Machinability of Sintered Metallic Materials in Additive Manufacturing

Abstract

Additive manufacturing (AM) technologies based on sintering, such as Powder Bed Fusion (PBF), Direct Energy Deposition (DED), Binder Jetting (BJT), and Material Extrusion (MEX), enable the production of complex metallic components with reduced material waste and design flexibility. However, the intrinsic porosity, microstructural anisotropy, and mechanical properties of sintered AM metals significantly influence their machinability, affecting tool wear, surface integrity, and cutting forces. This review explores the key material characteristics affecting the machining performance of sintered AM metals, focusing on conventional processes such as turning, milling, and drilling. The impact of microstructure, density, and mechanical properties on machining outcomes is analyzed, along with the challenges posed by the unique properties of sintered materials. Additionally, post-processing strategies, including heat treatments and surface finishing techniques, are discussed as potential solutions to enhance machinability. The review concludes by identifying future research opportunities, particularly in optimizing AM process parameters and developing hybrid manufacturing approaches to improve the industrial applicability of sintered AM metallic materials. Although previous studies focus on individual AM technologies, this review takes a novel approach by systematically comparing the machinability of metallic materials produced via PBF, DED, BJT, and MEX. By identifying commonalities and differences among these sintering-based AM processes, this work provides a comprehensive perspective on their machining behavior and post-processing requirements, offering valuable insights for industrial applications.

1. Introduction

Metal additive manufacturing (MAM) is no longer just an emerging technology; it is redefining the way complex metal components are designed and produced. Unlike conventional subtractive methods, MAM enables the creation of intricate geometries, optimized material distribution, and even multilateral structures that were once considered impossible. This technology has been proven to be valuable in manufacturing for producing low-volume components [1].

The ISO/ASTM 52900:2021 standard categorizes additive manufacturing (AM) into seven processes: binder jetting (BJT), directed energy deposition (DED), material extrusion (MEX), material jetting, powder bed fusion (PBF), sheet metal (SM), and VAT photopolymerization [2].

Among the various technologies, sinter-based ones can produce parts with near-net shapes and complex internal geometries, enabling part consolidation and topology optimization. This capability reduces lead times, lowers tooling cost for low to medium volumes, and permits material and microstructure tailoring through localized thermal histories [3]. Examples of sintered technologies include PBF, DED, BJ, and MEX. These are attractive to industries such as the aerospace and biomedical sectors for functional, load-bearing parts, as well as to specialized industries. Despite these advantages, metallic materials obtained by sintering have inherent limitations, such as residual porosity, microstructural anisotropy, and density variations, which directly influence their mechanical performance, surface finish, and the likelihood of meeting their requirements. Therefore, they require subsequent post-processing operations, such as surface machining, lathing, milling, drilling, and/or heat treatment, to achieve dimensional tolerances, surface finishes, or assembly suitability [4].

This review focuses on analyzing four key sintering-based technologies: powder bed fusion (PBF), direct energy deposition (DED), binder jetting (BJT), and material extrusion (ME), each with unique advantages and challenges in terms of accuracy, mechanical properties, machinability, and scalability. At the same time, four of the most used materials in these technologies, such as Stainless Steel (SS), Ni-based alloy, Ti-based alloy, and Al alloys, are analyzed. These materials were selected for their importance in automotive, medical devices, and aeronautics. The indicators analyzed are input parameters (raw material, bonding energy, printing settings), material properties (microstructural, mechanical, and thermal), post-processing (heat treatment, conventional machining), machinability in conventional machining, such as milling, turning, and drilling (tool wear, cutting forces, surface integrity, chip), and are compared. A graphical view of the analysis strategy is in Figure 1. This review seeks to identify similarities that support a processing and post-processing strategy to improve the machinability of materials and thus facilitate the industrial adoption of these technologies. This review also aims to identify existing knowledge gaps and future research directions.

2. Additive Manufacturing Technologies Based on Sintering

Sinter-based metal additive manufacturing technologies represent a subset of powder fusion processes that utilize thermal energy to bond metal particles below their melting point [5]. These technologies can produce complex geometries, porous structures, and functionally graded materials with tailored properties. Powder-sintered techniques in metal AM are classified by feedstock form, energy input, and bonding mechanism, yielding families such as powder bed fusion, directed energy deposition, and binder-mediated (indirect) methods, such as MEX, as well as sheet lamination [6]. Classification focuses on the attributes that determine how metal powders are joined during AM, commonly used criteria are the physical form of feedstock (powder, wire, sheet), the energy or activation method used to join material (laser, electron beam, thermal/chemical), and whether the process produces metal by fusion (melting), binder-mediated consolidation and sintering, or solid-state joining [1]. Four technologies will be reviewed: two powder bed technologies with joining energies such as laser and electron beam (PBF and DED), and two whose powder joining is carried out by sintering and vary in the raw material feeding method—powder bed (BJT) and powder extrusion (MEX).

2.1. Powder Bed Fusion (PBF)

PBF is an additive manufacturing (AM) technique that utilizes a high-energy laser or beam laser to selectively melt layers of metallic powders on a flat powder bed. The successive layers of powder are selectively bonded using concentrated energy sources. Of the Laser-Based Systems, Selective Laser Melting (SLM) uses laser energy to completely melt powder particles, creating fully dense parts; Selective Laser Sintering (SLS) employs lower energy levels for partial melting and sintering; and Direct Metal Laser Sintering (DMLS) is like SLM but optimized for specific alloy systems. Of the Electron Beam Systems, Electron Beam Melting (EBM) utilizes electron beam energy in vacuum environments [7]; this process enables the fabrication of complex geometries with high precision.

PBF processes a blade or wiper mechanism evenly spreads a thin layer of powder across the build plate, a high-energy source (laser or electron beam) selective melts the powder, following the cross-sectional slice of the 3D CAD model, after each layer is processed, the build platform lowers by one layer thickness, a new layer of powder is spread, and the process repeats layer by layer, the un melted powder acts as support material during the build process (Figure 2). The characteristic of the printed part depends on the process parameters and the interplay of physical phenomena that occur. The heat sources used for metals are lasers (LS) and electron beams (EB) because metals have high melting points. Laser melting operates under an atmosphere and allows convective cooling of the build surface; EBM operates under a high vacuum and therefore cannot sustain convection within the build chamber. Several heat transfer mechanisms are active at a micro and macro scale. Heat transfer occurs at the microscale because powder particles have low effective thermal conductivity due to air gaps between them. Other active physical mechanisms include melting and solidification, grain growth, fluid dynamics within the melt pool due to the Marangoni effect, powder wetting, and shrinkage during solidification, etc. [7]. The final microstructure of Powder Bed Fusion (PBF) metal part depends significantly on various parameters, including laser power (P), scanning speed (v,) hatch spacing (h), layer thickness (d), built orientation, scanning strategy, and powder characteristics, many researchers combine parameters in to an overall variable referred to as the “volumetric energy density (VED)”, “laser energy density” and sometimes “linear laser energy density”. The equations and variables for these parameters are listed below:

$$E={\displaystyle \frac{P}{\left(vxh\right)}}$$

(1)

$$\eta ={\displaystyle \frac{P}{v}}$$

(2)

$$\epsilon ={\displaystyle \frac{P}{\left(vxhxd\right)}}$$

(3)

Equation (1) refers to laser energy density (J/mm²) [8]. Equation (2) refers to linear energy density (J/mm) [9]. Equation (3) refers to volumetric energy density (J/mm³) [8,9,10]. Optimizing these factors is crucial to minimizing defects and ensuring high-quality final parts [11,12,13]. Examples of metal alloys most commonly used in the PBF are Ti, Ni, and Al alloys.

