Different Combinations Of Process Parameters Research Articles

Optimizing SLM process parameters using FE analysis for distortion mitigation

The investigation aimed to determine the optimal value of process parameters to minimize distortion while reducing the overall printing time. To achieve this, different combinations of process parameters are selected, and 25 sets of FE experiments are prepared using an orthogonal matrix. The coupled thermomechanical analysis with the element birth technique is used to mimic the behavior of Selective Laser Melting (SLM). Initially, a mesh convergence study is performed to reduce computation time with the least sacrifice in results. To minimize the temperature gradient, simulations are performed at different levels of bed temperature ranging from 303 K to 843 K. The minimum distortion was observed for a higher bed temperature of 843 K, as at this temperature, the gradient in temperature is minimum, resulting in the least development of residual stresses. The interactive behavior between laser power and scanning speed is studied, revealing an approximately linear trend with respect to distortion while keeping all other parameters constant. Additionally, it was observed that laser power and layer thickness also exhibited a similar linear trend with respect to distortion. To identify the optimal process parameter value within the design space, the Multi-Island Genetic Algorithms (MIGA) technique is employed, leading to a remarkable minimum distortion of 0.45 mm for a specific set of input process parameters.

Friction Stirs Processing - State of The Art Process to Fabricate Metal Matrix Composites

Friction stir processing(FSP) is the solid state method to fabricate the surface metal matrix composites(MMC). This process has been derived from the concept of Friction stir welding. As this process is performed in solid state, many defects related to phase transformation can be avoided. As this process is done below the melting point temperature of metal or alloy, it is easier to control the process. Machine variables (tool rotational speed, tool traverse speed, tool tilt angle etc.), tool design variables (diameter, profile and height of probe and shoulder of the FSP tool), and material properties are the main process variables to perform FSP in order to fabricate Metal matrix composite. In addition to these variables number of passes, tool traverse patterns, reinforcement particles’ content and its’ types also can be considered as process variables. Tribological properties’ comparison can be done between alloy and MMC fabricated by FSP for different combinations of process parameters. Microstructural study also can be carried out in order to see the effects of above process parameters. In this paper the above aspects are summarized and performance assessment done by various researchers has been covered.

Optimizing mechanical properties of virgin and recycled PLA components using Anova and neural networks

The increasing demand for polymers in additive manufacturing (AM) has led to a significant increase in plastic waste, with over 300 million metric tons used in recent years. This research article explores the use of Poly Lactic Acid (PLA) as a biodegradable thermoplastic recycled material for 3D printed components, comparing its properties with virgin PLA and discussing solutions for variation and mechanical features improvement. Fused Deposition Modeling (FDM) is a widely used additive manufacturing process that allows for the creation of three-dimensional objects by depositing molten material layer by layer. This study investigates the impact of infill density, layer thickness, and raster angle for recycled 3D printing material, focusing on their dimensions and their influence on processing efficiency. This research paper aims to investigate the mechanical effects of recycled 3d printed components which are printed by using FDM with the combination of different process parameters compared with virgin PLA. From results optimal process parameters are found to enhancing quality and performance of recycled 3D printed components. Later results are compared by Analysis of Variance (ANOVA) as a statistical tool and also with ANN technique, which minimizes error deviation.

Effect of Process Parameters on the Crystallinity and Geometric Quality of Injection Molded Polymer Gears and the Resulting Stress State during Gear Operation.

The quality of gear manufacturing significantly influences the way load is distributed in meshing gears. Despite this being well-known from practical experience, gear quality effects were never systematically characterized for polymer gears in a manner able to account for them in a standard calculation process. The present study employs a novel combination of numerical and experimental methods, leading to a successful determination of these effects. The findings of the study enhance existing gear design models and contribute to a more optimized polymer gear design. The study first explores the effect of injection-molding parameters on the gear quality and secondly the effect of resulting gear quality on the stress conditions in a polymer gear pair. For the gear sample production, different combinations of process parameters were investigated, and a classic injection-molding and the Variotherm process were utilized. Gear quality and crystallinity measurements were conducted for all produced gears, providing insights into the correlation between them. Based on the evaluated gear quality of produced samples, the effect of gear quality was further studied by numerical means within a meaningful range of quality grades and transmitted loads. Special attention was dedicated to lead and pitch deviations, which were found to exert a noteworthy influence on the stress state (both root and flank) of the gear. The effect of lead deviation was most pronounced when improving the gear quality from grade Q12 to grade Q10 (30% to 80% stress reduction, depending on the load). However, enhancing the quality grade from Q10 to Q8 yielded less improvement (5% to 20% stress reduction, depending on the load). A similar pattern was evident also for pitch deviations.

