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The purpose of this study is, to compare laser-based additive manufacturing and subtractive methods. Laser-based manufacturing is a widely used, noncontact, advanced manufacturing technique, which can be applied to a very wide range of materials, with particular emphasis on metals. In this paper, the governing principles of both laser-based subtractive of metals (LB-SM) and laser-based powder bed fusion (LB-PBF) of metallic materials are discussed and evaluated in terms of performance and capabilities. Using the principles of both laser-based methods, some new potential hybrid additive manufacturing options are discussed.

Production characteristics, such as surface quality, dimensional accuracy, material range, mechanical properties and applications, are reviewed and discussed. The process parameters for both LB-PBF and LB-SM were identified, and different factors that caused defects in both processes are explored. Advantages, disadvantages and limitations are explained and analyzed to shed light on the process selection for both additive and subtractive processes.

The performance of subtractive and additive processes is highly related to the material properties, such as diffusivity, reflectivity, thermal conductivity as well as laser parameters. LB-PBF has more influential factors affecting the quality of produced parts and is a more complex process. Both LB-SM and LB-PBF are flexible manufacturing methods that can be applied to a wide range of materials; however, they both suffer from low energy efficiency and production rate. These may be useful when producing highly innovative parts detailed, hollow products, such as medical implants.

This paper reviews the literature for both LB-PBF and LB-SM; nevertheless, the main contributions of this paper are twofold. To the best of the authors’ knowledge, this paper is one of the first to discuss the effect of the production process (both additive and subtractive) on the quality of the produced components. Also, some options for the hybrid capability of both LB-PBF and LB-SM are suggested to produce complex components with the desired macro- and microscale features.

This study aims to enhance merging of additive manufacturing (AM) techniques with powder injection molding (PIM). In this way, the prototypes could be 3D-printed and mass production implemented using PIM. Thus, the surface properties and mechanical performance of parts produced using powder/polymer binder feedstocks [material extrusion (MEX) and PIM] were investigated and compared with powder manufacturing based on direct metal laser sintering (DMLS).

PIM parts were manufactured from 17-4PH stainless steel PIM-quality powder and powder intended for powder bed fusion compounded with a recently developed environmentally benign binder. Rheological data obtained at the relevant temperatures were used to set up the process parameters of injection molding. The tensile and yield strengths as well as the strain at break were determined for PIM sintered parts and compared to those produced using MEX and DMLS. Surface properties were evaluated through a 3D scanner and analyzed with advanced statistical tools.

Advanced statistical analyses of the surface properties showed the proximity between the surfaces created via PIM and MEX. The tensile and yield strengths, as well as the strain at break, suggested that DMLS provides sintered samples with the highest strength and ductility; however, PIM parts made from environmentally benign feedstock may successfully compete with this manufacturing route.

This study addresses the issues connected to the merging of two environmentally efficient processing routes. The literature survey included has shown that there is so far no study comparing AM and PIM techniques systematically on the fixed part shape and dimensions using advanced statistical tools to derive the proximity of the investigated processing routes.

This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations.

This study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques.

A comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions.

Based on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain.

Current methods for the preparation of composite powder feedstock for selective laser melting (SLM) rely on costly nanoparticles or yield inconsistent powder morphology. This study aims to develop a cost-effective Ti6Al4V-carbon feedstock, which preserves the parent Ti6Al4V particle’s flowability, and produces in situ TiC-reinforced Ti6Al4V composites with superior traits.

Ti6Al4V particles were directly mixed with graphite flakes in a planetary ball mill. This composite powder feedstock was used to manufacture in situ TiC-Ti6Al4V composites using various energy densities. Relative porosity, microstructure and hardness of the composites were evaluated for different SLM processing parameters.

Homogeneously carbon-coated Ti6Al4V particles were produced by direct mixing. After SLM processing, in situ grown 100–500 nm size TiC nanoparticles were distributed within the α-martensite Ti6Al4V matrix. The formation of TiC particles refines the Ti6Al4V β grain size. Relative density varied between 96.4% and 99.5% depending on the processing parameters. Hatch distance, exposure time and point distance were all effective on relative porosity change, whereas only exposure time and point distance were effective on hardness change.

