A Critical Review of Ultrasonic-Assisted Machining of Titanium Alloys

Abstract

Ultrasonic-assisted machining (UAM) has emerged as a transformative technology for increasing material removal efficiency, improving surface quality and extending tool life in precision manufacturing. This review specifically focuses on the application of it to titanium aluminide (TiAl) alloys. These alloys are widely used in aerospace and automotive sectors due to their low density, high strength and poor machinability. This review covers various aspects of UAM, including ultrasonic vibration-assisted turning (UVAT), milling (UVAM) and grinding (UVAG), with emphasis on their influence on the machinability, tool wear behavior and surface integrity. It also highlights the limitations of single-energy field UAM, such as inconsistent energy transmission and tool fatigue, leading to the increasing demand for multi-field techniques. Therefore, the advanced machining strategies, i.e., ultrasonic plasma oxidation-assisted grinding (UPOAG), protective coating-assisted cutting, and dual-field ultrasonic integration (e.g., ultrasonic-magnetic or ultrasonic-laser machining), were discussed in terms of their potential to further improve TiAl alloys processing. In addition, the importance of predictive force models in optimizing UAM processes was also highlighted, emphasizing the role of analytical and AI-driven simulations for better process control. Overall, this review underscores the ongoing evolution of UAM as a cornerstone of high-efficiency and precision manufacturing, while providing a comprehensive outlook on its current applications and future potential in machining TiAl alloys.

1. Introduction

Intermetallic alloys of titanium and aluminum have always been a subject of growing interest due to their unique combination of high-temperature strength, low density, fatigue resistance [1] and excellent corrosion resistance [2,3]. Due to such properties, they are ideal materials for aerospace [4], defense and medical industry [5,6] applications. However, their brittle nature at room temperature poses significant challenges in machining [7,8]. This is due to the highly versatile combinations of alloying elements tailored for specific applications. The emergence of multi-component alloys, i.e., Ti-Al-Nb, Ti-Al-V and Ti-Al-Si, has significantly expanded their potential [9]. The ongoing research is crucial to overcoming these barriers for broader industrial adoption.

Ultrasonic-assisted machining (UAM) has emerged as a superior alternative to conventional machining (CM) for advanced materials (i.e., γ-TiAl intermetallic alloys) [10,11]. It enhances the cutting performance due to high-frequency and small-amplitude vibrations [12]. Yang et al.’s [13] study comprehensively reviews the evolution of UAM systems, from 1D to 3D configurations and analysis kinematics based on tool/workpiece motion. Key cutting characteristics such as contact rate, cutting force and surface integrity were summarized, highlighting the advantages in reducing machining forces. Despite these benefits, challenges remain in developing high-power, large-amplitude and efficient ultrasonic systems, as well as advancing theoretical research on UAM dynamics [14]. Given its interdisciplinary nature, future advancements should focus on the processing innovations and theoretical breakthroughs to further optimize UAM capabilities for intermetallic alloys applications in aerospace, medical and defense industry, as shown in Figure 1.

The literature selection process was structured following a PRISMA-style approach. Figure 2a summarizes the identification, screening, eligibility and inclusion strategies applied to TiAl machining studies. The distribution of literature in the field of machining and post-processing of titanium alloys reveals a clear dominance of studies focused on grinding, accounting for more than 50% of the total publications as shown in Figure 2b. The data were obtained through a comprehensive literature survey conducted using major scientific databases including Scopus, Web of Science, Springer and ScienceDirect. The search covered publications from the past two decades, with a main focus on 2017–25, using keywords such as “machining of titanium alloys”, “post-processing of titanium alloys”, “grinding titanium alloys” and related terms. Relevant articles were filtered based on their focus on specific machining or post-processing techniques and the final distribution was categorized accordingly. This distribution suggested that the researchers have extensively explored the effects of ultrasonic vibration-assisted turning (UVAT), milling (UVAM) and grinding (UVAG). Figure 2c shows the distribution of these studies over the past decade and underscores the importance and preference for high-frequency vibrations.

The present research primarily focuses on technological advancements and processing methods that integrate UAM to overcome machining challenges. In this paper, Section 2 discusses the characterization and processing considerations for TiAl. Section 3 is focused on the machining efficiency of TiAl with particular emphasis on various types of UAM (i.e., UVAM, UVAT and UVAG. The focus is on major key aspects: cutting force, cutting temperature, tool wear and surface integrity, as presented in Figure 3. Section 4 explores the emerging trends in UAM, highlighting the transition from a single energy field to dual-field integrated solutions. Section 5 addresses the challenges and presents a future outlook with prospects highlighting new research directions and potential advancement to further improve its application in advanced materials. Finally, the conclusion summarizes the key findings of the research.

2. Characterization and Processing Considerations for Titanium Alloys

2.1. Elemental Composition of Titanium Alloys

The simplest form of Ti-Al alloys is the binary system, consisting of varying proportions of titanium (Ti) and aluminum (Al). These alloys are classified into two major categories, i.e., the alpha ($\alpha -$TiAl) [15] and gamma phase ($\gamma -$TiAl). At lower aluminum content (typically below 10%), the alloy remains primarily in the $\alpha$-phase, which has a hexagonal close-packed structure [16]. This phase is more ductile and has good formability but does not possess the high-temperature strength that Ti-Al alloys are known for. At higher aluminum content (typically above 40%), the alloy forms the $\gamma -$phase, which has a face-centered cubic structure. This phase is more brittle but offers excellent high-temperature strength, oxidation resistance [17] and creep resistance. The $\gamma -$phase, specifically Ti-48Al-2Nb, is a popular $\gamma -$TiAl alloy, used in high-performance applications. One key challenge in binary Ti-Al alloys is balancing the ductility and toughness of the $\alpha -$phase with the high-temperature strength and oxidation resistance of the $\gamma -$phase. The alloy tends to be brittle due to the $\gamma -$phase’s properties, requiring a solution to improve its machinability and toughness for practical applications.

The development of $\gamma -$TiAl alloys has evolved on the basis of elemental composition through three distinct generations, each improving mechanical properties and high-temperature performance [16,18,19]. The first generation primarily consists of binary compositions with limited ductility and fracture toughness, i.e., Ti-48Al-1V-(0.1 wt.%) C. To enhance the mechanical properties, second generation alloys introduced small alloying elements, i.e., niobium (Nb) [20], molybdenum (Mo) and boron (B) etc., given in Equation (1):

$$Ti-(45-48)Al-(1-3)X-(2-5)Y-(<1)Z$$

(1)

where $X=$ Cr, Mn, V; $Y=$Nb, Ta, W, Mo; $Z=$Si, B, C.

The third generation further refined the composition for application-based manufacturability, based on the formula given in Equation (2):

$$Ti-\left(42-48\right)Al-\left(0-10\right)X-\left(0-3\right)Y-\left(0-1\right)Z-(0-0.5) R_e$$

(2)

where $X=$Cr, Mn, Nb, Ta; $Y=$Mo, Hf, W, Zr; $Z=$Si, B, C; $R_e$ are rare earth elements [21]. Therefore, the generalized formula for the elemental composition of titanium–aluminum intermetallic alloys is given in Equation (3):

$$Ti-\left(42-48\right)Al-\left(0-10\right)(\mathrm{a}\mathrm{l}\mathrm{l}\mathrm{o}\mathrm{y}\mathrm{i}\mathrm{n}\mathrm{g} \mathrm{e}\mathrm{l}\mathrm{e}\mathrm{m}\mathrm{e}\mathrm{n}\mathrm{t})$$

(3)

2.2. Binary and Tertiary Titanium Alloys

The brittle nature of γ-TiAl alloys affects their machinability and component reliability. In Figure 4, the element composition and mechanical properties of a binary γ-TiAl have been presented [22,23]. The alloy consists of two major elements: titanium and aluminum [24,25]. The material is manufactured through an additive manufacturing process [26]. The elements are distributed throughout the material [27]. In order to understand the fracture morphology of the material, it was tested at 30 °C as shown. This revealed the intrinsic brittleness, which significantly affects its mechanical performance. Furthermore, the compressive strength of the material was determined at a different interlayer temperature (30–500 °C) during additive manufacturing. The vertical and horizontal direction-based compressive strength shows that the ratio decreases significantly at a high temperature of 500 °C. At room temperature, the compressive strength remains the same in both principal directions.

