Production Of Metal Parts Research Articles

Smart Temperature Monitoring System for Machining Process Using Internet of Things

Outer surface integrity must be maintained throughout the machining process during the production of metal parts, which need the ability to monitor temperatures in real time. Changes in temperature during the machining process lead to changes in the behavior of the product after work is completed.To achieve quality and productivity criteria, the metal parts manufacturing process requires a continuous and precise temperature measuring and monitoring system by using IOT. An intelligent temperature measurement can be used during machining processes on conventional, non-conventional, and computer numerical control (CNC) machines. This paper presents a performance analysis of a temperature measuring system for machining process applications via Arduino IDE. In this proposal, a temperature monitoring system based on Arduino is used. The system would utilize an: MLX90614 infrared thermometer sensor” to measure the temperature of the workpiece during machining processes. The methodology's aim is to use the smart manufacturing model to measure and monitor the arising temperatures throughout the machining process in order to build a new tool path rapidly and efficiently. The placement of a non-contact infrared “MLX90614” temperature sensor allowed measuring of the average cutting temperature as well as the maximum cutting temperature. The data acquisition process was carried out using the “Xampp” Control Panel software, which communicated with the ESP32 “microcontroller” board using the Arduino IDE program. Experiments were carried out, so that the temperature of the cutting, which was measured, was recorded, and the results of the experiments were analyzed. Index Terms: Smart Manufacturing, Internet of Things, MLX90614 Infrared Temperature Sensor, Machining Parameters.

Evaluating the performance of Bi58Sn42 mold produced by material extrusion additive manufacturing system for agile manufacturing

PurposeThe purpose of this study is to produce a low-cost sheet metal forming mold made from the low melting point Bi58Sn42 (bismuth) alloy by using an open-source desktop-type material extrusion additive manufacturing system and to evaluate the performance of the additively manufactured mold for low volume sheet metal forming. Thus, it was aimed to develop a fast and inexpensive die tooling methodology for low-volume batch production.Design/methodology/approachInitially, the three-dimensional printing experiments were performed to produce the sheet metal forming mold. The encountered problems during the performed three-dimensional printing experiments were analyzed. Accordingly, both tunings in process parameters (extrusion temperature, extrusion multiplier, printing speed, infill percentage, etc.) and customizations on the extruder head of the available material extrusion additive manufacturing system were made to print the Bi58Sn42 alloy properly. Subsequently, the performance of the additively manufactured mold was evaluated according to the dimensional change that occurred on it during the performed pressing operations.FindingsResults showed that the additively manufactured mold was rigid enough and proved to have sufficient strength in sheet metal forming operations for low-volume production.Originality/valueAlternative mold production was carried out using open-source material extrusion system for low volume sheet metal part production. Thus, cost effective solution was presented for agile manufacturing.

Functional behaviour of novel multi-layered deposition via twin wire arc additive manufacturing: Microstructure evolution and wear tailoring characteristics

Twin wire arc additive manufacturing offers advantages such as high deposition rates and the ability to use a wide variety of materials, making it suitable for large-scale metal part production with enhanced efficiency and flexibility. Functionally graded deposition (FGD) based structure of dissimilar steels (SS316LSi and ER70S-6) fabricated via twin wire arc additive manufacturing and their detailed performance analysis are accomplished in the current research work. Microstructural, mechanical, and tribological characteristics of the deposited structure were investigated and analysed. Microstructure reveals polygonal ferrite, widmanstatten ferrite, skeletal ferrite, lathy ferrite, ferrite solidification, and ferrite to austenite (F/A) transformation. FGD structure possessed a microhardness of 371 HV. Average ultimate tensile strength, yield strength, and elongation percentage were 675.98 MPa, 414.21 MPa, and 38.37 %, respectively. In wear analysis, the average coefficient of friction value of WAAM-processed FGD samples is 0.44–0.49. 3D profilometer analysis reveals that average values of roughness, maximum height of roughness, and maximum roughness valley depth are significant with increasing applied loads. The findings of the present research focus on the quality and appropriateness of dissimilar steels for structural applications and provide a novel method for creating high-strength components.