This work introduces a novel, cost-effective powder feedstock preparation method for SLM manufacture of Ti6Al4V-TiC composites. The in situ SLM composites achieved in this study have high relative density values, well-dispersed TiC nanoparticles and increased hardness. In addition, the feedstock preparation method can be readily adapted for various matrix and reinforcement materials in future studies.

Ti6Al4V alloy patient-customized implants (PCI) are often fabricated using laser powder bed fusion (LPBF) and annealed to enhance the microstructural, physical and mechanical properties. This study aims to demonstrate the effects of annealing on the physio-mechanical properties to select optimal process parameters.

Test samples were fabricated using the Taguchi L9 approach by varying parameters such as laser power (LP), laser velocity (LV) and hatch distance (HD) to three levels. Physical and mechanical test results were used to optimize the parameters for fabricating as-built and annealed implants separately using Grey relational analysis. An optimized parameter set was used for fabricating biological test samples, followed by animal testing to validate the qualified parameters.

Two optimized sets of process parameters (LP = 100 W, LV = 500 mm/s and HD = 0.08 mm; and LP = 300 W, LV = 1,350 mm/s and HD = 0.08 mm) are suggested suitable for implant fabrication regardless of the inclusion of annealing in the manufacturing process. The absence of any necrosis or reaction on the local tissues after nine weeks validated the suitability of the parameter set for implants.

To help PCI manufacturers in parameter selection and to exclude annealing from the manufacturing process for faster implant delivery.

To the best of the authors’ knowledge, this is probably a first attempt that suggests LPBF parameters that are independent of inclusion of annealing in implant fabrication process.

Laser powder bed fusion (LPBF) can be used to fabricate complex extrusion die without the limitation of structures. Layer-by-layer processing leads to differences in microstructures and wear properties. This study aims to investigate the microstructure evolution and effects of tungsten carbide (WC) on the wear properties of LPBF-printed 18Ni300.

Economical spherical granulation-sintering-deoxygenation (GSD) WC-reinforced 18Ni300 steel matrix composites were produced by LPBF from powder mixtures of WC and 18Ni300. The effects of WC contents on anisotropic microstructures and wear properties of the composites were investigated.

The relative density is more than 99% for all the composites except 25% WC/18Ni300 composite. The grain sizes distributed on the top cross-section are smaller than those on the side cross-section. After adding WC particles, more high-angle grain boundaries and larger Schmid factor generate, and deformed grains decrease. With increasing WC contents, the hardness first decreases and then increases but the wear volume loss decreases. The side cross-section of the composite has higher hardness and better wear resistance. The 18Ni300 exhibits adhesive wear accompanying with abrasive wear, while plowing and fatigue wear are the predominant wear mechanisms of the composites.

Economical spherical GSD WC particles can be used to improve the wear resistance. The novel WC/18Ni300 composites are suitable for the application under the abrasive wear condition with low stress.

Selective laser melting and electron beam melting processes are well-known for the additive manufacturing of metal parts. Metal powder bed fusion (MPBF) is a common term for them. The MPBF process can empower the manufacturing of intricate shapes by reducing the use of special tools, shortening the supply chain and allowing small batches. However, the MPBF process suffers from many quality issues. In literature, several works are recorded for qualification of the MPBF part. The purpose of this study is to recollect those works done for quality control and report their helpful findings for further research and development.

A systematic literature review was conducted to highlight the major quality issues in the MPBF process and its root causes. Further, the works reported in the literature for mitigation of these issues are classified and discussed in five categories: experimental investigation, finite element method-based numerical models, physics-based analytical models, in-situ control using artificial intelligence (AI) and machine learning (ML) methods and statistical approaches. A comparison is also prepared among these strategies based on their suitability and limitations. Additionally, improvements in MPBF printers are pointed out to enhance the part quality.

Analytical models require less computational time to simulate the MPBF process and need a smaller number of experiments to confirm the results. They can be used as an efficient process parameter planning tool to print metal parts for noncritical applications. The AI-ML based quality control is also suitable for MPBF processes as it can control many processing parameters that may affect the quality of the MPBF part. Moreover, capabilities of MPBF printers like thinner layer thickness, smaller beam diameter, multiple lasers and high build temperature range can help in quality control.

This study converts the piecemeal data on MPBF part qualification methods into interesting information and presents it in tabular form under each strategy. This tabular information provides the basis for further quality improvement efforts in the MPBF process.