To further understand the behavior of different tertiary TiAl alloys, different compositions of niobium (Nb), carbon (C), tungsten (W) and silicon (Si) were added. The elemental composition analysis of the material is outlined in Figure 5. At room temperature, the $\alpha$ and γ-TiAl phases were identified at 500 nm, which underpins their mechanical behavior in high-temperature applications. [28].

2.3. Properties of Additively Manufactured γ-TiAl Alloy

As discussed earlier, the binary γ-TiAl consists of only two elements resulting in the ordered γ-phase. These alloys exhibit high strength-to-weight ratios at elevated temperatures [30,31,32]. However, they possess inherent brittle behavior (room ductility~1–4%) and limited ductility at room temperature in comparison to tertiary alloys, as presented in

Table 1. Mechanical and thermal properties of binary and tertiary TiAl alloys [37].

Performance	γ-TiAl	Ti2AlNb	${\mathit{\alpha }}_2$-Ti3Al	TC4
Density (g·cm−3)	3.7–3.9	5–5.8	4.1–4.7	4.54
Elastic modulus (GPa)	160–180	102–134	110–145	96–110
Yield strength (MPa)	400–800	1030–1292	700–1150	380–1150
Tensile strength (MPa)	450–900	1245–1413	750–1200	480–1200
Room temperature ductility (%)	1–4	3.5–10	2–10	5–20
Thermal conductivity (W·(m·K)−1)	22–24	7.87	7	6.8–7.95

. To introduce certain mechanical and thermal properties, tertiary alloying elements such as Nb, Mo, Cr and Si are added [33]. They affect the properties of the binary aluminides, making them suitable for specific applications. For instance, Nb improves fracture toughness and high-temperature strength, while Mo and Cr enhance creep resistance [33,34]. Si and B refine the microstructure, improving grain boundary strengthening and oxidation. The evolution of binary and tertiary TiAl alloys represents a significant advancement in material science, enabling broader industrial applications with improved performance, durability and manufacturability [35]. However, challenges such as cost-effective processing techniques and maintaining a balance between ductility and strength remain critical research areas for future development [36].

2.4. Challenges in Additively Manufactured $\gamma$-TiAl Alloys

Machining additively manufactured γ-TiAl alloys presents significant challenges due to their inherent brittleness, complex microstructure and high hardness variations [38,39,40,41]. Many studies have indicated that the different manufacturing methods obtained by selective elemental composition directly affect the surface friction properties [42,43,44,45]. Aspinwall et al. [46] studied the γ-TiAl alloy machining under turning and drilling, but it still poses a challenge. In Figure 6a, the surface often shows workpiece smearing, arc-shaped cracks, subsurface damage and high strain hardening. However, UAM can help reduce these issues. Furthermore, Liu et al. [47] studied the strain rates of forged Ti-46Al-5Nb-1.8Cr-0.2Ta-0.1B alloy to explore the damage evolution at elevated temperatures. For this purpose, mechanical tests at 0.001 to 0.1$s^{-1}$ strain rates were conducted. In Figure 6b, the strain rate hardening effect on its brittleness has been explained in terms of three modes of fracture. Similarly, Zhang et al. [48] also studied the damage propagation under different temperatures. At room temperature, deformation occurs mainly in γ-lamellae. In Figure 6c, the grain boundaries and phase deformation in tensile testing are presented. Due to tensile loading, the crack initiation at high temperature across grain orientation shows damage behavior. Zhang et al. [49] investigated the surface damage mechanism during nanometric cutting of γ-TiAl. The molecular dynamics simulation method was investigated to determine the influence of cutting parameters and pore defect radii on cutting forces, dislocations and stress, etc. The study is limited by its use of single-crystal models and the need for further exploration of multi-scale defects in real-world conditions as performed by Sahto et al. [50]. It was concluded that the brittle to ductile transition is influenced by the plastic deformation and crack propagation. While these findings are useful for optimizing processing parameters, further research is needed to refine the fracture mechanisms and improve surface quality during manufacturing.

3. Machining Efficiency of Titanium Alloys

The machining efficiency of titanium alloys can be evaluated from the perspective of applied techniques, underlying mechanisms and resulting output parameters [51,52,53,54,55]. Nowadays, advanced techniques, i.e., UVAT, UVAM and UVAG [56], have been widely adopted to improve its machinability [57,58,59,60]. These techniques utilize high-frequency vibrations to induce a periodic tool–workpiece separation motion, which reduces the continuous contact between them. The output techniques of UAM are reflected in key performance indicators, i.e., reduced cutting force, lower tool wear rate, improved surface integrity [61] and enhanced dimensional accuracy, having a complex relationship.

3.1. Ultrasonic Vibration-Assisted Turning (UVAT)

The UVAT technique offers distinct benefits depending on the material being machined, the desired output quality and the application requirements [62,63,64]. This technique applies high-frequency vibrations to the tool during the turning process. It has been divided into sub-categories based on key factors like vibration type, application and performance [65]. The UVAT mechanisms are normally based on the direction of vibration amplitude. It plays a decisive role in machining performance. In axial ultrasonic vibration-assisted turning (AUVAT), the amplitude is aligned axially with the cutting direction, producing an intermittent tool–workpiece separation. On the contrary, rotary ultrasonic vibration-assisted turning (RUVAT) applies amplitude radially, improving chip fragmentation and stability by altering lateral cutting dynamics. While torsional ultrasonic vibration-assisted turning (TUVAT) introduces torsional amplitude around the tool axis, increasing tool edge stresses. Therefore, conventional UVAT amplitude can be in a single or combined direction depending on proper alignment with the cutting mechanics. The mechanisms behind different UVAT configurations explain their varied performance, as presented in

Table 2. Comparative analysis of UVAT technology with respect to conventional turning.

Method	Materials	Percentage Reductions								Ref.	Year
		${\mathit{F}}_{\mathit{x}},{\mathit{F}}_{\mathit{y}},/{\mathit{F}}_{\mathit{z}}$	${\mathit{F}}_{\mathit{R}}$	${\mathit{S}}_{\mathit{a}}$	${\mathit{R}}_{\mathit{a}}$	${\mathit{T}}_{\mathit{c}}$	$\mathit{V}\mathit{B}$	${\mathit{\sigma }}_{\mathit{R}}$	$\mathit{T}\mathit{L}$
AUVAT	Ti6Al4V		↓40%							[66]	2020
UVAT	Ti6Al4V					↓16%		↑166%		[67]	2021
UVAT	Ti6Al4V				↓18.5%		↓70%			[68]	2022
UVAT	Ti6Al4V				↓57%					[69]	2020
AUVAT	Ti6Al4V		↓50%			↓15%			↑102%	[70]	2020
UVAT	Ti6Al4V								↑12%	[71]	2022
RUVAT	Ti6Al4V				↓47%		↓33%			[72]	2018
UVAT	Ti6Al4V			↓43.5%	↓49%					[73]	2014
AUVAT	Ti6Al4V				↓14.2%		↓25%	↑22.5%		[74]	2023
RUVAT	Ti6Al4V	↓51.1%/↓68.3%				↓9.4%				[75]	2021
TUVAT	Ti6Al4V	↓13%/↓21.3%								[76]	2021
UVAT	Ti6Al4V	↓30%/↓70%			↓30%					[77]	2020

Note: ↑ = Increase in value and ↓ = decrease in value.

.

The comparative analysis of different types of UVAT techniques and their benefits to the machining of TiAl alloy has been presented. AUVAT consistently achieves substantial reductions in cutting forces with reported values ranging from 40% to 50% [66,70], additional benefits in tool life improvement (↑102%) and reduced surface roughness (↓15%). Similarly, RUVAT also demonstrates strong performance, with cutting force reductions of up to 68.3% and notable improvements in tool wear (↓33%) [72,75]. This demonstrates its effectiveness in stabilizing chip formation. Lastly, torsional UVAT (TUVAT) offers moderate reductions in cutting forces (13–21.3%) [76] but stands out for enhancing surface integrity through multi-directional tool motion. Conventional UVAT, while generally effective, shows a broader range of outcomes with cutting force reductions between 16% and 70% [67,68,69,73,77]. These variations suggest that AUVAT is most suitable for tool wear suppression and productivity gains while RUVAT is most suitable for balanced improvements in force and tool wear. Overall, the vibration mode and its alignment with the tool–workpiece contact mechanics are key determinants of machining performance.

