of the material.

Apart from frictional heating, adiabatic heating also contributes to the thermal softening of the feed rod. Increasing spindle rotation rate therefore provides additional deformation induced heating and contributes to a downward influence on flow stress and coefficient of friction. Another aspect of increasing the spindle rotation rate is related to strain rate of deformation. Since AFSD is a shear assisted process, an increase in spindle rotation rate increases the strain rate of shear deformation and subsequent increase in the flow stress which counteracts the effect of adiabatic heating. However, the strain rate factor is dependent on how rate sensitive the material of deposition is. Additionally, it has been shown previously in FSP that the spindle torque monotonously reduces with an increase in spindle rotation rate even beyond the point where a significant temperature rise is not observed which suggests rather stronger influence of deformation-induced heating on flow stress than strain rate effects.

The model also predicts that the contact friction increases with an increase in the feed rate of the feed rod when other process parameters are kept constant. With an increase in feed rate, the axial compressive force, as well as the transverse force increase as more energy is needed to shear the material resulting in an upward influence on the contact friction. With a variation in spindle rotation rate, the influence of compressive force on contact friction counteracts the decrease in contact friction at higher spindle rotation rate. Additionally, the provision of features on contact surface of the tool directly influences the contact friction between the tool surface and deposited layer.

Drop in flow stress and frictional force with an increase in spindle rotation rate reduces the spindle torque as evident from Figure 22. The model conceptualises this effect by indicating an upward trend on spindle torque with an increase in friction and flow stress. Additionally, spindle torque is expected to increase with an increase in tool traverse speed which is indicated by an upward trend in the model. Since AFSD is a material deposition technique, volume deposited per rotation of the tool directly influences the spindle torque. For a constant feed rate of the feed rod, the material volume deposited per rotation decreases which further reduces the spindle torque as indicated in Figure 23.

At present, an Edisonian approach is used to optimise the friction stir process parameters, which is tedious, time-consuming, expensive, and energy-inefficient, all at once. Necessity of such numerous runs can be minimised by developing and using an appropriate process model, where a synergistic combination of physics-based thermomechanical-plastic flow model and thermodynamic model can predict the final microstructure and mechanical properties of the post-processed alloy.

Extensive research has been performed in FSW/FSP by developing numerical models and analytical models to analyse the thermal cycle, material flow, and residual stresses developed during welding/processing. He et al. [63] have reviewed various numerical analysis techniques performed in FSW to analyse various process aspects. Nourani et al. [64] have also briefly reviewed the thermomechanical models developed for FSW to analyse the thermal variables during FSW/FSP. Frigaard et al. [65] were one of the frontrunners to develop a process model to estimate the heat flow and temperature development in an FSP/FSW process. Later, Schmidt and Hattel [66] developed an analytical model to predict the temperature during FSP based on the contact condition between the tool and the workpiece. Various aspects of FSW/FSP were captured by other numerical models. Key examples are strain and residual stresses during the process analysed by computational mechanics models [67 -70], temperature and heat generation captured by thermal models [71, 72] and material flow around the tool modelled using CFD [73, 74], microstructural evolution analysis using kinetic models, and multi variable analysis by multi-physics models [75 -77].

Figure 24 gives an overview of the process modelling framework applicable to FSAM/AFSD with an intention to obtain parametric optimisation for maximum mechanical performance and desired microstructure. Different aspects of the process can be captured using multiple models. The thermal cycle and heating/cooling rates during the process can be achieved by a thermal model which considers the thermal properties of the tool and the material as well as the plastic flow properties of the material. Similarly, tool geometry optimisation can be achieved by a proper plastic flow model. The outputs from the thermal model such as temperature distribution and heating/cooling rates are inputs to the kinetic/thermodynamic model along with the initial microstructure to predict the final microstructure, phase evolution, as well as precipitate evolution existing during the process. Thus, the process model framework can be utilised to develop a process parameter-property-microstructure correlation map once validated by experimental runs. Such a process model involving a systematic methodology enables the process parametric optimisation of FSAM/AFSD, reducing the requirement of vast experimental runs.

Figure 24

Process modelling framework for FSAM/AFSD to achieve process parametric optimisation with minimal experimental runs. The choice of computational packages/tools are included for illustrative purposes only.