PBF emerged as the dominant method in industries such as aerospace and medical devices due to its ability to produce lightweight yet strong components [14]. Additionally, real-time monitoring of the PBF process using high-speed X-ray imaging has significantly improved understanding of thermal dynamics and solidification. This advancement is crucial for optimizing the machinability of parts produced via this method [15].

2.2. Direct Energy Deposition (DED)

DED involves feeding material directly into a focused energy source, enabling both powder-based (LMD) and wire-based (WAAM) systems [16]. The heat source comprises primarily a laser, an electron beam, or a plasma/electric arc. Electron beam and plasma/electric arc DED systems are strictly wire-based. In powder-based DED (LMD), the feedstock is mixed with a carrier gas and delivered to the focal point of the laser on the part surface. Inert gas is also utilized to generate a protective shroud around the melt pool. The microstructural evolution during the melt pool solidification in LMD is nearly independent of the feedstock microstructure [17].

The raw material is spread by a nozzle and completely melted by a laser, on the desired path to form a building layer. The nozzle follows a predefined path to construct the cross-section of the part’s geometry, and the final product is established layer by layer (Figure 3) [16]. The principal process parameters are laser power, scanning speed, feeding rate, spot size, and layer thickness. DED is highly adaptable for processing high-performance materials, including stainless steel, titanium-based alloys, aluminum alloys, ceramics, composites, and functionally graded materials.

2.3. Binder Jetting (BJT)

BJT was invented in 1993 at the Massachusetts Institute of Technology [18]. It is an AM technique that uses liquid binding agents to temporarily consolidate powder particles, followed by sintering to achieve final bonding [5]. BJT is a cost-effective additive manufacturing approach, particularly for large-scale production [19]. Furthermore, its layer-by-layer fabrication process enables rapid prototyping and production, significantly reducing lead times compared to conventional manufacturing techniques [20].

In BJT, first, metal powder is spread on a substrate, and the binder is deposited on the metal powder wherever directed by the computer-aided design (CAD) 3D model. Several post-processing processes may be required, such as debinding, curing, infiltration, sintering, and finishing (Figure 4) [21]. The main printing parameters that influence the quality and properties of parts printed in BJ are layer thickness, binder saturation, feedstock powder (powder size distribution (PSD) and powder morphology), rotation direction of the spreading rollers, and speed of the spreading layer [22]. Since parts produced via BJT typically exhibit lower initial density, additional sintering or infiltration processes are often required to enhance their mechanical properties and achieve the desired final density. This method offers significant advantages, particularly for large-scale component production. A key advantage of BJT is its versatility in material selection, as it can process metals, ceramics, and composites, making it suitable for diverse applications [19]. Additionally, this technique enables the fabrication of highly complex and customized structures that would be difficult to achieve with traditional manufacturing methods [20].

2.4. Material Extrusion (MEX)

MEX technology involves extruding metal-filled feedstock through a head nozzle to build parts layer by layer, offering effectiveness and design flexibility and requiring post-processing. Due to the coexistence of various terms in the literature referring to extrusion-based AM processes, it is herein established that the terms Fused Filament Fabrication (FFF) and Bound Metal Deposition (BDM) are used interchangeably with Material Extrusion (MEX) [23]. This method is gaining popularity due to its cost-effectiveness and simplicity compared to traditional metal AM techniques like Powder Bed Fusion (PBF) and Direct Energy Deposition (DED) [24]. In the context of material extrusion of polymeric-metal composite (MEXM), it is particularly appealing for the fabrication of metal components with intricate geometries, finding applications across various industries, including aerospace, automotive, and construction [25]. The process begins with the preparation of a feedstock, which consists of a mixture of metal powder and a polymeric binder, with the metal content typically ranging from 55% to 80% by volume [26]. This feedstock is extruded through a heated nozzle to form a “green part,” (Figure 5) which represents the initial shape of the component [27]. To obtain a fully metallic part, the green part undergoes a debinding process to remove the polymeric binder. This step can involve solvent-based, thermal, or combined methods [28]. The final stage is sintering, where the unglued part is heated to a temperature below the melting point of the metal to achieve densification and enhance mechanical properties [29]. The main print parameters are the nozzle and print bed temperatures, raster angle, printing speed, infill density, and flow rate [28].

A key advantage of metal extrusion is its lower energy consumption and simpler equipment requirements, making it a more cost-effective alternative to other metal AM techniques [24]. The process can be used with a variety of metals, including stainless steel and copper, enabling applications in sectors such as construction and medical devices [30]. Additionally, integrating renewable energy sources—such as concentrated solar energy—into the sintering stage can improve the sustainability of the process [29].

In these sintering technologies, the powder, as raw material, must meet the appropriate size, shape, and distribution to ensure flow and density for the feed types required by each technology [31]. Powder used in additive manufacturing must be as spherical as possible to achieve adequate process performance and thus better part properties [32].

As seen above, each of the technologies has printing parameters that are relevant to the quality of the final part. Below is a brief description of the most relevant printing parameters for each of the technologies and their relationship to the final properties of the part. The printing parameters of PBF (laser powder bed fusion (LPBF) and electron beam melting (EBM)), which greatly influence the final mechanical properties, include laser power. If the power is high, it increases melting penetration and density, raising ultimate strength, yield strength, and hardness. However, excessive power can produce keyholing or overheating, which degrades ductility [33,34,35]. Layer thickness: Thinner layer thickness favors a finer microstructure, high ultimate strength, and increased elongation; layer thickness may maintain strength, but often reduces elongation and increases porosity [33,36,37]. Scanning speed: A high scanning speed reduces the energy input per unit length, which increases porosity due to lack of fusion, reducing tensile and yield strengths, as well as elongation. A slower scan increases density and strength but can increase residual stress and roughness [33,35,38]. Hatching space: A larger hatching space increases the possibility of non-fusion, resulting in lower tensile strength and elongation; a conservative hatching space improves density and strength, but affects productivity [35,39]. Laser spot size: A smaller spot size can deepen the weld pool, improve mechanical properties, and promote near-isotropic behavior in some cases, but requires adjusting scan speed/power to avoid defects [34]. The scanning strategy/rotation can change the thermal gradient and anisotropy of the material [35,40].

DED: The principal process parameters are laser powder density, scan speed, and power feed rate. Laser power controls the size and dilution of the weld pool; increasing power with a fixed feed increases the width and dilution of the HAZ (heat-affected zone), which affects the microstructure and tensile properties and can enhance the bond or induce defects if not adjusted [41]. Wavelength is a parameter that determines the laser’s absorption capacity at the surface of materials. The absorption capacities of Nd/YAG and Yb fiber lasers are greater on metallic surfaces than that of the CO₂ laser due to their shorter operating wavelength (1064 nm) compared to the CO₂ laser (10.6 µm) [42]. Powder feed rate and powder line-density set the mass of metal delivered per unit length; these factors strongly influence the bead geometry, anisotropy, and mechanical response, even at an equal nominal energy density [43]. The optimum feed rate ensures a defect-free manufactured product with a high build rate [42]. Scan speed determines the microstructure features, surface roughness, build rate, and defect density; faster speeds reduce the deposition height and the melt pool dwell time [44]. Overlap ratio and path strategy (offset between adjacent passes, layer rotation) determine remelting, grain morphology, and elimination of penetrating columnar grains [45].