3.1.1. Influence of UVAT on Cutting Force

Cutting force is a key indicator of machining stability. During the turning operation, high cutting forces can lead to rapid tool wear, poor surface quality and increased costs [78]. To address this, researchers have explored UVAT, which enhances the machining performance. Qiu et al. [79] studied the material removal mechanism of Ti-47.5Al-2.5V-1.0Cr alloy during cryogenic machining. The methodology involved turning tests under different cooling media, focusing on the effect of liquid nitrogen cooling on chip formation and material behavior. The results show that cryogenic cooling enhances the brittleness, leading to a change in the material removal mechanism, where periodic brittle fracture occurs near the chip-free surface and ductile-brittle fracture near the cutting edge. As cutting speed increases, the alloy exhibits a sawtooth chip morphology under cryogenic conditions [80,81]. However, the main drawback of high-speed cryogenic machining is the potential for reduced tool life, limiting the feasibility of extremely high cutting speeds in TiAl alloy machining.

It is well known that UVAT technology arises from the periodic separation between the tool and workpiece due to ultrasonic vibrations. Therefore, its effectiveness is largely influenced by the machining parameters, i.e., feed rate, spindle speed and phase shift. In Figure 7, the mechanism of the UVAT system is shown [70]. In the case of conventional turning, the ultrasonic amplitude is zero. The workpiece is allowed to rotate along its axis. The tool cutting action is perpendicular to the workpiece axis. Due to no movement in this direction, the tool continuously remains in contact with the machined surface. This either results in a heat-concentrated region, tool wear or material adhesion. This creates a challenge that needs to be addressed. During UVAT, the ultrasonic vibration is given to the cutting tool in the axial direction of the workpiece. Due to this movement, a separation state results at the cutting interface. This allows the lubrication to assist in reducing the temperature of the tool contact region. This causes a reduction in cutting forces.

According to the performance characteristics of titanium alloys, researchers have used UVAT for improving the machining process. The comparison of measured forces due to conventional and UVAT studied by Li et al. [82] highlights the reduction in cutting forces across both feed rate and cutting speed. It was also observed that the increase in speed has caused the rise in cutting forces for both conventional and UVAT processes. Chen et al. [75] investigated the effect of UVAT on the machining of Ti6Al4V. Using the finite element method (FEM), a model was developed to analyze the plowing force and its influence on tool wear and surface quality. The cutting forces in the plowing area are evaluated under varying conditions. The results show that UVAT significantly reduces plowing forces compared to conventional cutting with reductions of 13.4–51.1% in $F_x$ and 5.3–68.3% in $F_y$. Increasing the vibration amplitude further reduces these forces, improving machining efficiency. Overall, UVAT minimizes cutting forces, reducing tool wear, making it a promising technique for Ti6Al4V. Airao et al. [83] analyzed the effect of UVAT of Ti6Al4V under sustainable machining conditions using a vegetable oil based cutting fluid. The comparison between conventional and UVAT under dry and oil-based conditions was conducted to evaluate the surface integrity. The findings reveal that UVAT significantly reduces cutting forces, with an average reduction of approximately 30–45%. The lowest forces were observed under vegetable oil conditions, where cutting forces were reduced by up to 50% compared to dry UVAT. In addition to this, Kandi et al. [84] also examined the impact of UVAT on cutting forces for Ti6Al4V. A horn-based tool holder was designed and FEM was conducted to assess its suitability. A comparison between conventional machining and UVAT was carried out. A significant reduction in cutting forces, achieving 40% lower at 18 m/min, 35% at 30 m/min and 25% at 40 m/min compared to the conventional method. These findings support the idea that UVAT reduces cutting forces. Pei et al.’s [85] study also explores the influence of UVAT with a major focus on improving surface integrity and reducing tool wear. A series of experiments were conducted. The findings indicate that vibration amplitude is effective for optimizing the machinability of TiAl alloys.

3.1.2. Influence of UVAT on Cutting Temperature

Cutting temperature is important in UVAT technique due to its effectiveness in reducing thermal load, improving tool life and enhancing surface quality. Zhang et al. [86] explores the effect of high-frequency vibrations on cutting temperature in the machining of Ti6Al4V using FEM. Conventional and ultrasonic vibration cutting were simulated in ABAQUS/Explicit using the arbitrary Lagrange Eulerian approach, with cutting speed (40–60 m/min), feed rate (0.08–0.16 mm/rev) and depth-of-cut (0.1–0.5 mm) varied in single-factor tests. The results show that UVAT significantly reduces cutting temperature due to intermittent contact, which allows heat dissipation. The temperature in the UVAT technique fluctuates in a pulse-wave pattern, reaching its peak when the tool fully engages the workpiece and decreasing when the tool detaches. In Figure 8, the effect of cutting parameters on contact temperature has been presented. Sui et al. [87] addressed the thermal challenge in both conventional machining and UVAT. A theoretical model was also developed for comparative analysis. The results show that UVAT reduces cutting temperature. The increase in cutting speed reduces the temperature which is nearly consistent. However, at lower depths and feed rates, the decrease in temperature is high as compared to higher depths and feed rates.

3.1.3. Influence of UVAT on Tool Wear

Studies comparing conventional machining and UVAT have demonstrated that tool wear is significantly reduced when high-frequency vibrations are applied. The UVAT process is influenced by several tool wear types, i.e., flank wear, crater wear, built-up-edge (BUE), chipping fracture and adhesion wear. In Figure 9, Airao et al. [68] observed tool wear and tool life in the machining of Ti6Al4V using conventional and UVAT under dry, wet, minimum quantity lubrication (MQL) and liquid carbon dioxide (LCO2). The results showed that LCO2 combined with UVAT significantly reduces tool wear. It assists in eliminating the BUE, minimizing flank and crater wear due to its superior cooling effects. Compared to dry conditions, the average width of flank wear reduced by 35%, 54% and 70% under wet MQL and LCO2 conditions, respectively. The reduction in crater wear was also observed across all cooling strategies. As a result, tool life was extended significantly, and the machining process became more sustainable. Yan et al. [72] also studied the combined effect of LCO2 with UVAT. The findings also highlight its superiority in improving tool longevity for TiAl alloys. Sivareddy et al. [88] also examined tool wear and tool life using an uncoated carbide cutting tool at varying cutting speeds (90–150 m/min) and ultrasonic power levels (80–100%). Tool and flank wear were analyzed using a scanning electron microscope (SEM). Tool life improvement in UVAT was highest at maximum ultrasonic power (100%) and lower cutting speeds with enhancements of 62%, 53.2% and 32% at 90, 120 and 150 m/min, respectively. Similarly, increasing ultrasonic power at a fixed cutting speed of 90 m/min extended tool life by 18%, 55% and 62% for 80%, 90% and 100% power levels. This concludes the benefits of using high-frequency vibrations.

3.1.4. Influence of UVAT on Surface Integrity

Surface integrity is a critical factor in the performance of longevity of TiAl components [89]. Yan et al. [72] conducted a study to show the impact of conventional turning and UVAT under dry and MQL conditions. Under dry machining conditions, a higher surface roughness is observed due to increased adhesion and friction at the chip–tool interface. This also resulted in severe groove and notch wear. The study concluded that UVAT and MQL combined provide the best surface finish, demonstrating their effectiveness in improving the processing of this material. A study by Silberschmidt et al. [73] discussed the effect of UVAT on surface roughness across a broad range of metals and alloys, including copper, aluminum, stainless steel and titanium alloys. However, the degree of improvement varies depending on the specific material and machining parameters. Overall, the study validates that UVAT is an effective technique for difficult-to-cut materials.

Although UVAT improves the surface quality of the machined surface, it also results in the formation of micro-structures. The micro-structures are dependent on the vibration amplitude along the longitudinal and transverse direction of the tool movement. According to Lofti et al. [77], the 3-dimensional elliptical ultrasonic vibration-assisted turning (EUAT) results in surface microstructural change, including surface roughness, micro-hardness and surface isotropy. Experimental and 3D-finite element simulations were conducted to investigate these effects under different cutting conditions. The results showed that elliptical UVAT significantly reduced grain size, leading to improved surface hardness. The technique also produced semi-spherical micro-textures that enhanced surface isotropy, providing a more uniform surface compared to conventional turning, as shown in Figure 10. Surface roughness R_a (μm) was also found to be lower than conventional processing. The method effectively controlled excessive variations in roughness by stabilizing cutting forces. Overall, the use of high-frequency vibrations in the turning process for titanium alloys improves surface uniformity while maintaining appropriate surface roughness.