Application of machine learning towards process optimisation

Recently, the adaptation of machine learning (ML) in advanced manufacturing has become more common as the processes need optimisation of multiple parameters in synergy. ML is a way of implementing artificial intelligence (AI) which uses an algorithm for the computer to learn from a large set of experimental data thereby enabling it to predict the outcome based on processing of big data set. Ample work has been carried out in FSW and friction stir spot welding (FSSW) for parametric optimisation using various ML techniques such as artificial neural network (ANN), Regression model (RSM), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Support Vector Machine (SVM). One of the pioneering works on application of ML on FSW was carried out by Okuyucu et al. [78] where FSW parametric prediction was achieved for tensile strength, yield strength, hardness, and elongation of the aluminium weld material using ANN. Later Fratini et al. [79] coupled ANN with finite element data to predict the average grain size of the welded material of butt, lap, and T-joints. Multiple attempts were made using ANN which empowered the computer to predict the values of mechanical properties of the weld such as tensile strength, hardness, shear strength of lap joint, impact strength, fracture strength, presence of worm hole defect, and microstructure [80 -86]. Similarly, the ANFIS learning model was also successfully applied to FSW for obtaining outputs such as tensile strength, yield strength, and hardness of the weld as well as for determining the weld quality using input parameters such as tool rotational rate, weld speed, tool geometry, tool tilt angle, axial force [87 -90], etc. Further, regression models such as response surface methodology (RSM) were also used for prediction of FSW parameters using minimal experimental data [91 -94].

Successful implementation of ML techniques for FSW paves the way for similar ML implementation in FSAM and AFSD. Achieving predictive capabilities in friction stir-based AM methods using ML techniques will enable selection of the process parameters and other influential process variables beforehand in order to achieve a desired build quality and microstructure. Such smart innovation in advanced manufacturing techniques will minimise experimental cost, material cost, as well as intricacies in tool selection, material selection, and process parameter selection for a desired process outcome. AFSD being a new technique, adaptation of ML in its early research stage will facilitate rapid expansion, establishment, and its widespread industrial acceptance.

Challenges in solid-state AM processes

Despite all the advantages over fusion-based AM, friction stir-based AM processes have multiple challenges to overcome before its commercialisation. Friction stir-based AM processes are relatively new technologies which demand innovation and optimisation. Major challenges associated with these processes are:

Intricate shape fabrication: unlike fusion-based AM techniques which enable manufacturing of net-shaped complex geometries AFSD requires special fixtures for fabrication of intricate shapes.

In plane resolution: minimum feature size that can be printed using powder bed fusion is ∼0.5 mm whereas in case of additive friction stir deposition it is in the order of ∼10 mm [20]. In plane resolution can be improved by reducing the size of tooling and feed material. Currently, the MELD machines for AFSD have fixed feed rod size.

Mechanical stability of the components: fabrication of high aspect ratio components using additive friction stir deposition sometimes causes buckling. Thermal cycling during the process results in compliance gradient in the material that reduces the critical height – diameter ratio which can be printed without buckling.

Post process: post-process machining of the edges is required to compensate for the stepwise transition at the edge of each layer. The side-by-side printing in AFSD has not been explored properly yet. This would also have the issue on proper bonding near the edge.

Capital cost: to fabricate complex shapes, special clamps and custom-built fixtures are required which will add to the cost of the component.

Tool wear: performance of friction stir-based additive manufacturing process mainly depends on how effectively tool is stirring the material. Tool health and lifetime is of utmost concern. Processing of soft materials such Al and Mg will not affect the tool health much, but processing of high strength materials requires tool materials with high strength, high wear resistance, and high fatigue resistance. Currently, the tool is the limiting factor for expanding AFSD to high-temperature materials. The PCBN and W-Re tools are quite suitable for most of materials that are of interest for FSAM.

Friction stir-based additive manufacturing processes lack quantitative relationships between process controls and resulting microstructure and properties. For AFSD, these knowledge gaps in process controls relationships are largely due to a lack of process monitoring with feedback control capable of monitoring the forces applied and the resulting temperature generated in the build during deposition. A fully instrumented machine equipped with in-situ sensors, e.g. the layer-by-layer thermal images, spatial–temporal temperature information, actuator force, and spindle torque, can provide a real-time dynamic feedback that can obviously be used for process monitoring and control of the deposition. Machine health and tool health can also be monitored through the feedback data from the sensors in the machine.

Friction stir-based additive manufacturing processes are at the initial stage of its development. Improvisation of these technologies for troubleshooting above mentioned technological challenges will be immensely significant in improving the understanding of these game-changing additive manufacturing processes. Researchers should focus their attention on developing friction stir-based additive manufacturing processes to come up with the innovative approaches to eliminate the above-mentioned limitations and expand the research from coupons to component-level design and manufacturing!

Footnotes

Acknowledgements

RSM is grateful to Professor Sundeep Mukherjee for the collaborative work on FSAM of titanium alloys and steels.

Disclosure statement

No potential conflict of interest was reported by the author(s).

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