BJT: In BJT technology, powder particle size is directly related to density. High packing (finer classification and good flow) increases the density of the green part and allows for a higher final density after sintering, improving tensile strength, yield strength, and hardness [46]. Layer thickness, also known as layer height, also influences density and mechanical properties. Thinner layers and uniform distribution reduce defects and improve dimensional accuracy and final strength after sintering [47]. However, reducing layer thickness increases the time cost. Some research has found that layer thicknesses with three times the maximum particle diameter can optimize powder bed density and improve surface quality. Binder saturation is related to surface defects and dimensional accuracy: Inadequate saturation can result in surface defects that affect dimensional accuracy. Higher binder saturation and higher layer thickness help achieve higher green part density, which reduces sintering shrinkage and distortion and improves dimensional capability [48]. Post-processing curing and sintering depend on the binder system, component geometry and size, and powder bed capacity [22]. The sintering process determines densification, grain growth, and residual porosity. This densification is the determining factor in tensile strength, hardness, and elongation. Powder applicator speed has statistical relevance in the green state [49].

In MEX, powder loading and raw material composition parameters are directly related to density and mechanical properties; higher powder loading improves final density and tensile strength after sintering, but increases extrusion viscosity and printability [28]. Binder selection affects printability, green part strength, and debinding behavior. Problematic binders cause geometric inaccuracies and residual contaminants that reduce mechanical properties—the infill density factor, for example—affecting mechanical properties in SS 316L. Higher infill density and lower layer thickness improve tensile strength. Layer thickness also affects dimensional accuracy, which increases with decreasing thickness [50]. The raster angle, in 17-4PH, has the greatest influence on mechanical properties. Infill orientations of 0° and 90° exhibit a 20% higher Young’s modulus compared to other orientations. However, this results in a 50% to 70% lower elongation at break compared to the 0° configuration [51]. Other factors influencing tensile properties are the flow rate multiplier, layer thickness, and extrusion temperature. Increasing these three factors results in increased tensile properties [52]. The debinding and sintering schedule determines the densification and residual porosity. Inadequate cycles produce porous parts with lower ultimate tensile strength and elongation compared to wrought parts. MEX typically yields higher residual porosity. Mechanical property improvement leans heavily on optimized debinding and sintering rather than small tweaks to print speed or layer thickness alone [28]. The values of each of the printing parameters depend on the type of material to be worked with. A summary of the printing parameters for each of the technologies, with the range of values used for the most analyzed materials, can be found in

Table 1. Printing parameters of PBF, LDED, BJT, and MEX; Note: Not all jobs report this information.

Material	PBF		LDED	BJT	MEX	References
	SLM	EBM
SS316L	P = 90 to 400 W PT = 150 °C SG: Ar 550–600 L/min BO: 45° or 90° SR: 45° ot 67° HP: rectangular or hexagonal h: reducer v: moderated d: 30 to 50 µm ED = 50–125 J/mm3 SpS: smaller or higher	BC: 15 mA PT: 800 to 850 °C VP: He for 10−3 to 10−2 BO: Vertical or horizontal ScSt: 90° h: 0.1 mm v: 2800 to 4350 mm/s d: 50 to 70 µm ED: 64.28 J/mm3 BSS: smaller	P = 400 W PT = 300 °C SG = Ar + 3%Ni; 5–25 L/min BO: 0° or 90° FR: 10 g/min DP: Offset, Raster ND: 0.02 to 0.40 mm ID: 15% v: 960 to 1200 mm/min	BS: 85 to 65% d: 25–100 µm DT: 20 to 15 s RTS: 7 mm/s PT: 45 to 55 °C PS: 150 mm/s Cured 55 °C Sintered: Tem: 1380 to 1950 °C Time: 2 to 6 h Atm: Vaccum/Ar or H2	B: TPE, O, LDPE, POM, PW NT: 220 to 290 °C ND: 0.3 to 0.8 mm PT: 60 to 100 °C d: 0.1 to 0.25 mm PS: 15 to 80 mm/s Lw: ±10–20% ID 100% Raster angle 0–90° Debindig Cycloehexane Ni Temp: 70 to 500 °C Time: 90 min Heating rate: 5 °C/min Sintered H2, Ar Tem: 1380 °C Time: 180 min Heating rate: 5 °C/min	[14,32,53,54,55,56,57,58,59,60]
Ti6Al4V	P = 150–400 W PT = 220–500 °C SG: BO: 45° SR: HP: Chessboard, stripe pattern h: 50 to 100 µm v: 800 to 1200 mm/s d: 30 to 50 µm ED: SpS: 45 to 100	BC: 25 to 30 mA PT: 730 °C VP: 10−3 mbar BO: horizontal ScSt: h: 0.1 mm v: d: 50 µm ED: BSS:	P: 70 to 400 W PT: SG d: 20 to 50 µm FR DP ND ID v: 70 to 1800 mm/s	B: Organic and inorganic BS: 40 to 80% d: 30 to 90 µm DS: RTS PT: 40 to 60 °C Cured Oven at 180 °C for 4 h Heating rate 3 °C/min up to 550 °C held for 60 min Sintered: Tem: 1000 to 1360 °C Time: 60 and 40 min Heating rate: 5 °C/min Cooling rate: 10 °C/min	B: PVA, PP-PE, TPE, PO NT: 240 °C ND: 400 µm PT: 65 °C D: 150 µm PS: 10 mm/s Lw: ID: 100% Debinding Acetone, water Heating rate 1 °C/min four holds 250° for 3 h 330 °C for 3 h 440 °C for h and 550 °C for 4 h Sintered Partial vacuum of 150 millitons at 1250 °C or 1340 °C for 4 h Ar Heating rate 3 °C/min	[27,60,61,62,63,64,65]
Inconel 718, Inconel NiTi	P = 40 to 1000 W PT= SG: BO: 67° SR: HP: h: 60 to 120 µm v: 50 to 1400 mm/S d: 30 to 1000 µm LT: ED: SpS:	BC: 7.5 to 27.5 mA PT: 900 °C VP:  BO: 90° ScSt: h: v: 2000 to 8000 mm/s d: 50 µm LT: ED: SpS: 50 µm	P: 500 to 1000 W PT SG d: 250 to 1000 µm h: 500 to 220 µm FR DP ND ID v: 10.16 to 16.67 mm/s	BS: LT: DS: RTS PT: Sintered: Tem: 1270 °C Time: 10 h Atm:	B: TPE, PO, PD, LDPE, SA, PA, PW NT: 210 to 280 °C ND: 0.6 mm PT: 20 °C d: 0.1 mm PS: 10 mm/s Lw: 0.75 mm Debinding	[66,67,68,69,70]
Al Alloys	P = 300–400 W PT = 35–200 °C SG: BO: 67° SR: HP: h: 60–190 µm v: 600–1300 mm/s d: 30 to 70 µm ED: 42.18 to 80.58 j/mm3 SpS:	BC: 3.33 to 8.33 mA PT: VP:  BO: 90, 45, and 0° ScSt: h: 100 µm v: 500–1500 mm/s d: 100 µm ED: SpS: 100 µm	P: 370 W PT SG d: 30 µm FR DP ND ID v: 1300 mm/s	BS: d: DS: RTS PT: Sintered: Tem: °C Time: hr Atm:	NT: ND: PT: d: PS: Lw:	[71,72,73,74,75,76,77]