3.2. Ultrasonic Vibration-Assisted Milling (UVAM)

UAM offers significant advantages over traditional machining by incorporating high-frequency vibrations into the tool’s motion. When this technology is combined with the milling process, the need for a high material removal rate (MRR) can be achieved. The integration of high-frequency in the milling process is termed ultrasonic vibration-assisted milling (UVAM) [90,91]. This process is dependent on the tool relative displacement generated with respect to the workpiece [92,93]. This is a key distinguished feature of this method, which is significantly different from conventional milling, as demonstrated in

Table 3. Tool motion trajectory in various UVAM methods.

Without Vibration	Vibration in Cutting Direction	Vibration to Normal to Surface	Vibration Normal to Cutting Direction	Compound Vibration
Tool trajectory equations
$x\left(t\right)=v_{c}t$ $z\left(t\right)=0$	$x\left(t\right)=v_{c}t+A_{x}cos (2\pi ft$) $y\left(t\right)=0$ $z\left(t\right)=0$	$x\left(t\right)=v_{c}t$ $y\left(t\right)=A_{y}cos \left(2\pi ft\right)$ $z\left(t\right)=0$	$x\left(t\right)=v_{c}t$ $y\left(t\right)=0$ $z\left(t\right)=A_{z}sin \left(2\pi ft\right)$	$x\left(t\right)=v_{c}t+A_x$ $cos (2\pi ft$) $y\left(t\right)=A_{y}cos (2\pi ft+{\varnothing }_1)$ $z\left(t\right)=A_{z}sin (2\pi ft+{\varnothing }_1)$
Trajectory plots

. Sun et al. [94] discussed the conventional tool-tip trajectory by superimposing high-frequency oscillations onto the cutting motion. It was found that this mechanism is influenced by the amplitude and frequency. Gu et al.’s [95] review also examines the intermittent separation cutting characteristics under specific machining conditions. It also discusses the effect of tool motion trajectory on surface morphology, chip formation and tool wear. The findings emphasize that further investigation into the tool’s motion trajectory can potentially address existing challenges in UAM, paving the way for more efficient and precise machining solutions.

In

Table 4. Comparative analysis of UVAM technology with respect to conventional milling.

Method	Materials	Percentage Reductions								Ref.	Year
		${\mathit{F}}_{\mathit{x}},{\mathit{F}}_{\mathit{y}},/{\mathit{F}}_{\mathit{z}}$	${\mathit{F}}_{\mathit{R}}$	${\mathit{S}}_{\mathit{a}}$	${\mathit{R}}_{\mathit{a}}$	${\mathit{T}}_{\mathit{c}}$	$\mathit{V}\mathit{B}$	${\mathit{\sigma }}_{\mathit{R}}$	$\mathit{T}\mathit{L}$
LUVAM	TC18	-	↓34.1%	↑85%	-	↓19.5%	-	↑50%	-	[101]	2022
FDUVAM	Ti6Al4V	-	-	-	↓30%	-	-	-	-	[102]	2019
LTUAM	Ti6Al4V	↓29.1% /↓34.7%	-	-	-	-	↓18%	-	-	[103]	2021
UVAM	TC18		↓16.1%		↓45.7					[104]	2022
LBUAM	TC4	↓32.3%/31%/6.6%		↓35%					↑166%	[105]	2022
LTUAM	Ti6Al4V		↓40%	↓74.6%						[106]	2018
LTUAM	Ti6Al4V	↓36%				↓25%		↑25%		[107]	2020
LUVAM	Ti6Al4V		↓55%		↓15%	↓17%				[108]	2020
LUVAM	Ti6Al4V				↓24%					[109]	2022
LTUAM	Ti6Al4V		↓14%				↓30%			[110]	2020
LUVAM	Ti6Al4V						↓67%	↓26%		[111]	2018
UVAM	Ti6Al4V		↓56.5%							[112]	2022
LUVAM	Ti6Al4V		↓12.2%		↑27.9%					[113]	2022
LUVAM	Ti6Al4V		↓18.6%		↓24%	↓15%				[114]	2023
LUVAM	TC18		↓15.6%		↓44%	↓42%		↑40%		[115]	2023
LUVAM	Ti6Al4V	↓15%			↓72%					[116]	2023
LTUAM	Ti6Al4V	↓45.1%	↓28.9%							[117]	2022
LUVAM	Ti6Al4V	↓14.6%/-/↓30.2%			↓35.1%	↓25.9%				[118]	2022

Note: ↑ = Increase in value and ↓ = decrease in value.

, the summary related to the processing of titanium alloys by the use of UVAM has been presented. The literature related to it uses longitudinal vibration (L-UVAM), feed direction (FD-UVAM) and longitudinal torsional ultrasonic vibration-assisted milling (LT-UVAM) [96]. In L-UVAM, the ultrasonic vibrations are applied in the axial direction of the tool (parallel to the spindle). This results in the tool moving up and down along its axis during milling [97]. The key advantages include improved cutting efficiency, reduced cutting forces and enhanced chip evacuation due to intermittent tool–workpiece contact [98,99,100]. In the FD-UVAM approach, the ultrasonic vibration is applied in the direction of the tool feed. The periodic acceleration and deceleration in the feed direction led to better chip segmentation and reduced adhesion at the tool–workpiece interface. Lastly, the LT-UVAM approach is a hybrid technique that combines longitudinal and torsional vibration. This results in a more complex motion where both axial and rotational oscillations contribute to the cutting action. The combined effect of these vibrations minimizes the cutting resistance.

3.2.1. Influence of UVAM on Cutting Force

The analysis of cutting force in UVAM is conducted by calculating tool trajectory, instantaneous chip thickness and tool vibration magnitude [92]. Ming et al. [119] conducted an experimental and theoretical study for Ti6Al4V processing. The study focused on analyzing the reduction in cutting forces by evaluating tool trajectory. Experimental results demonstrated that UVAM significantly reduced tangential and radial plowing force coefficients by 32.16% and 42.77%, respectively. Overall, the study demonstrates that UVAM effectively decreases cutting forces in tangential and radial directions, although axial forces require further optimization for an enhanced process stability. Similarly, Gao et al. [103] examined the relationship between tool flank wear and cutting forces in UAM of Ti6Al4V under dry conditions, comparing it with conventional milling. In Figure 11a, the measurement of cutting forces using an oblique cutting model is presented. This model uses cutting force coefficients that were calibrated through mechanical methods and time-frequency transformation to analyze the force behavior. Experimental results validated the model, showing an average error of 19.1% and 12.9% for $F_x$ and $F_y$, respectively. Compared to conventional machining, the cutting forces were reduced, with $F_x$ decreasing by 7.4% to 29.1% and $F_y$ by 34.7% to 40.1%. The presence of a high frequency signal (33.1 kHz) confirmed the impact of ultrasonic vibration, demonstrating the method’s effectiveness. In Figure 11b, the benefit of UVAM was also presented by Niu et al. [114]. In addition to this, Rinck et al.’s [120] study focused on developing an analytical force model for predicting cutting forces in UVAM, addressing the challenge in machining Ti6Al4V. The model considers both intermittent and non-intermittent cutting conditions by considering the relative contact ratio between the rake face and chip for shearing calculations. Implemented in MATLAB, the model predicts cutting forces without requiring experimental data. The predicted forces align well with experimental results, demonstrating the model’s accuracy. Future research can expand its application to different workpiece materials and tool geometries, enhancing its versatility in cutting force prediction.

Advanced force models and vibration-assisted milling techniques have significantly reduced cutting forces. However, further research is needed to refine predictive models by incorporating more complex tool geometries, varying workpiece materials and dynamic process conditions. Future studies should also explore real-time force monitoring, adaptive strategies and the integration of intelligence tools to enhance precision machining [121].

3.2.2. Influence of UVAM on Cutting Temperature

The superimposition of high-frequency vibrations alters the heat generation and dissipation mechanisms compared to conventional machining. In conventional machining, cutting heat is generated by plastic deformation in the shear zone [122,123]. This is due to the friction between the tool and chip as well as with the workpiece. The intermittent tool–workpiece contact in UVAM influences the heat distribution. As a result, UVAM is beneficial in machining temperature-sensitive materials, i.e., titanium and superalloys.