Ансамбль онтологических моделей для обеспечения интеллектуальной поддержки лазерных аддитивных технологических процессов

Barriers hindering the use of additive manufacturing processes for metal parts production are discussed. The necessity of integrating an intelligent decision support system (DSS) into the professional activities of laser additive manufactur-ing engineers is substantiated. The advantages of the developed ontological two-level approach for forming semantic information are highlighted. This approach's peculiarity lies in separating ontological models from the databases and knowledge formed on their basis—target information. The ontology dictates the rules for the structured formation and interpretation of target information. An ensemble of ontological models, forming the foundation of the developed intel-ligent system, is presented. The composition of the ensemble, the purpose of its individual components, and possible types of connections between them are described. The ensemble includes ontologies for reference databases on equip-ment and materials for laser additive manufacturing, an archive of protocols for technological operations of laser pro-cessing, a knowledge base about settings for laser processing modes, and a database of mathematical models. The en-semble of ontological models is implemented on the IACPaaS cloud platform using its tools. Ontologies, databases, knowledge bases, and a decision support system are part of the Laser Additive Manufacturing Knowledge Portal. Ac-cumulating and using the knowledge and experience from different technologists in the portal will reduce the number of preliminary experiments needed to identify suitable technological modes and lower the qualification requirements for users of technological equipment.

STUDY OF THE RELIABILITY AND OPTIMIZATION OF THE AUTOMATED ROLLING STAMPING COMPLEX

The reliability of technical objects is one of their most important quality characteristics. Automated rolling stamping complexes are widely used in mechanical engineering for the manufacture of parts of complex shape. Reliability of CABs is a key factor that determines their efficiency and cost-effectiveness. The development of a device for automatically changing the equipment of the stamping-rolling complex is due to the need to increase efficiency and automate production processes in industry. Roll stamping is an important technology for the production of metal parts, but the process of changing equipment (for example, tools or dies) can be time- and resource-intensive. The development of an automatic equipment changer can significantly improve the productivity and efficiency of production lines, reduce equipment downtime and manual labor costs. In addition, such a device can increase occupational safety and reduce the risk of injury among workers. Since modern industry is rapidly developing and constantly improving production technologies, the development of a device for automatically changing equipment for a stamping-rolling complex is an urgent and important task. The implementation of such a device can help enterprises maintain a competitive edge in the market and increase their efficiency and profitability. The article deals with the reliability of the automated rolling stamping complex, which is one of the key aspects of modern production. Factors affecting the reliability of such systems and ways to increase them to ensure smooth operation of production lines are analyzed. The article reveals the main problems associated with equipment failures and downtime, which can lead to significant financial losses and loss of reputation of the enterprise. The impact of such factors as the intensity of operation, maintenance, as well as the introduction of the latest management and monitoring technologies on the overall reliability of the system was analyzed. The article proposes a comprehensive approach to increasing the reliability of automated rolling stamping complexes. This approach includes optimization of operating modes, improvement of maintenance and diagnostics systems, as well as the use of advanced management technologies and equipment condition monitoring. The results of the research can be useful for factories that use automated rolling stamping complexes in their activities. They will make it possible to increase the efficiency of the production process, reduce the costs of maintenance and repair, as well as ensure the stable and uninterrupted operation of production lines.

Optimization of extrusion-based additive manufacturing of bronze metal parts using a CuSn10/Polylactic acid composite

As additive manufacturing gains widespread adoption across various industries, its application to traditional materials such as bronze remains relatively underexplored. Through a comprehensive assessment, this research investigates the extrusion-based additive manufacturing of bronze, utilizing a CuSn10/Polylactic Acid (PLA) composite filament for printing bronze green parts, followed by thermal debinding and sintering processes to produce metal parts. By systematically varying 3D printing, debinding, and sintering parameters, optimized conditions for manufacturing bronze metal parts are identified. The study evaluates key material properties including density, ultimate tensile strength, surface morphology, and electrical conductivity of the produced metal parts. Additionally, the influence of printing parameters on dimensional deviation and shrinkage for both bronze green and metal parts is analyzed. Overall, this research highlights the potential of additive manufacturing to revolutionize bronze production, offering valuable insights into optimized process parameters and the enhancement of bronze component properties for a wide range of industrial applications.