P: Laser Power; PT: Preheating Temperature; SG: Shielding Gas; BO: Build Orientation; FR: Feed Rate; DP: Deposition Pattern; ND: Nozzle Diameter; ID: Infill Density; v: Scan Speed; SR: Scan Rotation, HP: Hatching Patterns; h: Hatching Spacing; d: layer thickness; ED: Energy Deposition; SpS: Spot Size; VP: Vacuum Pressure; ScSt: Scan Strategy; BC: Beam Current BSS: Beam Spot Size; BS: Binder Saturation; DS: Drying Saturation; RTS: Roller Traverse Speed; NT: Nozzle temperature; PS: printing Speed; Lw: Layer width; DT: Drying Time; B: Binder System.

.

2.5. Advantages and Disadvantages

Each of the technologies reviewed has its advantages and disadvantages, depending on the work in which they are to be used. Powder Bed Fusion (PBF) generally offers high precision, but slower build speeds compared to DED, which provides faster deposition rates suitable for large parts. PBF is favored for applications requiring high-dimensional accuracy, fine surface finish, and complex geometries, but this demands skilled operation and extensive post-processing. DED is suitable for large parts, repairs, and coatings, offering scalability but with lower surface quality and higher residual stresses. PBF typically produces parts with superior tensile strength, density, and mechanical uniformity compared to DED, BJT, and MEX, although DED parts may exhibit better thermal stability. Defects such as porosity and residual stress are common across PFB and DED, negatively impacting mechanical performance and necessitating post-processing [17,78,79].

BJT and MEX processes are often faster and offer lower costs, but they may require additional post-processing steps such as sintering, impacting the overall efficiency. MEX parts often show higher hardness but lower density and a more heterogeneous microstructure. Binder Jetting parts generally have lower mechanical strength but can achieve acceptable properties after optimized sintering. BJT generally exhibits lower energy consumption and environmental impact compared to PBF and DED, mainly due to reduced energy use and material waste, though sintering adds to the footprint. BJT offers rapid production of complex shapes but requires sintering and densification steps, limiting immediate use. MEX is simpler and cost-effective but less precise, often requiring significant post-processing to meet industrial standards [28,80].

Techniques of metal additive manufacturing present a landscape of advantages and disadvantages shaped by their distinctive operational principles, material compatibilities, and performance outcomes.

3. Properties of Sintered AM Metallic Materials Affecting Machinability

For the analysis of the properties of sintered AM metals, three areas that are related to the life of the tool will be analyzed, the latter being one of the factors of machinability.

• Microstructural properties, which include grain size, microstructure, and porosity/relative density.
• Mechanical properties, which analyze hardness, residual stress, and strength.
• Thermal properties, which examine conductivity, thermal expansion, and melting point.

3.1. Microstructural Properties

Grain size: Smaller grain sizes can enhance dislocation movement, leading to lower cutting forces. For instance, equiaxed cutting speeds indicate reduced shear instability and dynamic cutting forces [81]. Solidification determines the initial phase distribution and grain morphology of the metal deposit. The speed, power, and size of the heat source determine the geometry of the molten pool, which in turn determines the solidification kinetics [6]. Porosity/relative density: In the construction of MAM materials, it is normal for small porosity defects to develop. Pore formation is inevitable due to the complex dynamics of the molten pool and can be of different types: gas porosity and lack of fusion porosity that may occur depending on the AM technology and printing strategy. Pore acts as a stress concentration region with the material, reducing its tensile strength and ductility. The common goal is to fabricate parts with a density of above 99.5% [82]. Pore is usually measured with a percentage of porosity and relative density analysis. Microstructure morphology: MAM parts are characterized by rapid solidification processes that create a unique microstructure compared to conventional manufacturing methods. Microstructure determines properties such as strength, ductility, hardness, and toughness. Microstructure influences thermal conductivity and expansion [83]. The final microstructure of the MAM parts is a function of parameters such as the building atmosphere, building orientation, scanning strategy, layer deposition thickness, energy density, and hatch spacing [7]. The microstructure produced by MAM has unique forms, including crystallographic, textural, and cellular structures, as well as the shape and distribution of grains and phases [82].

3.2. Mechanical Properties

The factors measured are hardness, tensile yield, ultimate strength, and elongation. Hardness is a mechanical property that influences the machinability of AM materials. The higher hardness of materials can lead to increased tool wear and higher cutting forces during machining. The high hardness can reduce the material plasticity and the level of lateral plastic flow, thereby reducing the surface roughness [84]. Tensile yield and ultimate strength of AM materials are influenced by their microstructure, porosity, and build orientation. The anisotropic nature of AM materials can lead to variations in tensile strength depending on the build orientation. Therefore, this anisotropy can also influence machinability, as cutting forces and tool wear rates may vary with the direction of machining. Generally, lower tensile strength affects chip formation.

3.3. Thermal Properties

It identifies that powder sintering technologies generally exhibit lower thermal conductivity and higher thermal expansion than other additive methods due to porosity and microstructural differences. Variations in heat capacity are material-dependent, but manufacturing technique and process parameters, such as laser power and preheating, critically influence thermal properties and densification [85]. Thermal conductivity: is the material’s ability to conduct heat; variations can affect melted pool geometry and cooling rates, directly impacting part quality and reproducibility [85]. Heat capacity quantifies the amount of heat energy required to change the temperature of a substance by a given amount. It is a measure of how much thermal energy a material can store. Thermal expansion: the dimensional change with temperature rise [86]. Thermal expansion affects dimensional accuracy and the formation of defects. Process parameters such as sintering temperature, infill density, and print speed significantly modulate thermal properties and microstructure evolution [87].

Mechanical properties are a result of the material’s chemical characteristics and the control of printing parameters in MAM. PBF typically produces near-full-density parts with a fine weld pool, dendritic or cellular structures, strong thermal gradients, textures, fine subgrain areas, and imbalanced microstructures that result in good dimensional control, high strength, and toughness [82].

DED tends to produce larger grains and more heterogeneous microstructures due to lower cooling rates and layer-to-layer reheating, which can lower ductility and alter hardness locally [88], dimensional accuracy in the final (as-built) part is lower than in PBF, making it ideal for large builds, near-net shapes, and repairs where bulk geometry is critical and final machining provides tolerances. The hardness and strength of the final (as-built) part, and its fatigue life, typically differ from those of PBF [82].