Cutting temperature at the tool tip directly affects the tool life in titanium alloy processing. In another study [108], the comparison of tool wear between conventional milling and UVAM shows that it reduces the contact temperature as well as improves tool life. According to Niu et al. [114], the effect of cutting speed on temperature evolution is shown in Figure 12. At a low speed, UVAM reduces the maximum cutting temperature. As the speed increases, this difference diminishes. Feng et al. [124] studied the temperature distribution and phase transformations based on simulation. The results indicate that the average temperature distribution is higher in extrusion rather than in shearing with respect to cutting distance.

It is found that the use of high-frequency vibration effectively reduces the cutting temperature. Rauf et al. [125] explored this effect of the reduction in cutting temperatures in UVAM of Ti6Al4V under various cooling conditions. Utilizing a Taguchi L16 orthogonal array, the research systematically examines the effects of cutting speed, feed per tooth, depth-of-cut, cooling conditions and ultrasonic amplitude on cutting temperatures. Key findings revealed that the depth-of-cut significantly influences temperature reduction, followed by feed per tooth and cutting speed. It was also observed that cryogenic cooling demonstrates superior performance in terms of heat dissipation [126,127,128]. Similarly, Li et al. [129] focused on heat treatment and machinability of the γ-TiAlNb intermetallic compound, which is considered a promising material for aircraft structural components. A 46Ti46Al8Nb alloy was subjected to vacuum heat treatment at temperatures between 950 and 1280 °C, with varying holding times (24 h, 1 h and 0.5 h) followed by furnace cooling. The results show that as-cast material consists of $\gamma$-phase with the same amount of $\alpha$-phase AlTi. Heat treatment causes the phase change but improves the machinability by reducing cutting forces in all directions. However, the study indicates that further optimization is needed to fully address the wear resistance. This indicates that hydrostatic pressure near the tool drives phase transformations, affecting cutting resistance [130]. Overall, the findings provide insight into the cutting force mechanisms at the nanoscale, aiding in the optimization of ductile machining in brittle materials.

3.2.3. Influence of UVAM on Tool Wear

Flank wear is a critical factor in machining efficiency and product quality. In conventional milling, flank wear expands the tool–workpiece contact area, leading to higher temperatures, increased forces and severe tool peeling [131,132,133,134,135]. As depicted in Figure 13a, the LT-UVAM mechanism using an AlTiN-coated carbide tool is presented by Gao et al. [103]. It was observed that high-frequency vibration reduces thermal cycling, minimizing excessive wear and tool failure. Additionally, the axial force ($F_z$) in LT-UVAM is dynamic due to ultrasonic impact and its increase with helix angle stress concentration. The study concluded that a larger helix angle accelerates tool wear, making it unsuitable for this machining approach. Wang et al. [136] also discussed tool behavior in the milling of γ-TiAl alloy (Ti-47.5Al-2.5V-1.0Cr) under different machining conditions. A full-factorial design (3-factors, 3-levels, 27 tests) was used to examine the impact of process parameters. Figure 13b shows the primary wear mechanism observed on the flank and rake wear. This study confirms that increasing tool wear significantly impacts its degradation. Moreover, Priarone et al. [137] investigated tool wear and tool life in the milling of gamma titanium aluminide (γ-TiAl) fabricated via electron beam melting and subsequent thermal treatment, a material of aeronautic interest known for its challenging machinability. The study concludes that optimizing lubrication strategies, tool geometry and coatings is essential for improving tool life and machinability when milling γ-TiAl. Lastly, Zhang et al. [138] also validated that UVAM helps in extending tool life. Figure 13c shows the initial profile of the tool, which should be coordinated with processing parameters to achieve better performance.

From the previous discussion, it is concluded that UVAM has significant potential in reducing tool wear compared to conventional milling, primarily due to its intermittent cutting nature. However, despite these advantages, a major challenge remains: the increased dynamic loading on the tool due to high-frequency vibrations, which can lead to micro-chipping and fatigue failure over extended machining durations [139,140,141]. To fully leverage UVAM’s benefit, future research should focus on optimizing tool geometries and vibration parameters to mitigate dynamic effects while maintaining efficiency for γ-TiAl.

3.2.4. Influence of UVAM on Surface Integrity

UVAM influences the microstructural evolution of γ-TiAl alloys, directly impacting surface integrity. The high-frequency vibration superimposed on the cutting motion induces unique deformation mechanisms, including localized grain refinement, work hardening and dynamic recrystallization [142], which enhance the surface properties of the machined TiAl components [143,144]. In addition to this, the oscillatory nature of UVAM imparts micro-textured patterns or periodic surface marks that may appear [129]. This results in affecting the roughness and tribological behavior of the machined surface. In Figure 14a, the surface morphology under various conditions has been presented to show the effect of high-frequency vibration [114]. In conventional milling, adhered material and plowing phenomenon were observed. However, UVAM results in adhered microparticles and ultrasonic ironing of the surface. This is due to the intermittent contact behavior. Guo et al. [145] conducted a comparative study on subsurface damage between conventional milling and UVAM, as shown in Figure 14b. The UVAM process, with a vibration amplitude of 4 μm introduces fine sinusoidal vibration textures in addition to the conventional tool feed trajectory. In conventional milling, distinct ridged textures appear due to the cutting-edge feed, with noticeable chatter marks at higher feed rates. The results suggest that UVAM alters the surface morphology, potentially impacting functional performance.

3.3. Ultrasonic Vibration-Assisted Grinding (UVAG)

UVAG machining method integrates high-frequency vibrations into conventional grinding processes to enhance the material removal efficiency and surface quality [146]. By applying ultrasonic vibrations, typically in the range of 20–40 kHz [58], the grinding force is significantly reduced, improving tool life and reducing heat generation [147]. This process is particularly effective for hard and brittle materials, such as titanium alloys and ceramics, as it minimizes subsurface damage and improves chip formation mechanisms. The UVAG method can be classified based on tool–workpiece relative motion.

The UVAG method uses a lower depth-of-cut (typically in micrometers) for precision and surface quality. Lower MRR is focused on controlled material removal and surface integrity [148]. In contrast, ultrasonic vibration-assisted high-efficiency deep grinding (UVHEDG) uses a significantly higher depth-of-cut (typically in millimeters) to achieve deep grinding in a single pass [149]. High MRR is due to deeper penetration and aggressive cutting. This method is highly productive for grinding hard materials, i.e., aerospace components and automotive parts. A summary of these methods has been outlined in

Table 5. Comparative analysis of UAVG with respect to conventional grinding.

Method	Materials	Reductions					Ref.	Year
		${\mathit{F}}_{\mathit{t}}/{\mathit{F}}_{\mathit{n}}$	${\mathit{F}}_{\mathit{R}}$	${\mathit{R}}_{\mathit{a}}$	${\mathit{T}}_{\mathit{c}}$	$\mathit{V}\mathit{B}$
UVHEDG	γ-TiAl		↓38.7%	↓19.5%	↓39.1%		[150]	2023
UVAG	γ-TiAl			↓20.1%			[37]	2024
UVHEDG	γ-TiAl				↓39.1%		[151]	2025
UVAG	γ-TiAl	↓35%/↓19%		↓10%			[152]	2017
UVAG	Ti6Al4V	↓35%/↓39%					[153]	2020
UVAG	Ti6Al4V	14.2%/13.5%		↓10%			[154]	2012
UVHEDG	γ-TiAl	16.2%/14.7%		↓46.5%	↓15.4%		[149]	2024
UVAG	γ-TiAl		↓25%	↓45.9%			[155]	2023
UVAG	TC4					↓25.2%	[156]	2022
UVAG	γ-TiAl		↓40.5%		↓38.7%		[157]	2020

Note: ↑ = Increase in value and ↓ = decrease in value.

.