This study references researchers and practitioners on recent quality control efforts and their significant findings for a better quality of MPBF part.

The purpose of this paper is to design and manufacture an intelligent 3D printed sensor to monitor the re-occurrence of diaphragmatic hernia (DH; after surgery) in bovines as an Internet of Things (IOT)-based solution.

The approach used in this study is based on a bibliographic analysis for the re-occurrence of DH in the bovine after surgery. Using SolidWorks and ANSYS, the computer-aided design model of the implant was 3D printed based on literature and discussions on surgical techniques with a veterinarian. To ensure the error-proof design, load test and strain–stress rate analyses with boundary distortion have been carried out for the implant sub-assembly.

An innovative IOT-based additive manufacturing solution has been presented for the construction of a mesh-type sensor (for the health monitoring of bovine after surgery).

An innovative mesh-type sensor has been fabricated by integration of metal and polymer 3D printing (comprising 17–4 precipitate hardened stainless steel and polyvinylidene fluoride-hydroxyapatite-chitosan) without sacrificing strength and specific absorption ratio value.

The purpose of this paper is to determine the ultra-high cycle fatigue behavior and ultra-slow crack propagation behavior of selective laser melting (SLM) AlSi7Mg alloy under as-built conditions.

Constant amplitude and two-step variable amplitude fatigue tests were carried out using ultrasonic fatigue equipment. The fracture surface of the failure specimen was quantitatively analyzed by scanning electron microscope (SEM).

The results show that the competition of surface and interior crack initiation modes leads to a duplex S–N curve. Both manufacturing defects (such as the lack of fusion) and inclusions can act as initially fatal fatigue microcracks, and the fatigue sensitivity level decreases with the location, size and type of the maximum defects.

The research results play a certain role in understanding the ultra-high cycle fatigue behavior of additive manufacturing aluminum alloys. It can provide reference for improving the process parameters of SLM technology.

Since the biomedical implants with an improved compressive strength, near bone elastic modulus, controlled porosity, and sufficient surface roughness, can assist in long term implantation. Therefore, the fine process tuning plays its crucial role to develop optimal settings to achieve these desired properties. This paper aims to find applications for fine process tuning in laser powder bed fusion of biomedical Ti alloys for load-bearing implants.

In this work, the parametric porosity simulations were initially performed to simulate the process-induced porosity for selective laser-melted Ti₆Al₄V as per full factorial design. Continually, the experiments were performed to validate the simulation results and perform multiresponse optimization to fine-tune the processing parameters. Three levels of each control variable, namely, laser power – Pl (180, 190, 200) W, scanning speed – Vs (1500, 1600, 1700) mm/s and scan orientation – ϴ{1(0,0), 2(0,67°), 3(0,90°)} were used to investigate the processing performance. The measured properties from this study include compressive yield strength, elastic modulus, process-induced porosity and surface roughness. Finally, confirmatory experiments and comparisons with the already published works were also performed to validate the research results.

The results of porosity parametric simulation and experiments in selective laser melting of Ti₆Al₄V were found close to each other with overall porosity (less than 10%). The fine process tuning was resulted in optimal settings [Pl (200 W), Vs (1500 mm/s), ϴ (0,90°)], [Pl (200 W), Vs (1500 mm/s), ϴ (0,67°)], [Pl (200 W), Vs (1500 mm/s), ϴ (0,0)] and [Pl (200 W), Vs (1500 mm/s), ϴ (0,0)] with higher compressive strength (672.78 MPa), near cortical bone elastic modulus (12.932 GPa), process-induced porosity (0.751%) and minimum surface roughness (2.72 µm). The morphology of the selective laser melted (SLMed) surface indicated that the lack of fusion pores was prominent because of low laser energy density among the laser and powder bed. Confirmatory experimentation revealed that an overall percent improvement of around 15% was found between predicted and the experimental values.

Since no significant works are available on the collaborative optimization and fine process tuning in laser powder bed fusion of biomedical Ti alloys for different load bearing implants. Therefore, this work involves the comprehensive investigation and multi-objective optimization to determine optimal parametric settings for better mechanical and physical properties. Another novel aspect is the parametric porosity simulation using Ansys Additive to assist in process parameters and their levels selection. As a result, selective laser melted Ti alloys at optimal settings may help in examining the possibility for manufacturing metallic implants for load-bearing applications.