3D printing of low carbon steel using novel slurry feedstock formulation via material extrusion method

Conventional 3D metal printing methods, such as laser sintering and binder jetting are often associated with high initial capital costs that make them inaccessible to many consumers. In this article, an economical alternative approach to 3D metal printing is presented, which uses a slurry-based formulation with the material extrusion method. This method involves a novel slurry feedstock of metal powder and liquid binder, which can be printed at room temperature to form green samples without the need for equipment such as a laser source, binder jetting head, or heated nozzle. It is followed by a thermal treatment process to fuse the printed samples into a metal article. The slurry is prepared by blending carbon steel powder with a cellulose derivative binder and additives. Rheological behaviours of different metal contents and binder concentrations are being investigated to determine the optimum printable slurry formulation. It is found that the optimum slurry feedstock formulation comprises 45 vol% metal content, 54 vol% cellulose derivative binder solution at a concentration of 300 g/L, and 1 vol% defoamer. The resulting slurry has fast-drying shear-thinning behaviour and a high storage modulus of 4 × 107 Pa to sustain the printed article at room temperature. The printed articles exhibited an average linear shrinkage of 12.36%, with less than a 1% linear shrinkage difference between X, Y, and Z directions after thermal treatment. The measured densities of the sintered articles were 95% ± 2% compared to the ASTM B783 (material code F-0000). The sintered articles have a measured carbon content of 0.28 ± 0.02%, hardness of 64.15 ± 9 HV, ultimate tensile strength of 255.33 MPa and Young's modulus of 130.47 GPa. This work demonstrates the viability of this additive manufacturing method in producing metal parts with comparable properties to conventional manufacturing.

Dimensional Characterization and Hybrid Manufacturing of Copper Parts Obtained by Atomic Diffusion Additive Manufacturing, and CNC Machining.

The combination of Atomic Diffusion Additive Manufacturing (ADAM) and traditional CNC machining allows manufacturers to leverage the advantages of both technologies in the production of functional metal parts. This study presents the methodological development of hybrid manufacturing for solid copper parts, initially produced using ADAM technology and subsequently machined using a 5-axis CNC system. The ADAM technology was dimensionally characterized by adapting and manufacturing the seven types of test artifacts standardized by ISO/ASTM 52902:2019. The results showed that slender geometries suffered warpage and detachment during sintering despite complying with the design guidelines. ADAM technology undersizes cylinders and oversizes circular holes and linear lengths. In terms of roughness, the lowest results were obtained for horizontal flat surfaces, while 15° inclined surfaces exhibited the highest roughness due to the stair-stepping effect. The dimensional deviation results for each type of geometry were used to determine the specific and global oversize factors necessary to compensate for major dimensional defects. This also involved generating appropriate over-thicknesses for subsequent CNC machining. The experimental validation of this process, conducted on a validation part, demonstrated final deviations lower than 0.5% with respect to the desired final part, affirming the feasibility of achieving copper parts with a high degree of dimensional accuracy through the hybridization of ADAM and CNC machining technologies.

Effect of copper powder addition on the product quality of sintered stainless steels

Abstract Powder metallurgy and selective laser melting (SLM) methods are widely used in producing metal parts. Adding reinforcements can improve the mechanical and physical properties of the parts. This study uses the powder metallurgy method before SLM to investigate the effect of copper reinforcement (0, 0.5, 1, 2, and 5 wt.%) on 316L and MS1 (maraging steel) material. The study started by thermochemical investigating the effects of copper addition on the phases during cooling. According to the thermochemical analysis, experimental sintering processes were carried out with the addition of copper in suitable mixing ratios. The findings show that 316L material is more convenient to the sinter than MS1 due to alloy ratios and powder sizes. Adding up to 2 wt.% copper to 316L results in a 36 wt.% reduction in linear shrinkage and improved mechanical and physical stability. The most satisfactory results were obtained by sintering the samples at 1200 °C for 1 h. This study shows that future research should focus on producing copper-reinforced 316L metal powders using SLM methods and parameter optimization and developing hybrid manufacturing methods that combine SLM with powder metallurgy.