BJT in this technique a green part is obtained which requires curing and sintering, the realized parts after sintering is governed by solid state or liquid-phase sintering, equiaxed grains, possible retained phases or eutectics depending on alloy and sintered profile, good near net shapes but sintering shrinkage (anisotropic shrinkage a long build Z), lower yield and ultimate tensile strength and hardness versus PBF, tensile strength and fatigue are often limited by reduce strength. Rougher than PBF (binder droplets, powder topography, and sintered shrinking. Residual porosity on the order of 1 to 3% after sintering [55]. As [22] says, the relationship between the MBJ process and the microstructure and mechanical properties of alloys remains to be thoroughly investigated.

MEX metal printing properties depend on extrusion settings—such as flow, temperature, and nozzle geometry, as well as layer thickness, raster, fill, and shells—and post-processing settings, such as debinding and sintering. These affect density, porosity, and anisotropy [52,89]. Nozzle and extrusion temperatures affect melt viscosity, inter-bead bonding, and green part strength; lower nozzle temperature combined with higher flow improved sintered mechanicals in one 316L study [90]. Flow rate and flow multiplier control over-extrusion to close voids; these are dominant factors for tensile in 17-4PH green prints [52]. Larger nozzle diameters result in fewer inter-bead voids and higher relative density but coarser surface finish [91]. Layer thickness, thicker layers can increase deposited mass per pass (help close voids) but affect surface and dimensional accuracy [52,90]. Raster, infill orientation, orientation controls anisotropy: 0–90° can increase Young’s modulus by ~20% but reduce elongation 50–70% in one study [51]. Infill pattern and density: Higher infill density generally increases stiffness and strength, but increases print time and can change shrinkage during sintering [28]. Shells, number of walls: Thicker shells increase bending, tensile performance, and change thermal mass during printing [92]. Ironing/surface passes: Ironing and flow selection significantly influenced green density and reduced sintering shrinkage in bronze filament prints [93]. A sample of values that have been published is made for the mechanical properties of each material, with the MAM techniques reviewed here in

Table 2. Mechanical Properties. Note: Not all jobs report this information.

Material		Mechanical Characteristics
	PBF		DED	BJ	MEX	References
	SLM	EBM
SS316L	MG: has an austenite microstructure Ra: H: 197 to 270 HV Ts: 555 to 738 MPa Ys: 541 to 718 MPa %e: 20 to 47	MG: columnar grain, intergranular dendrites, discontinuous precipitates, and precipitates are rich in Cr and Mo Ra: - H: - Ts: 436 to 651.7 MPa Ys: 315.17 to 395.8 MPa %e: 9.6 to 30.6	MG: columnar dendrites that grew epitaxially from the substrate, primary austenite cells contain intercellular ferrite and martensite Ra: H: 272 to 289 HV; 295 to 428 PH13-8Mo Ts: 469 to 703 MPa 1129 to 1148 MPa PH13-8Mo Ys: 479 to 649 MPa 641 to 787 MPa PH13-8Mo %e: 17 to 33; 5.17 to 7.28 PH13-8Mo	MG: Sintering introduces a higher level of delta-ferrite phase, and leaves some ferrite residues after cooling Ra: - H; 66 HRB Ts: 437 to 640 MPa Ys: 191 to 312 MPa %e: 5.3 to 73	MG: extrusión Poros, Interlayer gap Ra: - H: 60 HRB Ts: 719 to 761 MPa Ys: 548 to 590 MPa %e: 168 to 6.62	[51,53,55,56,57,63,94,95,96,97,98,99]
Ti6Al4V	MG: bimodal (α + β), lamellar (α + β), Equiaxed (globular) primary α with β along the grain boundaries, acicular α’ Ra: 2.65 to 5.10 µm H: 364 HV Ts: 1260 MPa Ys: 925 to 1160 MPa %e: 1.7 to 9.66	MG: V-rich β phase and Al-rich α phase, β length and width, and α thickness Ra: 1.62 to 3.49 µm H: 371 to 385 HV Ts: 792 to 1269 MPa Ys: 630 to 1195 MPa %e: 2.7 to 17	MG: - Ra: - H: - Ts: 884 to 1190 MPa Ys: 892 to 1020 MPa %e: 4 to 23	MG: - Ra: - H: - Ts: 912 to 957 MPa Ys: 869 to 790 MPa %e: 6 to 9.4	MG: α + β phases, presence of intergranular β lamella (prior β). Presence of spherical, isolated pores. Ra: - H: - Ts: 875 MPa Ys; 745 MPa %e: 17%	[4,17,62,64,69,100,101,102]
Inconel	MG: orderly distribution of grains in bands, with many fine equiaxed grains surrounding the coarser grains Ra: - H: 313–302 HV Ts: 1010 to 1417 Mpa Ys: 737 to 1222 MPa %e 15.9 to 20.6	MG: γ matrix with FCC Al crystal structure with round fcc MX precipitates (Nb, Ti) (C, N), B1 type crystal structure and platelike orthorhombic δ phase precipitates, Ni3 (Nb, Ti) Ra: - H: 410 to 500 HV Ts: 929 to 1270 MPa Yp: 744 to 954 MPa %e: 5.5 to 34	MG: large number of coarse columnar grains, texture along the build Ra: - H: 195–201 HV Ts: 687 to 1436 MPa Ys: 325 to 1170 MPa %e	MG: - Ra: - H: - Ts: 612 to 718 MPa Ys: 327 to 394 MPa %e: 29 to 40	MG: - Ra: - H: 350 HV Ts: 1247 MPa Ys: %e, 6.6	[4,17,66,68,70,103,104,105]
Al alloys AlSi10Mg	MG: - Ra: 2.3 to 8.2 µm H: 106 HV to 127 HV Ts: 267 to 1387 MPa Ys: 169 to 1186 MPa %e: 1 to 17.4	MG: dendritic solidification behavior of near-eutectic AlSi10Mg alloy. Finer distribution of Si precipitates and low dendritic arm spacing Ra H: 14 to 36 HV Ts: 113 to 152 MPa Ys: - %e: 22 to 27.5	MG: eutectic type with α Al cells surrounded by a eutectic Si network Ra: 6 µm H: 58 to 102 HV Ts: 237 to 377 MPa Ys: 187 to 140 MPa %e: 5.27 to 7.9	MG: - Ra: - H: - Ts: 320 to 330 MPa Ys: 276 to 240 MPa %e: 8.2 to 9.5	MG: - Ra: - H: - Ts: - Ys: - %e: -	[4,76,106,107,108]

MG: microstructure; Ra: surface roughness; H: hardness; Ts: Tensile strength; Ys: Yield strength; %e: percentage of elongation.

.

3.4. Field Assisted Additive Technologies

In recent years, field-assisted Additive Technologies have been integrated into metal additive manufacturing techniques (PBF, DED, BJT, MEX) to enhance melt-pool dynamics, refine microstructures, and reduce defects. This technology has been actively investigated since mid-2010, with rapid acceleration in the 2020s.

The field-assisted additive manufacturing (FAAM) represents an enhancement paradigm where auxiliary energy fields—magnetic, electric, and acoustic—are integrated into conventional metal AM processes to actively modify physical phenomena during fabrication [109]. These fields do not replace the base AM technique, but rather augment it by influencing melt-pool dynamics, altering conventional partners and fluid flow via magnetic, electric, and ultrasonic forces. They also influence solidification behavior by changing nucleation rates, thermal gradients, and crystal growth kinetics. Additionally, they promote grain refinement, columnar-to-equiaxed transitions, and texture control in microstructure evolution. Finally, they reduce porosity, cracking, and residual stresses through modified thermal histories. The relationship is fundamentally complementary and synergistic: conventional metal AM provides the material deposition and layer-building capability, while field assistance provides real-time process control and property enhancement [109,110].