3.3.1. Influence of UVAG on Cutting Force

In the UVAG method, the periodic separation between the abrasive grains and the workpiece reduces the average normal and tangential forces compared to conventional grinding. This reduction is attributed to the intermittent contact, which minimizes friction and thermal effects, which can be explained through mechanistic models. Li et al. [147] proposed a grinding force prediction model for ultrasonic grinding of γ-TiAl material. The model is based on the chip formation mechanism of abrasive sliding, grinding and high-frequency assisted machining, considering shear effects, plastic deformation and friction. The predictions were compared to the experimental results, in which showed a 23% deviation in tangential force and 21.7% deviation in the normal force, indicating a good agreement between the two. The model can also predict grinding forces for different materials by adjusting parameters, though the deviations suggest room for further refinement, especially in highly variable conditions. Similarly, Li et al. [158] also proposed grinding models for other aerospace materials.

In Figure 15, the UVAG experimental setup and material removal mechanism has been presented by Chen et al. [149]. The ultrasonic vibrations are applied in the feed direction. This allows the lubrication liquid to flow in the grinding arc. Moreover, Song et al. [159] conducted a parametric study to show the relationship between the evolution of the grinding force. The research shows the grain wear mechanism in UVAG of γ-TiAl material. The results indicate that UVAG enhances material removal efficiency by reducing adhesion and grinding forces due to periodic impact forces. However, when the unformed chip thickness exceeds 0.8 μm, grains are more likely to experience macro-fracture, reducing grinding efficiency. At grinding speeds over 80 m/s, increased thermal damage leads to material adhesion, further decreasing effectiveness. Additionally, ultrasonic amplitudes above 6 μm significantly increase impact forces, making boron nitride grains susceptible to cleavage fractures and accelerating wear.

3.3.2. Influence of UVAG on Cutting Temperature

In UVAG, temperature control is a critical factor influencing grinding performance. The application of high-frequency ultrasonic vibrations, which reduces continuous friction between abrasive grains and the workpiece under various lubrication conditions, [160,161] leads to lower average temperatures compared to conventional grinding. However, localized temperature rise can still occur due to periodic impact forces, especially at high vibration amplitudes. The reduction in thermal load enhances tool life and minimizes thermal damage. Chen et al. [149] addresses issues such as burns and tool wear during high-efficiency deep grinding with the aid of ultrasonic vibrations. The results show that high-frequency vibration reduces the grinding temperature by an average of 15.4% when compared with deep grinding. It was also determined that the wear of micro-grain is significantly improved with ultrasonic vibrations. These findings demonstrate that high-frequency vibration results in smoother surface morphology, a shallow plastic deformation layer and shear-like chip shapes due to it. Further studies are needed to fully understand the long-term effects of ultrasonic assisted vibrations on tool wear and material performance [162,163]. Yang et al. [37] investigated the machining performance of γ-TiAl intermetallic compound (Ti-45Al-2Mn-2Nb) through ultrasonic assisted grinding. Gray relational analysis was used to determine the optimal machining parameters with best condition as $F_n=3.22 N$, $F_t=1.08 N$ and $T=174 °\mathrm{C}$. Ultrasonic vibration decreased surface roughness by up to 20.12%, with a maximum profile height of 1.94 μm. A potential drawback is that the impact of material microstructure variations and long-term performance under industrial-scale conditions was not fully explored.

The grinding performance of this material machining using ultrasonic-assisted deep grinding is significant. The key performance indicators include grinding force and temperature, which have been studied by Wang et al. [150], having 38.69% and 39.05% reductions, compared to high-efficiency grinding. The ultrasonic vibrations enhance the sharpness of the abrasive grains, resulting in 23.95% reduction in specific energy. However, at high-speed grinding, the ultrasonic weakening effect slightly reduces the vibration cycles. In Figure 16, the simulation and experimental outcome of the UVAG of the γ-TiAl blade tenon has been presented. Zhao et al. [151] conducted a simulation with a 3D meshed model using Solid70 hexahedral elements, and accurately captured the temperature evolution across different grinding stages. Results showed that grinding temperature increased rapidly in the initial phase, stabilized during the steady-state grinding, and decreased as the heat source transitioned out. Experimental findings validated the simulation results, with a discrepancy of 2.3% to 13.1%. Compared to HEDG, UVHEDG exhibited 37–38.25% lower temperatures, attributed to the intermittent “contact-separation” cycle that enhanced heat dissipation by allowing better coolant penetration. The highest grinding temperature recorded in HEDG was 877.2 °C, while UVHEDG peaked at 647.1 °C. The linear increase in temperature with grinding speed and workpiece velocity was confirmed, demonstrating that ultrasonic vibration significantly reduces grinding temperature and the heat-affected zone, improving thermal control in machining processes.

3.3.3. Influence of UVAG on Tool Wear

In UVAG, the constant grain trajectory results in prolonged contact time between the abrasive grains and the workpiece, leading to the formation of wear flats. As the shearing forces exceed the grain’s bonding strength, abrasive pull-out occurs, accelerating tool wear and degrading machining performance [164]. In contrast, ultrasonic vibration-assisted high-efficiency deep grinding (UVHEDG) minimizes abrasive pull-out by reducing the grain’s continuous contact, leading to only microscopic fracturing rather than large-scale grain loss. This helps maintain the wheel’s smooth contour, extending tool life. The negative rake angle of grains results in a bamboo-like chip morphology, which mitigates excessive tool wear by controlling chip deformation. The process also promotes a more uniform stress distribution on γ-TiAl surfaces, reducing the risk of localized tool failure. Overall, UVHEDG enhances tool longevity, reduces abrasive grain loss, and improves grinding stability, making it a superior choice for machining brittle γ-TiAl alloys. In Figure 17a, Liu et al. [156] also studied the tool wear with respect to grinding depth and speed. A comparison between predicted and actual wear rate was presented. It shows that grinding depth increased the wear rate and speed decreases it.

In Figure 17b, a machine learning method to determine the wear ratio is presented [165]. For this purpose, a physical model is compared with the machine learning method in UVAG. The result shows a good agreement between the two methods with a mean error of 0.53–5.2%. This method can provide a knowledge-based rapid method to measure grit wear. In addition to this, Zhang et al. [159] investigated the surface damage mechanism during nanometric cutting of γ-TiAl. The molecular dynamics simulation method was investigated to determine the influence of cutting parameters and pore defect radii on cutting forces, dislocations and stress, etc. The results showed that larger pore defects lead to a more pronounced difference in the studied performance factors. In addition, a “shear-off” phenomenon occurs with a 15$\dot{A}$ pore defect and the increasing cutting depth raises the proportion of atoms without pore defects. The study is limited by its use of single-crystal models and the need for further exploration of multi-scale defects in real world conditions.

3.3.4. Influence of UVAG on Surface Integrity

In UVAG application, the material removal characteristics are more distinct compared to conventional grinding [166]. Due to the periodic separation between the tool and the workpiece, the grinding path is interrupted, resulting in shorter and more discontinuous scratches compared to CG, where scratches are longer and continuous [150]. In Figure 18, a similar pattern was observed by Cao et al. [153]. The ultrasonic vibrations enhance the shearing effect and reduce the dominance of plowing, leading to a less severe material deformation and a uniform surface profile. In UVAG, the interrupted cutting action modifies the grinding track with a more irregular and textured surface, while in CG, the grinding track is smoother but affected by material smearing and adhesion [37]. Overall, UVAG enhances material removal efficiency, reduces grinding forces and heat generation, and improves surface integrity, making it advantageous for brittle and hard-to-machine materials like γ-TiAl alloys.

Under conventional grinding, horizontal scratches due to feed rate were observed by Yan et al. [167]. However, the UVAG process shows a sinusoidal horizontal pattern due to its material separation effect that has been discussed earlier. The γ-TiAl has superior strength, but its brittleness creates significant machining challenges. Xia et al. [168] studied the potential of elliptical ultrasonic vibration milling to overcome these challenges and improve machining outcomes. A separation time model was developed to analyze the vibration process in the cutting mechanism. It was determined that periodic brittle fractures with local dimples indicate material plasticity, causing an 18.17% reduction in cutting force with respect to conventional machining.

3.4. Comparative Analysis of UAM Methods for Titanium Alloys

The ultrasonic-assisted machining (UAM) methods, i.e., UVAT, UVAG and UVAM offer significant advantages when working with challenging materials like additively manufactured γ-TiAl alloys [169,170,171]. Traditional methods are less efficient and more prone to tool wear. Therefore, comparative advantages of the UAM methods with conventional machining are presented in

Table 6. Comparative benefits and limitations of UAM in comparison to conventional processes.