On the possibilities of merging additive manufacturing and powder injection molding in the production of metal parts

PurposeThis 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).Design/methodology/approachPIM 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.FindingsAdvanced 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.Originality/valueThis 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.

Improvement of mechanical properties and corrosion resistance of SLM-AlSi10Mg alloy by an eco-friendly electric pulse treatment

In this study, we aim to effectively improve the mechanical properties and corrosion resistance of SLM-AlSi10Mg ally by electric pulse treatment (EPT), which is an eco-friendly method. The results show that EPT can reduce the micropores and dislocation density in SLM-AlSi10Mg alloy. It makes the dislocation distribution more uniform, without causing obvious effects on the phase composition, grain morphology and size. Compared with the as-printed SLM-AlSi10Mg alloy samples, the elongation the EPTed specimen is increased by 23.9%, while the ultimate tensile strength is only slightly decreased (about 1.2%). The fatigue test results of ten as-printed and EPTed samples selected randomly reveal that the maximum fatigue life of the EPTed sample is not significantly improved, but the minimum fatigue life is improved by about 164.4%, the average fatigue life is improved by about 49.4%, and the standard deviation is reduced by about 34.8%, which means that the EPT reduces the dispersion of fatigue life and improves the service stability. Moreover, electrochemical measurements confirme that the EPTed sample has more positive open circuit potential, corrosion potential, and pitting potential, and smaller corrosion current than those of the as-printed sample, which indicates that EPT enhances the corrosion resistance of SLM-AlSi10Mg alloy. In this paper, the service performance of AlSi10Mg alloys prepared by a clean process (SLM) is improved via an eco-friendly post-treatment process (EPT), which provides a new light to about cleaner production of metal parts.

Strain rate-dependent tensile response and deformation mechanism of laser powder bed fusion 316L stainless steel

The laser powder bed fusion (LPBF) process is renowned for producing metal parts with exceptional mechanical properties, attributed to their unique microstructures. However, there is a lack of discussion in the literature regarding the plastic deformation mechanism at wide strain rates. To address this research gap, this study employs both quasi-static tensile (QST) tests and dynamic Split-Hopkinson tensile bar (SHTB) experiments to investigate the tensile properties and deformation mechanisms of a well-characterized material, 316L stainless steel (SS), across an extensive range of strain rates spanning from 10−3 s−1 to 103 s−1. Our results reveal the superior quasi-static and dynamic stretching behavior exhibited by LPBF specimen in comparison to the wrought 316L counterpart. This enhanced behavior can be primarily attributed to the cellular and hierarchical structures inherent to LPBF specimen. Notably, the cellular structure emerges as the primary controlling factor in mechanical deformation due to its capacity for increasing the critical strain required for deformed twinning and martensite transition. Consequently, under quasi-static loading, twinning and martensite transition act as the dominant deformation mechanism, while dynamic loading conditions are characterized by a prevalence of dislocation interactions. This comprehensive understanding of the deformation mechanism and strain rate-dependent behavior of LPBF 316L SS provides valuable insight for optimizing its mechanical properties under a wide range of loading conditions.

Microstructural Characterization of 1.4542 Type Stainless Steel Specimens Manufactured by Fused Filament Fabrication

The processes of design and manufacturing continue to expand with extraordinary opportunities due to the emergence and development of additive manufacturing technologies. Additive manufacturing processes radically differ from traditional manufacturing methods and require a completely new engineering approach. As a result, new possibilities emerge, allowing the creation of geometries that were previously difficult or impossible to produce using other technologies. Significant application opportunities exist in fields such as medicine and many sectors of industry due to this advancement. The range of materials used in additive manufacturing is constantly improving and expanding, although the most significant results are in the area of industrial applicability, which is the focus of this research. It is important to mention that besides Selective Laser Sintering / Selective Laser Melting (SLS / SLM), Fused Filament Fabrication (FFF) is worth considering for producing metal parts, due to lower costs and the possibility of manufacturing larger parts. The aim of the research is to examine the microstructural and macrostructural characteristics of finished components produced by FFF.