Magnetic field advantage is melting, stiffening, and refining. It can redistribute particles and refine crystals. The disadvantage is the high integration cost. It requires coils and magnets near the build zone. Complex field control is typical. The effects promote melt convection and alter solidification morphology. It reduces some defects. The best applications are large-scale DED and arc-based AM. It is used in applications that need electromagnetic stirring for homogeneity [109].

Electric (Electro pulsing) advantages include microstructure tailoring and accelerated diffusion and dislocation dynamics. Disadvantages include process control complexity, potential for unwanted localized heating, and uncertain scalability [109]. Typical effects include altering phase transformation, relieving residual stress, and promoting desired precipitates. The best applications are targeted phase and microstructure control, residual stress management, and experimental multifield coupling [111].

Acoustic (Ultrasonic) advantages include grain refinement and promotion of the columnar-to-equiaxed transition. It increases nucleation density. The disadvantage is that it changes melt-pool dynamics, which can increase spatter. It complicates in situ sensing. Typical effects are increased grain number density and modification of thermal gradients. It reduces porosity when tuned. The best applications are fine-grained structural parts, fatigue-critical components, and applications seeking isotropic microstructures [112,113].

Field-assisted additive technologies have been used with PBF technology. For example, acoustic coupling has been used in 316L stainless steel additive manufacturing (AM) and ultrasound-induced columnar-to-equiaxed transitions, producing finer and more isotropic microstructure with improved mechanical properties [113]. Direct Energy Deposition is particularly compatible with field assistance because the melt bath is openly accessible for external actuators. Ultrasonic-Assisted DED (UADED) ultrasonic transducers mounted on the substrate or integrated into the deposition head promote grain refinement, reduce porosity, and minimize hot cracking in deposited beads [114].

While field assistance offers significant advantages in gran refinement, defect reduction, and property enhancement, it also introduces equipment complexity, monitoring challenges, and increased capital costs.

4. Machinability of Sintered AM Metallic Materials

Machinability was defined as the characteristic of materials that relates the influence of hardness, strength, ductility, grain size, microstructure, and their chemical composition, with tool wear, chip formation, ease of cutting, and surface finish [115]. Machinability differs significantly between traditional metalworking and metal additive manufacturing (AM). AM can be more challenging due to anisotropic properties, higher surface roughness, and unique defects that require extensive post-processing [14]. Post-processing processes, such as mechanical machining, must be followed to ensure that the surface quality and the geometric precision of the MAM components are within acceptable ranges [116].

In machinability investigations of MAM parts, indicators such as cutting forces, tool wear, surface roughness, and chip formation are used to measure machinability and compare it with reference parts that have been obtained from conventional processes such as forging or casting [82]. Tool wear is one of the most widely used criteria for evaluating machinability. Tool wear is defined as a continuous loss of material on the tool, leading to a change in micro- and macro-shape. Tool wear results from mechanisms such as abrasion, adhesion, diffusion, and tribo-chemical reactions (surface fatigue). The most common forms of wear due to the mechanisms are flank wear, notch wear, crater wear, oxidation, crack formation, plastic deformation, and layer/edge buildup [115], BUE (built-up edge) typically occurs when there is significant material work-hardening, giving that the workpiece material at the tool–workpiece interface is highly deformed and, thus, much harder than the base workpiece material [117]. Cutting forces and temperature are also widely used as the criteria for the evaluation of the machinability. The cutting force depends on the hardness and strength properties of the material. Change in cutting force is the factor influencing the temperature, surface integrity, and the development of tool wear [116]. In addition to these parameters, machinability can be quantified by parameters such as cutting force, specific cutting energy, or specific cutting pressure.

In this section, the machinability indicators, such as specific cutting energy force, energy, and pressures, for conventional machining processes, such as lathe, milling, and drilling, which are used in MAM parts, will be analyzed. Specific cutting force can be calculated as the ratio of principal cutting force Fc and the real chip cross-section A_D [118].

$$K_c={\displaystyle \raisebox{1ex}{$F_c$}\!\left/ \!\raisebox{-1ex}{$A_D$}\right.}$$

(4)

A_D = l_eff × h_eq

(5)

where l_eff = equivalent length, h_eq = equivalent thickness that calculates the following:

$$h_{eq}= {\displaystyle \raisebox{1ex}{$a_{p}xf$}\!\left/ \!\raisebox{-1ex}{$l_{eff}$}\right.}$$

(6)

where a_p = depth of cut and f = feed rate [118]. Each of the conventional machine processes is reviewed separately, and the cutting parameters used for the different materials and MAM printing processes are reviewed.

4.1. Turning Processes

Turning is a single-point cutting process where the cutting tool remains stationary and the workpiece rotates. It is commonly used for machining cylindrical components. Measuring machinability in turning with its specific cutting force or energy depends on cutting parameters, type, geometry, and material of the tool. As an example,

Table 3. Machining parameters of Turning.

	EBM Ti6Al4V	EBM Ti-6Al-4V ELI	DML Ti64
Machining	FEL-660HG lathe	Turning center with 22 kW spindle power maximum rotation of 4000 rpm,	EMCO (Hallein, Austria) CT60 CNC Lathe
Tool	Sandvik CNMG 12 04 08-SM H13A	SECO Tools carbide insert CNMG120408-MF4 TS2000 TiAlN/Tin coating, tool holder: PCLNL2020K2 6° rake angle, 95° cutting edge angle 0.8 mm of corner radius and a chip breaker on both sides	DCGT070201LF coating grade of KCU10: multilayer PVD coating noise radius 0.1 mm 95° major cutting edge angle 30° relief angle 10° rake angle
Enviromental	Dry and lubricant oil Siroil Emulg	Dry
Cutting speed	-	60 m/min	90 and 120 m/min
Spindel speed	300 rev/min	-	-
Feed rate	0.28 mm/tol	0.1 and 0.2 mm/rev	0.05 mm/rev
Depth per cut	0.8 mm	0.15 mm	0.25 mm
MRR	10.5 mm3/s	-	-
Reference	[119]	[120]	[121]

shows examples of materials manufactured by Electron Beam Melting (EBM) and Direct Metal Laser (DML) with their respective parameters.

These articles show results based on the specific cutting energy or force, one article the specific cutting energy was calculated in two types of dry and wet machining environments, the results of the study demonstrate that dry turning is more energy efficient than wet turning by selecting the same machining process parameters while obtaining a comparable surface roughness, the value of specific cutting energy was 0.7 J/mm³ to dry turning and 1.1 J/mm³ to wet turning, the roughness parameter R_a was measured in parallel and perpendicular to the building, in parallel R_a= 35.81 µm and in perpendicular to the building R_a= 28.79 µm [119], the other study aimed to manufacture a functional cone of the modular hip prothesis component by turning and evaluate whether an EBM produced component could offer improved machinability compared to forged titanium while ensuring functionality, as a results were obtained the specific cutting force of titanium EBM was determined to be 1775 n/mm² that is approximately 20% lower than the value determined for the wrought titanium alloy. It can be inferred that EBM-produced titanium parts exhibit better machinability than wrought Ti6Al4V. Higher roughness values were also obtained: Ra = 0.4 µm at f = 0.1 mm/rev. The chip control conditions were met for EBM test samples at a feed rate of 0.2 mm/s, enabling the production of helical-shaped chips [120].

