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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.

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.

This paper aims to present a systematic approach in the literature survey related to metal additive manufacturing (AM) processes and its multi-physics continuum modelling approach for its better understanding.

A systematic review of the literature available in the area of continuum modelling practices adopted for the powder bed fusion (PBF) AM processes for the deposition of powder layer over the substrate along with quantification of residual stress and distortion. Discrete element method (DEM) and finite element method (FEM) approaches have been reviewed for the deposition of powder layer and thermo-mechanical modelling, respectively. Further, thermo-mechanical modelling adopted for the PBF AM process have been discussed in detail with its constituents. Finally, on the basis of prediction through thermo-mechanical models and experimental validation, distortion mitigation/minimisation techniques applied in PBF AM processes have been reviewed to provide a future direction in the field.

The findings of this paper are the future directions for the implementation and modification of the continuum modelling approaches applied to PBF AM processes. On the basis of the extensive review in the domain, gaps are recommended for future work for the betterment of modelling approach.

This paper is limited to review only the modelling approach adopted by the PBF AM processes, i.e. modelling techniques (DEM approach) used for the deposition of powder layer and macro-models at process scale for the prediction of residual stress and distortion in the component. Modelling of microstructure and grain growth has not been included in this paper.

This paper presents an extensive review of the FEM approach adopted for the prediction of residual stress and distortion in the PBF AM processes which sets the platform for the development of distortion mitigation techniques. An extensive review of distortion mitigation techniques has been presented in the last section of the paper, which has not been reviewed yet.

dding dopants to a powder bed could be a cost-effective method for spatially varying the material properties in laser powder bed fusion (LPBF) or for evaluating new materials and processing relationships. However, these additions may impact the selection of processing parameters. Furthermore, these impacts may be different when depositing nanoparticles into the powder bed than when the same composition is incorporated into the powder particles as by ball milling of powders or mixing similarly sized powders. This study aims to measure the changes in the single bead characteristics with laser power, laser scan speed, laser spot size and quantity of zirconia nanoparticle dopant added to SS 316 L powder.

A zirconia slurry was inkjet-printed into a single layer of 316 SS powder and dried. Single bead experiments were conducted on the composite powder. The line type (continuous vs balling) and the melt pool geometry were compared at various levels of zirconia doping.

The balling regime expands dramatically with the zirconia dopant to both higher and lower energy density values indicating the presence of multiple physical mechanisms that influence the resulting melt track morphology. However, the energy density required for continuous tracks was not impacted as significantly by zirconia addition. These results suggest that the addition of dopants may alter the process parameter ranges suitable for the fabrication of high-quality parts.

This work provides new insight into the potential impact of material doping on the ranges of energy density values that form continuous lines in single bead tests. It also illustrates a potential method for spatially varying material composition for process development or even part optimization in powder bed fusion without producing a mixed powder that cannot be recycled.

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.

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.

In recent years, additive manufacturing techniques have attracted much research attention because of their ability to fabricate customised parts with complex geometry. The range of composites suitable for laser-based powder bed fusion technique is limited, and has not been investigated yet. This paper aims to study the fabrication of AlSi₁₀Mg reinforced with nAl₂O₃ using the laser-based powder bed fusion technique.

An experimental approach was used to investigate the densification of AlSi₁₀Mg–nAl₂O₃ composites using laser-based powder bed fusion technique. Optimisation of the porosity was performed, and microstructure evolution was evaluated.

In this study, laser volumetric energy density (approximately 109 J/mm³) was found to be required for the fabrication of AlSi₁₀Mg–nAl₂O₃ composites with a relative volumetric density approximating 99%. The use of laser volumetric energy density resulted in larger grains. Columnar grain structure was observed via the use of electron backscatter diffraction mapping.

This paper examines the processing of new aluminium composite material suitable for the fabrication via the laser-based powder bed fusion technique.

This paper aims to develop efficient and simple models for thermal distribution, melt pool dimensions and controlled phase change in the laser additive manufacturing (AM) of bulk and powder particles ceramic materials.