Effects of Full Chain Processes on the Performance of 316L Stainless Steel Composite by Fused Deposition Modeling and Sintering

Fused deposition modeling and sintering (FDMS) is a novel 3D printing technique that combines fused deposition modeling with catalytic debinding and sintering processes to enable the rapid production of metal parts with low energy consumption and costs. Firstly, a 316L/POM composite filament is prepared. Subsequently, test specimens are printed using a fused deposition modeling (FDM) printer, followed by catalytic debinding and sintering processes to create dense metal parts. The process parameters show an influence on the part structure and, subsequently, the properties, and this study examines the microstructural characteristics of the 316L/POM composite filament at each process stage. Using tensile strength as the indicator, an orthogonal experiment is designed to identify suitable combinations of process parameters. Experimental results demonstrate that the FDMS process can manufacture 316L stainless steel parts; moreover, they influence the structure and, consequently, the mechanical behavior, as these are strongly related. By appropriately adjusting the process parameters, this method can be suitable for applications requiring functional parts with less stringent strength requirements.

Formability and Dimensional Accuracy Enhancement with Controlled Tool Rotational Speed in Stretch Forming Process

We present a new stretch forming method for axisymmetric sheet metal parts production. A test bench is designed, fabricated, and mounted on a drilling machine. The blank is fixed rigidly around its periphery in the apparatus, and the forming tool is mounted on the machine spindle. Thus, the control of tool rotational speed, feed rate, and vertical motion from the upper sheet surface becomes possible. Experimental tests are then conducted to form a reference shape. Rotational speed, feed rate, lubrication effect on the final thickness distribution, and geometric profiles are studied. A new multi-pass forming method is also developed and verified. The feed rate decrease, within the range of 0.11–0.18[Formula: see text]mm/rev, reduces the sheet thinning, while its increase improves the dimensional accuracy. The rotational speed increase, within the range of 112–710[Formula: see text]rpm, reduces the thickness, while its decrease enhances the geometrical accuracy. Mineral oil seems to be more effective than greases, so the thickness drop is reduced and the dimensional accuracy is improved. The use of the multi-pass strategy avoids the sheet cracking at great forming depth. The decrease in step size, within the range of 0.3–1[Formula: see text]mm, reduces the thickness minima, while good dimensional accuracy can be obtained in the range of 0.5–1[Formula: see text]mm.

Data-driven density prediction of AlSi10Mg parts produced by laser powder bed fusion using machine learning and finite element simulation

Powder bed fusion of metals using laser beam (PBF-LB/M) is a commonly used additive manufacturing process for the production of high-performance metal parts. AlSi10Mg is a widely used material in PBF-LB/M due to its excellent mechanical and thermal properties. However, the part quality of AlSi10Mg parts produced using PBF-LB/M can vary significantly depending on the process parameters. This study investigates the use of machine learning (ML) algorithms for the prediction of the resulting part density of AlSi10Mg parts produced using PBF-LB/M. An empirical data set of PBF-LB/M process parameters and resulting part densities is used to train ML models. Furthermore, a methodology is developed to allow density predictions based on simulated meltpool dimensions for different process parameters. This approach uses finite element simulations to calculate the meltpool dimensions, which are then used as input parameters for the ML models. The accuracy of this methodology is evaluated by comparing the predicted densities with experimental measurements. The results show that ML models can accurately predict the part density of AlSi10Mg parts produced using PBF-LB/M. Moreover, the methodology based on simulated meltpool dimensions can provide accurate predictions while significantly reducing the experimental effort needed in process development in PBF-LB/M. This study provides insights into the development of data-driven approaches for the optimization of PBF-LB/M process parameters and the prediction of part properties.

Printing, Debinding and Sintering of 15-5PH Stainless Steel Components by Fused Deposition Modeling Additive Manufacturing.