The study conducted using the DML technique aimed to compare the machinability of metal additive manufacturing (MAM)-manufactured and traditionally forged Ti64 using a holistic approach. Four specimens were tested: two MAM materials (one heat-treated and one as-built), and two wrought materials (one heat-treated and one as-built). The main machining outcomes included tool life, surface finish, and dimensional accuracy. The results show that MAM is not particularly difficult to machine in terms of force and temperature. However, it creates high-frequency cutting vibrations across a wide range (up to 5 kHz). High vibrations do not affect surface finish or dimensional accuracy, but they do tend to worsen tool life by chipping off the cutting edge. The vibrations can be attributed to the brittle martensitic microstructure presented in additive-manufactured Ti64, also evidenced by the more serrated chips. The specific cutting force shows that the heat-treated MAM part has the lowest value. Chip analysis shows serrated chips in all samples. The chip from the MAM sample appears to exhibit more shear band formation and the smallest spacing. Tool wear analysis shows that MAM cutting can produce sudden changes in the tool condition, such as chipping or notching. The tool used on the MAM exhibits rake wear, abrasive wear, buildup, and missing pieces at the cutting tip [121].

4.2. Milling

Millig is a rotate multi point cutting application to remove material for a workpiece that can move in x, y and z axis, typically used for suited flats, slots and complex contours and rectangular components, the machinability results are discussed below mainly based on the pressure, energy or specific cutting force in the machining process, applied to MAM, a resume of machining parameters for milling machining in

Table 4. Machining parameters of Milling.

	LPBF Inconel	EBM Ti6Al4V	LBPF 18Ni300
Machining	Mill Haas VF0 Three-axis vertical machining center.	High-precision five-axis CNC machining center (KERN Pyramid Nano)	Mill
Tool	Kennametal Model No. HPFT250S6075 TiAlN-coated carbide end mill Six-flute Diameter of 6.35 mm (0.25 in.) Helix angle of 45°.	Three-flute micro-end milling tool WN 3142 R-N PVD coating TiAlN 1.8 mm diameter	XPET 060204 PDER-LP carbide insert solution AlTiN coated through Physical Vapor Deposition (PVD) 4 slot 0.4 tool radius and a positive rake angle
Enviromental	Dry	Wet Oil as a coolant and lubricant	Dry
Cutting speed	24.4 m/min	Variable 35, 60, 80 m/min	80, 200, 300 m/min
Spindel speed	-	-	-
Feed rate	0.0254 mm/th	Variable 1.5, 2.5, 5, 10, 15, 20, 25, 50 µm/th	0.05, 0.1, 0.2 mm/tooth
Depth per cut	1.016 mm	1 mm	0.2, 0.4, 0.6 mm
Radial immersion	50%	-	-
Width of cut	-	0.3 mm	-
Strategy	-	Down milling	-
Observations	-	Samples were polished and etched prior to micro-milling.	-
Reference	[122]	[123]	[124]

.

In PBF Inconel 718, the objective was to investigate the behavior of Inconel 718 in milling machining, manufacturing variable-height block supports, and peripherally end-milling to study deformation and fracture behavior, specific cutting energy, the influence of tooth-support wall interactions on milling forces, and tool wear. The investigation shows that supports do not uproot from the base or generally collapse when milled. They maintain their structure and support localized chip formation, despite being designed to be removed from the base using hand tools. The specific cutting energy of milling blocks supports is 12% of that of full-density metal when considered on a swept volume basis. A tool wear study showed that a Ti AlN-coated carbide end mill is more prone to premature failure when machining block supports than fully dense metal. This failure is due to fractures at the corner radius and is possible due to tooth-support wall interactions [122].

For the Electron Beam Melting (EBM) of Ti6Al4V, the study addresses the machinability of additive manufacturing (AM) and extruded Ti6Al4V titanium alloy parts in the micro-milling process with a specific focus on cutting forces, specific cutting energy, burr formation, and surface quality. The comparison results show no significant difference in cutting forces for both materials with chip thicknesses between 7.4 and 37.3 µm, despite the higher hardness of EBM Ti6Al4V compared to extruded Ti6Al4V. However, micro-milling of the EBM parts produced a finer surface. The cutting forces and specific cutting energies of EBM parts were lower than those of extruded parts at minimal chip thickness (lower than 7.4 mm). Continuous wavy-type burs were formed in micro-milling of the EBM Ti6Al4V and were larger than those of extruded Ti6Al4V [123]. LPBF 18Ni300: the research focused on the machinability of 18Ni300 maraging steel obtained by laser powder bed fusion and its comparison with the conventional counterpart. The test was carried out covering a wide range of parameters, aiming at understanding their influence and comparing the results obtained in terms of cutting force, specific cutting pressure, roughness, and chip morphology. The results show that despite the higher mechanical strength of the AM metallurgical condition, no significant differences were noticed in milling operation energy-wise when compared with the CM counterpart. The higher mechanical strength of additively manufactured maraging steel (on average 15%) does not contribute to an accountable decrease in its machinability, despite the slight tendencies for higher cutting forces and specific cutting pressures (amounting to approximately 5%). With regard to cutting tools, more pronounced wear tendencies were observed on inserts used at higher cutting speeds, arising from the relatively higher pressures and temperatures in the tool-chip interface [124].

4.3. Drilling

Drilling is employed for creating holes by axial penetration of a cutting tool into the workpiece. The concept of specific cutting energy in drilling can be calculated with power [125]:

$$P={\displaystyle \raisebox{1ex}{$2\pi TN$}\!\left/ \!\raisebox{-1ex}{$60$}\right.}$$

(7)

where T is torque (N-m), N spindle speed (RPM), and MRR (mm³/min) material removal rate.

$$MRR={\displaystyle \raisebox{1ex}{$\pi D^{2}f$}\!\left/ \!\raisebox{-1ex}{$4$}\right.}$$

(8)

where D is drill diameter (mm) and f feed rate (mm/min) [125]. A resume of machining parameters for drilling machining is in

Table 5. Machining parameters of Drilling.

	EBM Ti6Al4V	DMLS Ti6Al4V
Machining	CNC high-speed machining center (Model K-mill 8).	CNC vertical machining center (HURCO VMX42)
Tool	drill bits	Cemented carbide drill made of tungsten carbide (WC-Co) with a single layer of TiAlN coating
Feed rate	Varing 40 to 200 mm/min	0.06, 0.09, 0.12, 0.15
Spindel speed	Varing 3000, 3500, 4000 4500 and 5000 rpm	500, 800, 1200, 1500
Environmental machining	Dry	Dry
Drill depth		12 mm
Reference	[125]	[126]

.