Parameter	UVAT	UVAG	UVAM
Surface roughness (Ra, µm)	Improved over conventional	Excellent finish	Moderate to good
Material removal rate (MRR)	Moderate	Low to Moderate	Moderate
Tool wear	Significantly reduced	Reduced (abrasive tool wear controlled)	Reduced (especially in intermittent cuts)
Dimensional accuracy	High	Very high	Moderate to high
Thermal effects	Minimal (due to lower cutting forces)	Very low	Low
Energy consumption	Moderate	Low to moderate	Moderate
Geometric complexity handling	Low to Moderate	Limited	High (due to milling path flexibility)
Suitability for γ-TiAl	Very effective for finishing and precision	Excellent for final surface conditioning	Effective for shallow features and slots

. For example, UVAT utilizes high ultrasonic vibrations to reduce cutting forces during machining [71]. This results in improved surface roughness (R_a), which is significantly better than conventional turning processes [84]. The reduced cutting forces not only minimize tool wear but also enhance dimensional accuracy. As a result, UVAT is suitable for precision turning operations. However, its MRR remains moderate and it is most effective for final operations where fine finishing is required [72,172].

In contrast, UVAG stands out due to its ability to achieve an excellent surface finishing. This method is particularly beneficial for the final surface finish of hard materials like γ-TiAl, where traditional methods often lead to high temperatures, potentially causing cracks or defects on the surface [136]. The UVAG intermittent cutting action reduces grinding forces, leading to lower thermal effects and higher precision. The reduction in grinding forces leads to reduced tool wear and it is especially beneficial for abrasive tools, which tends to degrade quickly under conventional grinding. A significant challenge is the relatively low MRR, which limits its application to finer finishing rather than large-scale material removal [173,174].

UVAM combines the benefits of both turning and grinding but offers flexibility in handling complex geometries and shallow features [120]. It allows for reduced milling forces, minimizing the risk of tool deflection and improving the stability of process. This aspect is valuable in the milling of γ-TiAl, where maintaining cutting precision while managing heat and wear is crucial. The surface roughness achieved with UVAM is generally moderate to good ($R_a$ usually higher than UVAG). Due to this reason, this method is preferred for creating features like slots, pockets and other geometric shapes where conventional milling would struggle due to tool wear and heat buildup.

Overall, UAM methods provide a balanced combination of reduced thermal effects, controlled vibration and increased tool life. Each method has its strengths: UVAT excels in precision finishing, UVAG provides superior surface quality and minimal thermal effect, and UVAM offers versatility for complex geometries. However, the limitations in MRR for these methods highlight the need for further innovation, particularly in hybrid machining processes. The future of γ-TiAl lies in the development of these processes that combine UAM with other processes [129,175,176,177]. Such a hybridized process could lead to substantial improvements in both production and efficiency, making them ideal for applications where precision and durability are of paramount importance.

4. Emerging Frontiers of UAM

With the advancement of manufacturing technologies and increasing demand for precision machining, UAM has evolved beyond single-mode applications to incorporate multi-energy field strategies. These novel approaches enhance the machinability of hard-to-cut brittle materials by reducing cutting forces, minimizing tool wear and improving surface integrity. Therefore, recent research studies are focusing on predictive models of UAM behavior, ultrasonic/plasma oxidation-assisted machining (UPOAM), hybrid ultrasonic machining with protective coating (HUMPC) and hybrid laser-assisted ultrasonic machining (HLAUM). The emerging frontiers in the field of UAM are outlined in Figure 19.

4.1. Prediction Model for UAM

The integration of predictive models (cutting force, temperature or machining length) is a key frontier in UAM. These models combine analytical, empirical and computational approaches (e.g., finite element simulations and artificial intelligence) to optimize cutting conditions and tool performance. These models help in understanding the complex interactions between ultrasonic vibrations, material properties and tool dynamics [178,179]. According to Wang et al. [180], a finite element model can be validated through a mechanistic milling force model. This method requires the determination of the cutting force coefficient, which can be obtained by least squares regression. Aydin et al. [181] suggested a mechanical model that also uses related coefficients. However, these coefficients were determined through experimental data. The data were based on cutting force distribution depending on machining conditions.

UAM methods are relatively complex and difficult to control due to high-frequency vibrations and intermittent contact, when compared with conventional methods. The relative motion of tool and workpiece is different in each of these methods. Thus, there is a need for different predictive models for explaining the chip formation behavior [182]. In

Table 7. Predictive force models for milling, grinding and turning.

Process	Prediction Model	Ref.
Milling (2D-force model)	$\left[\begin{array}{c}{F}_x\\ F_y\end{array}\right]={\displaystyle \sum _{j=1}^N}g\left({\varphi }_j\left(t\right)\right)\left[\begin{array}{cc}-\mathit{cos}{\varphi }_j\left(t\right)& -\mathit{sin}{\varphi }_j\left(t\right)\\ \mathit{sin}{\varphi }_j\left(t\right)& -\mathit{cos}{\varphi }_j\left(t\right)\end{array}\right]$	[183]
	Whereas, g(ϕ_j (t)) is the window function.
Milling (2D-force model)	$F_x=F_u{\left[C_1{\displaystyle \frac{f_z}{r}}{\mathit{sin}}^3\theta +C_2{\displaystyle \frac{f_z}{r}}{\mathit{cos}}^3\theta -{\mathit{sin}}^2\theta +{\displaystyle \frac{1}{2}}p\mathit{sin}2\theta -{\displaystyle \frac{f_z}{r}}\mathit{sin}\theta -p\theta \right]}_{{\theta }_s}^{{\theta }_e}$ $F_y=F_u{\left[C_2{\displaystyle \frac{f_z}{r}}{\mathit{sin}}^3\theta -C_1{\displaystyle \frac{f_z}{r}}{\mathit{cos}}^3\theta -p{\mathit{sin}}^2\theta -{\displaystyle \frac{1}{2}}\mathit{sin}2\theta -p{\displaystyle \frac{f_z}{r}}\mathit{sin}\theta -\theta \right]}_{{\theta }_s}^{{\theta }_e}$	[184]
Milling (3D-force model)	$F_x=-\mathit{cos}\theta \int \left[{\beta }_n{D}_1\mathit{cos}\left({\beta }_n-\alpha \right)+\mathit{tan}{i}_t\mathit{tan}{\eta }_c\mathit{sin}{\beta }_n+K_{te}\right]dz$ $-\mathit{sin}\theta \int \left[{\displaystyle \frac{{\beta }_n{D}_1}{\mathit{cos}{i}_t}}\mathit{sin}\left({\beta }_n-\alpha \right)+K_{re}\right]dz$ $F_y=\mathit{sin}\theta \int \left[{\beta }_n{D}_1\mathit{cos}\left({\beta }_n-\alpha \right)+\mathit{tan}{i}_t\mathit{tan}{\eta }_c\mathit{sin}{\beta }_n+K_{te}\right]dz$ $--\mathit{cos}\theta \int \left[{\displaystyle \frac{{\beta }_n{D}_1}{\mathit{cos}{i}_t}}\mathit{sin}\left({\beta }_n-\alpha \right)+K_{re}\right]dz$ $F_z=\int \left[{\beta }_n{D}_1\mathit{cos}\left({\beta }_n-\alpha \right)+\mathit{tan}{i}_t\mathit{tan}{\eta }_c\mathit{sin}{\beta }_n+K_{ae}\right]dz$ $D_1={\displaystyle \frac{h_{\tau }}{\mathit{sin}\varphi \sqrt{{\mathit{cos}}^2\left(\varphi +{\beta }_n-\alpha \right)+{\mathit{tan}}^2{\eta }_c{\mathit{sin}}^2{\beta }_n}}}$	[185]
Milling (3D-force model)	$\left[\begin{array}{c}{F}_x\left(\theta \right)\\ F_y\left(\theta \right)\\ F_z\left(\theta \right)\end{array}\right]=\left[\begin{array}{ccc}-\mathit{cos}\theta & -\mathit{sin}\theta & 0\\ \mathit{sin}\theta & -\mathit{cos}\theta & 0\\ 0& 0& 1\end{array}\right]$	[186]
Grinding (cutting)	$F_n=A{\left({\displaystyle \frac{C^2}{K_1}}\right)}^{{\displaystyle \frac{1-m}{3}}}$	[187]
Grinding (Cutting, plowing, Rubbing)	$F_n={\displaystyle \frac{k_1{\mu }_{ch}{a}_p{v}_w}{v_s}}+k_2{F}_{t,p}+p_c\sqrt{d_e{a}_p}Q$	[188]
Grinding (Cutting, plowing, Rubbing)	$F_n=K\left({\displaystyle \frac{v_w}{v_s}}\right)a_p+K_1\left({\displaystyle \frac{v_w}{v_s}}\right)d^{-0.5}{a}_p^{0.5}+K_4{\left({\displaystyle \frac{v_w}{v_s}}\right)}^2{d}_e^b{C}_s{d}_e^{0.5}{a}_p^{0.5+c}$	[189,190,191]

, a summary of the predictive models available in the literature is presented. Most of these models are focused on determining the predictive cutting forces. The importance of such models lies in selecting optimal parameters, i.e., cutting speed, feed rate, vibration amplitude and frequency. Predictive cutting forces avoids excessive toll stress and premature failure. It also ensures minimizing cutting forces for better surface quality and reduced subsurface damage. Overall, it enables lower force requirements, reducing energy consumption and improving sustainability in manufacturing.