This paper proposes new analytical models for the AM of bulk and powder bed ceramic materials. A volumetric moving heat source, along with the complete melting of bulk and powder particle materials, is taken into account. Different values of laser absorption coefficient in solid and liquid states have been used to investigate the phase transformation. Furthermore, the pores and voids dimensions are also included in the modeling. Theoretical predictions have been compared with the experimental analyses and finite element simulations in laser to silicon nitride and laser to alumina interaction. The analysis focuses on the impact of laser power and scanning speed on the melt pool width and depth evolution into the bulk substrate and powder bed.

This study shows that the powder particles exhibit a higher thermal distribution value than the bulk substrate because of voids in the powder layer. The laser beam experiences multiple reflections in the presence of porosity/voids, thus increasing the surface absorption coefficient, which becomes relevant with the increment in the pore/void dimension. A direct relationship has been found between the laser power and melt pool dimensions, while the scanning speed displayed an inverse relationship for the melt pool width and length. Larger melt dimensions were inferred in the case of laser–powder particle interaction compared with laser–bulk substrate interaction. A close correlation was found between the analytical simulations, experimental investigations and numerical simulation results within the range of 4%–8%.

This paper fulfills an identified need to develop efficient and simplified models for ceramics laser AM by taking into account different laser absorption coefficients in solid and liquid form, voids and pores dimensions and controlled phase transformation to avoid vapors and plasma formation. The limitation of the finite element simulation model is that the solution is strongly dependent on the mesh quality and accuracy directly linked to the computation efficiency and time. A finer mesh requires a longer computing time than a coarse mesh. Finite element simulations require, however, specialized skills.

This study aims to provide a comprehensive overview of the current state of the art in powder bed fusion (PBF) techniques for additive manufacturing of multiple materials. It reviews the emerging technologies in PBF multimaterial printing and summarizes the latest simulation approaches for modeling them. The topic of “multimaterial PBF techniques” is still very new, undeveloped, and of interest to academia and industry on many levels.

This is a review paper. The study approach was to carefully search for and investigate notable works and peer-reviewed publications concerning multimaterial three-dimensional printing using PBF techniques. The current methodologies, as well as their advantages and disadvantages, are cross-compared through a systematic review.

The results show that the development of multimaterial PBF techniques is still in its infancy as many fundamental “research” questions have yet to be addressed before production. Experimentation has many limitations and is costly; therefore, modeling and simulation can be very helpful and is, of course, possible; however, it is heavily dependent on the material data and computational power, so it needs further development in future studies.

This work investigates the multimaterial PBF techniques and discusses the novel printing methods with practical examples. Our literature survey revealed that the number of accounts on the predictive modeling of stresses and optimizing laser scan strategies in multimaterial PBF is low with a (very) limited range of applications. To facilitate future developments in this direction, the key information of the simulation efforts and the state-of-the-art computational models of multimaterial PBF are provided.

The purpose of this study is to investigate the microstructural evolution of high-strength 2024 Al alloy prepared by the laser powder bed fusion (L-PBF) additive manufacturing (AM) route. The high-strength wrought Al alloy has typically been unsuitable for AM due to its particular solidification characteristics such as hot cracking, porosity and columnar grain growth.

In this research work, samples were fabricated using L-PBF under various laser energy densities by varying laser power and scan speed. The microstructural features that developed during the solidification are correlated with operating laser parameters. In addition, finite element modelling (FEM) was performed to understand the experimentally observed results.

Microstructure evolution and defect formation have been assessed, quantified and correlated with operating laser parameters. Thermal behaviour of samples was predicted using FEM to support experimental observations. An optimised combination of intermediate laser power and scan speed produced the least defects. Higher energy density increased hot tearing along the columnar grain boundaries, while lower energy density promoted void formation. From the quantitative results, it is evident that with increasing energy density, both the top surface and side wall roughness initially reduced till a minimum and then increased. Hardness and compressive strength were found to decrease with increasing power density due to stress relaxation from hot tearing.

This research work examined how L-PBF processing conditions influence the microstructure, defects, surface roughness and mechanical properties. The results indicates that complete elimination of solidification cracks can be only achieved by combining process optimisation and possible grain refining strategies.