In the case of drilling for MAM, no information was found in articles that take into account energy, pressure, or cutting force as machinability parameters. EBM Ti6Al 4V, the article investigates the influence of processing variables on the dry drilling performance of EBM-produced Ti6Al4V. Machinability is investigated by analyzing cutting force, chip morphology, tool wear, shape error, hole size, and burr formation. The results show that the cutting force increases with increasing spindle speed from 3000 to 3500 rpm, decreases between 3500 and 4500 rpm, and increases subsequently. Smooth and uniform spiral chips were observed only at low spindle speed (3000 rpm), and short distorted chips were formed at high spindle speed (4500–5000 rpm), indicating favorable and unfavorable machining conditions, respectively [125]. The article addresses the effect of the microstructure of DMLS Ti6Al4V on machining stability and tool wear behavior. Three conditions were tested: as-built DMLS, HTDMLS with heat treatment, and wrought. The results highlight a correlation between tool wear behavior and material microstructure. A great number of micro-pits appeared on the tool flank face, along with abrasive marks, coating delamination, and catastrophic failure of the cutting edge. In general, Ti6Al4V-DMLS, HTDMLS, and wrought materials exhibit low machinability, resulting in premature tool wear during dry machining [126].

5. Post-Processing Strategies for Improving Machinability, Treat Thermic

As analyzed, metal additive manufacturing parts often exhibit surface imperfections, residual stresses, and heterogeneous microstructures, which negatively affect their mechanical performance and functional reliability. Post-processing techniques such as heat treatment and surface finishing are used to improve mechanical properties and machinability. Surface finishing methods such as mechanical polishing, laser polishing, chemical and electrical polishing, and abrasive flow machining are effective in reducing surface roughness and improving the fatigue life of MAM parts. These techniques address surface defects such as porosity, balling, and staircase effects that impair machinability and performance [127]. Heat treatments, including hot isostatic pressing (HIP), annealing, quenching and tempering, and normalization, are crucial for modifying the microstructure, reducing residual stresses, and enhancing mechanical properties such as tensile strength and fatigue resistance in MAM. These treatments complement surface finishing by improving subsurface integrity and homogenizing microstructures [82,128].

In Powder Bed Fusion (PBF), a combination of stress-relief/solution treatment, hot isostatic pressing (HIP), and many surface finishing routes is used to improve toughness, density, and fatigue performance. Heat treatment includes stress-relief annealing and hot isostatic pressing (HIP) to reduce tensile residual stress, homogenize the microstructure, and close internal porosity in PBF [129]. The typical heat treatment applied in Direct Energy Deposition (DED) is stress relief, resulting in large cutting force reductions (Ti6Al4V) and an increase in compressive surface stress after heat treatment. Mechanisms include microstructure, homogenization, stress relaxation, and grain coarsening [130]. BJT requires thermal curing and sintering (and often infiltration on HIP) to achieve metallic density. Surface finishing follows densification and can include abrasive and chemical polishing to improve external surface quality. Post-sinter HIP or liquid–metal infiltrations are used when higher density and mechanical performance are needed. These steps can significantly reduce porosity but add process complexity and cost. Surface finishing after sintering, tumbling, abrasive flow machining, chemical polishing, and selective machining is used to lower surface roughness. However, the remaining internal porosity can limit the achievable fatigue/toughness compared with fully melted routes [47].

Table 6. Heat treatment PBF, DMLS.

Material/Technique	Heat Treatment/Surface Finish	Results	References
L-PBF AlSi10Mg	Direct Aging (DA) 150 °C and 170 °C for different times	195 HV for DA 6 h Fine cell microstructure—precipitation of Si nanoparticles Improve mechanical properties DA 170 °C for 6 h increases tensile strength to 430 MPa compared to the as-built condition	[74]
L-PBF Ti5553	BASCA (Beta annealed, solution treated, and aged) STA (solution treated and aged)	BASCA: increase fatigue strength and toughness α-phase precipitates in the form of plates within the β-phase matrix STA: enhance strength α-globular/plates and β matrix Tool life decreases due to increased mechanical properties such as hardness and toughness.	[131]
DMLS AlSi10Mg	T6	Reduce the surface roughness, refine the microstructure, increase micro hardness (78.7 HV), and increase ductility. Cutting force 16.9–67.1% reduction relative to untreated AM parts	[132]

shows examples of heat treatments applied to two types of materials obtained from LPBF and DMLS techniques.

6. Summary and Future Perspectives and Research Opportunities

This article presents an analysis of four sintered metal additive manufacturing technologies (PBF, DED, BJT, and MEX), analyzing the mechanical properties that affect machining in conventional methods such as turning, milling, and drilling. The analysis covers the microstructure, density, and mechanical properties. Additionally, the main heat treatment post-processing processes applied to parts made with these technologies were reviewed.

The analysis reviewed the properties of the most studied materials: Ti6Al4V, SS316L, Inconel, and AlSi10Mg. It examined the printing parameters and mechanical properties of each technology. However, comparing technologies is difficult because not all technologies have been used with the same materials. The reporting of parameters and properties lacks standardization. This opens the opportunity to expand the use of materials in different technologies and to standardize the parameters and mechanical properties to be reported. Regarding machinability, it was found that the most studied material is Ti6Al4V, which is produced using technologies such as EBM, DMLS, and LPBF. This opens an opportunity to generate research into the machinability of other materials and more sintering technologies, such as BJT and MEX.

Little information was found on drilling, and the technologies used to make the machined parts were EBM, DMLS, and LPBF. Information was also found on micromachining and hybrid additive manufacturing; these last two processes are being investigated, but only with certain AM technologies. It is convenient to continue adding technologies and different materials. No studies were found to compare the same heat treatment for a material using different technologies. This opens a research opportunity for thermal post-processing studies for AM metals, reviewing thermal cycles, temperatures, times, and phase control.

The information generated on printing parameters, mechanical properties, and MAM machinability seeks to establish a complete understanding of material behavior. This understanding is based on the type of powder, the measurements of properties, and the establishment of machining parameters according to properties to ensure the machinability of the part. This leaves room for research into interrelated parameters that allow for the prediction of part behavior during machining. The influence of meal additive manufacturing properties on cutting force during machining. Variations in microstructure, porosity, and residual stresses inherent to metal AM significantly affect cutting force magnitudes and stability. Understanding this effect is crucial for optimizing parameters and improving component performance.

Data scarcity and limited generalization hinder scalability and industrial adoption of Machine-Learning (ML)-based control systems [133,134,135]. Developing large-scale, diverse datasets and standardized protocols, as well as research on transfer learning and domain adaptation, is necessary to improve model robustness across varied AM scenarios. Real-time decision making is critical for defect mitigation and process optimization, but remains challenging due to data latency and computational demands [136,137,138]. Designing and validating real-time, low-latency digital twin architectures, integrated with control algorithms, should focus on edge computing and distributed architectures for scalability.

Autonomous AM promises efficiency gains but requires overcoming technical and integration challenges [139,140], developing integrated hierarchical AI frameworks combining knowledge, generative, operational, and cognitive layers, and validating lifelong learning and self-optimization capabilities in industrial AM settings. Robust models are necessary for broad industrial applicability and process reliability [141,142]. Investigating physics-informed Machine-Learning (ML) models and hybrid digital twins is necessary to improve adaptability, as well as conduct extensive validation across multiple AM materials and part designs.