Current force and thermal models for UVAM/UVAG remain limited under dynamic and industrial conditions. Most assume steady state cutting, constant vibration parameters, fixed tool geometry and simplified heat partition. Therefore, the effects of transient contact, muti-degree of freedom vibration and contact variability remain unpredicted. This assumption leads to biased force and temperature predictions at production feeds/speed. Future work should integrate coupled structural dynamics and temperature-dependent material laws, and employ probabilistic learning frameworks that can be validated by high standardized benchmarks.

4.2. Hybrid Ultrasonic Machining with Protective Coating (HUMPC)

Brittle materials such as ceramics, glass and silicon wafers pose challenges due to their tendency to fracture under mechanical stress. Hybrid ultrasonic machining with protective coating (HUMPC) involves the application of thin coatings (e.g., TiAlN) that improves thermal stability, impact resistance and lubrication. Their role is to act as a barrier between the tool and the workpiece [192]. Some coatings provide self-lubricating properties, lowering friction and cutting temperatures. These coatings work synergistically with ultrasonic vibrations to minimize crack formation, improve tool life and enhance surface integrity while maintaining the structural integrity of brittle materials [193]. Moreover, the coating reduces tool–workpiece interaction by decreasing the stress concentration at the cutting edges, as depicted in Figure 20. According to Zhao et al. [194], micro-channeling during high-frequency lateral tool motion results in edge breakage and overcutting. This phenomenon was observed for a silicon workpiece with a tungsten–carbide cutting tool. Therefore, a protective layer coating was applied to the surface. It was determined that the machining parameters and the viscosity of it have an impact on the overall performance. A similar characteristic of protective layer was observed by Lan et al. [195] and Yoon et al. [196].

4.3. Ultrasonic/Plasma Oxidation-Assisted Machining (UPOAM)

Plasma oxidation has been introduced in UAM to modify the surface properties of materials, reducing their hardness and improving their machinability. This technique creates an oxide layer on the material surface, which acts as a protective barrier, reducing tool wear and cutting forces. When combined with ultrasonic vibration, plasma oxidation enhances chip control, reduces cutting temperatures and improves quality. Therefore, it is highly effective for machining superalloys and titanium-based alloys. According to Wu et al. [197], UPOAM can have significant advantages in improving machining efficiency of Ti6Al4V, as presented in Figure 21. The effect of plasma on Ti6Al4V substrate shows how it can cause a decrease in surface properties. By integrating ultrasonic vibration with plasma oxidation, it can reduce the cutting forces, primarily due to the cavitation effect, which is enhanced by plasma intensity. The authors of [198] also show the potential of UPOAG as a high-efficiency, precision machining technique for titanium alloys.

4.4. Dual-Field Integrated Ultrasonic Assisted Machining (DFI-UAM)

As manufacturing demands evolve, dual-field integrated ultrasonic assisted machining (DFI-UAM) presents a transformative approach to overcome machining challenges. By integrating multiple energy fields, such as laser, electrical discharge and magnetic field-assisted techniques, DFI-UAM ensures improved machining accuracy, particularly for aerospace alloys and other hard-to-cut materials. These frontiers pave the way for next generation precision manufacturing, making UAM a cornerstone of advanced machining strategies.

In laser ultrasonic-assisted machining (LUAM), localized laser heating is combined with high-frequency vibrations to enhance the machinability of Ti6Al4V, a challenging alloy [199]. In Figure 22a, a schematic of the process and the combined effect of laser and UAM have been presented by Dominguez-Caballero et al. [200]. In their study, the synergistic effect of using multi-field energies (UAM and laser) was considered beneficial for improving MRR and minimizing tool wear, making it beneficial for titanium alloys. Similarly, Figure 22b shows the mechanism of pulsed-ultrasonic electrical discharge machining (EDM) to enhance machining and precision of finishing operations. According to Goiogana et al. [201], the integration of ultrasonic vibrations with pulsed EDM improves MRR and enhances surface integrity. The high-frequency vibrations facilitate debris removal and promote uniform energy distribution.

Lastly, the magnetic and ultrasonic-assisted machining (M-UAM) technique is an advanced hybrid approach tailored for high-entropy alloys [204]. According to Xing et al. [203], the M-UAM method enhances material plasticity, reduces cutting forces and improves surface integrity. The magnetic field stabilizes the cutting forces by influencing dislocation movement and thermal effects, while the ultrasonic vibrations promote intermittent cutting, minimizing subsurface damage [205]. Overall, the methods mentioned represent a breakthrough in ultra-precision manufacturing, ensuring enhanced machining.

5. Challenges and Future Outlook

Despite the significant advantages of UAM in enhancing machining efficiency, several challenges hinder its widespread industrial adoption. One major challenge is the complexity of integrating ultrasonic vibration into conventional machining setups while maintaining precise control over amplitude and frequency [51]. Variations in workpiece material properties, tool geometry and machining parameters can lead to inconsistent results, limiting process reliability. Additionally, high-frequency vibrations induce stress and fatigue issues in the tool, leading to premature wear or even breakage, particularly when machining brittle or high-hardness materials.

From an industrial perspective, scalability and cost-effectiveness remain pressing concerns. The integration of ultrasonic modules into high-volume manufacturing lines requires robust and compact systems that can operate reliably under demanding production conditions. The additional cost of transducers, tool holders and control units must be justified by productivity gains. So far, a comprehensive cost–benefit analysis is still scarce. Furthermore, continuous operations barriers, i.e., fixture stability, heat management and long-term durability pose a significant challenge to industrial deployment. Addressing these challenges will require modular retrofitting solutions, energy-efficient ultrasonic generators and real-time monitoring strategies.

The increasing demand for machining complex and high-performance materials will continue to drive innovations in UAM techniques. Looking ahead, the future of UAM lies in multi-field hybrid machining, where ultrasonic vibration is integrated with other energy fields, i.e., laser, electrical discharge, plasma oxidation and magnetic. In Figure 23, a summary of current and future research prospects of UAM technology has been outlined. It is evident that the development of predictive models and Artificial Intelligence (AI)-based optimization algorithms will enhance process control. Consequently, UAM is made more adaptive and efficient for diverse applications. Additionally, advancements in high-speed imaging and acoustic emission sensors will enable better process optimization and defect detection [10,53,206,207]. Overall, as automation and digital manufacturing technologies evolve, UAM is expected to become a key enabler of next-generation precision manufacturing.

6. Conclusions

In conclusion, ultrasonic-assisted machining (UAM) has proven to be an effective approach for improving the machinability of titanium–aluminum (TiAl) alloys, which are difficult to process. Techniques such as ultrasonic-assisted turning (UVAT), milling (UVAM) and grinding (UVAG) have demonstrated significant improvements in material removal, efficiency, surface quality and tool life. However, this review highlighted the limitations of these single-energy field UAM techniques, including the inconsistencies, which have driven the need for the development of multi-field and hybrid strategies. Advanced approaches, including ultrasonic-plasma oxidation-assisted grinding and dual field integrations, present promising avenues for further enhancing TiAl processing. Overall, this review not only evaluates the characterization, machining efficiency and emerging trends in UAM for TiAl, but also outlines the challenges and future outlook. This aims to guide both future research and industrial applications in high-performance material processing.