Metal FDM technology overcomes the problems of high cost, high energy consumption and high material requirements of traditional metal additive manufacturing by combining FDM and powder metallurgy and realizes the low-cost manufacturing of complex metal parts. In this work, 15-5PH stainless steel granules with a powder content of 90% and suitable for metal FDM were developed. The flowability and formability of the feedstock were investigated and the parts were printed. A two-step (solvent and thermal) debinding process is used to remove the binder from the green part. After being kept at 75 °C in cyclohexane for 24 h, the solvent debinding rate reached 98.7%. Following thermal debinding, the material's weight decreased by slightly more than 10%. Sintering was conducted at 1300 °C, 1375 °C and 1390 °C in a hydrogen atmosphere. The results show that the shrinkage of the sintered components in the X-Y-Z direction remains quite consistent, with values ranging from 13.26% to 19.58% between 1300 °C and 1390 °C. After sintering at 1390 °C, the material exhibited a relative density of 95.83%, a hardness of 101.63 HRBW and a remarkable tensile strength of 770 MPa. This work realizes the production of metal parts using 15-5PH granules' extrusion additive manufacturing, providing a method for the low-cost preparation of metal parts. And it provides a useful reference for the debinding and sintering process settings of metal FDM. In addition, it also enriches the selection range of materials for metal FDM.

A review of the multi-dimensional application of machine learning to improve the integrated intelligence of laser powder bed fusion

Laser powder bed fusion (LPBF) as one of the most promising additive manufacturing (AM) technologies, has been widely used to produce metal parts and applied in fields such as medical and aerospace. However, the full development of LPBF is still limited by the existence of a limited variety of materials suitable for LPBF, a single structure of printed components, defects in the processing, and complex post-processing. Machine learning (ML), as the core of artificial intelligence (AI), is expected to be an effective tool for LPBF related researches due to its ability to find latent relationships among numerous research issues. This paper provides a newly comprehensive review of ML applications to LPBF. The ML-assisted three stages of LPBF, including the pre-processing, in-situ processing and post-processing, are systematically reviewed. In the pre-processing phase, the application of ML in designing lightweight structures as well as high-performance materials are analyzed in detail. The optimization on the identification of the process and real-time monitoring during the in-situ processing stage are thoroughly discussed. In the post-processing stage, the material-structure-performance (MSP) relationship and their optimization are summarized. Based on the comprehensive review, challenges and perspectives for ML multiscale application development are eventually envisaged. This work contributes a great help to utilize ML to AM and suggests meaningful guidelines for future ML applications to manufacturing work.

NiTiCu alloy from elemental and alloyed powders using vat photopolymerization additive manufacturing

The metal vat photopolymerization technique (MVP) has high potential for metal part production because of its high accuracy, speed, and flexibility. However, low density, poor mechanical properties, and effects of sintering parameters on the properties are some of the challenges in MVP. This paper is the first to investigate the possibility of producing a NiTiCu metal alloy using VP from Ni, Ti, and Cu elemental and mechanically alloyed powders. The effect of particle size distribution and solid content on the physical and mechanical properties is also studied and compared. The results indicate that all three elements are homogeneously distributed in the whole print without premixing the powders, which considerably reduces processing time. Finer particle size and higher solid content also improve densification degree, hardness, flexural strength, and surface quality of the final parts. The measured surface roughness (Ra) of NiTiCu was 6.42 µm and 10.31 µm for milled and elemental powders, respectively. However, the mechanical properties of NiTiCu produced by VP in this study remain insufficient and in need of further improvement.

Effects of laser rescanning on microstructure and mechanical properties of Al-10Si-1Mg alloy produced by laser-directed energy deposition

Laser-based additive manufacturing (AM) is a powerful tool for the production of complex metal parts. In this study, the Al-10Si-1Mg (wt%) alloy was fabricated using the laser-based directed energy deposition (L-DED) process. Additionally, the laser rescanning (LRS) process was used to fabricate samples under the same L-DED processing parameters. The microstructure and mechanical properties of the samples were investigated. Microstructural analysis showed the presence of a unique microstructure containing relatively coarse dendrites near the laser melt-pool boundary and fine equiaxed grains inside the melt pool. LRS was shown to effectively alter the grain size and texture of the alloy. Tensile tests in directions vertical and transverse to the L-DED BD showed that only the L-DED-processed alloys exhibited strong anisotropy in their mechanical properties. The LRS-processed samples exhibited significant improvements in strength and elongation with significantly reduced anisotropy compared to the L-DED-only processed samples. Under the same laser volumetric energy density conditions, increasing the laser scanning speed could effectively reduce the porosity, which resulted in a significant improvement in the mechanical properties with and without the LRS.