Microstructure and mechanical characterization of additively manufactured Fe11Cr8Ni5Co3Mo martensitic stainless steel

This study investigates the impact of various printing processes on the microstructure, grain orientation, dislocation density, residual stresses, and mechanical properties of Fe11Cr8Ni5Co3Mo0.2Si0.16Al0.12 V martensitic aged stainless steels produced through laser-based powder bed fusion (LPBF) using different processing parameters. The LPBF samples displayed varying densities, dislocation densities, and grain orientations with different combinations of process parameters. Sample 3 showed the highest densification effect, dislocation density ranged from 6.23 × 1013 m−2-1.164 × 1014 m−2. The horizontally crystallographic texture is primarily 〈111〉 orientation, it was observed that sample 3 also had a 〈001〉 orientation. The building direction has strong Gaussian texture {110} 〈001〉. The residual stress is compressive residual stress, and the maximum residual stress is depicted in sample 6, which is −222.8 ± 16.8 MPa. The optimal combination for the ultimate tensile strength and elongation was achieved using a laser power of 200 W, scanning speed of 1000 mm/s, hatch spacing of 100 μm, layer thickness of 30 μm, and laser energy density of 66.7 J/mm3. The total yield strength increase in the LPBF MSS samples, 60% can be attributed to the intensification of dislocations, with the contributions to intensity ranked in the order of σd>σt>σgb>σp.

Microstructure and mechanical characterization of direct metal laser sintered Ti-6Al-4V alloy for orthopedic implant applications

Additive manufacturing (AM) technologies like direct metal Laser sintering (DMLS) or powder bed fusion technologies enable the fabrication of complex-shaped biomedical implants. Since process parameters influence the microstructure and thus, mechanical properties of a built structure, optimizing the parameters to produce implants that can withstand the imposed biomechanical forces is necessary. In this study, biocompatible Ti-6Al-4 V samples were fabricated using nine different combinations of process parameters for DMLS technology. The optimal printing parameters were determined using mechanical and microstructural analysis of printed samples. The mechanical and microstructure analysis revealed that parts built with volumetric energy density input of 37–93 J/mm3 are nearly defect-free and suitable for biomedical implant applications.

A Comparison of Microstructure and Microhardness Properties of IN718 Fabricated via Powder- and Wire-Fed Laser-Directed Energy Deposition.

The objective of this work is to compare the microstructure and microhardness properties of IN718 deposited by both powder- and wire-fed laser-directed energy deposition (L-DED) processes. The powder-fed L-DED is carried out on an Optomec LENS® system while the wire-fed L-DED is performed in an in-house custom-built system. Several single-layer single-track specimens are fabricated using different combinations of process parameters to down-select the optimal process parameters for both systems. The finalized parameters are, thereafter, used to build thin-wall specimens having identical designs. The specimens are characterized using optical and electron microscopy as well as microhardness measurements. The results demonstrate that the powder-fed specimen, built using optimal process parameters, does not exhibit any distortion. On the contrary, the wire-fed specimen, built with optimal process parameters, show lesser porosity. Differences in elemental segregation are also detected in the two specimens. For example, nitrides and carbides are observed in the wire-fed specimen but not in the powder-fed specimen. The microhardness measurements reveal the powder-fed specimen has higher microhardness values compared to the wire-fed specimen. These results can be used to fabricate parts with sequential powder and wire deposition to achieve biomimetic structures of varying microstructure and microhardness properties.

Parameter Optimization of Intercalated Meltblown Nonwovens Based on NSGA-II

The preparation process parameters of intercalated meltblown nonwoven materials are complicated, and the relationship between process parameters, structural variables, and product performance needs to be investigated to establish a good mechanism for product performance regulation. In this study, we first used Wilcoxon test and Pearson correlation analysis to investigate the effect of intercalation rate on structural variables and product performance. Then, regression models were constructed to predict the values of each structural variable under different combinations of process parameters. Finally, we constructed a multi-objective constrained optimization problem based on the stepwise regression model and the product variable conditions. The problem was solved using the NSGA-II algorithm. The optimal was achieved when the acceptance distance was 2.892 cm and the hot air speed was 2000 r/min.

Developing a numerical model to analyze the production process of PMEDM

Production process optimization has been considered as one of the essential elements in modern metal mines context. Several operations were started to modify with these resources concern, which mainly includes machining processes. Various technological developments have been evident in these machining processes including electrical discharge machining. However, due to several limitations of conventional process, powder mixed discharge machining has been brought into the research realm. Recent years, many applications can be found under the mining sector. Despite of various perspectives have been considered but concerning with increase of mining process through optimizing its parameters are limited. In this study, this literature gap has been addressed, with the consideration of optimizing the production process parameters optimization of metal mines, in which concentrations of the reinforcements and peak current are considered as input parameters. The performance of the proposed parameters has been measured with the outputs including surface quality, surface roughness, material removal rate and tool wear rate. Various behavior analysis was done to identify the effective process parameters with resource optimization objective. Totally, ten different combination of process parameters were studied through numerical analysis in addition with experimental studies. Finally, the results revealed that PP2 is the best process parameter for achieving better performance. Further, the necessary future direction to explore more scientific potential on the concern topic has been discussed.

3-Dimensional heat transfer modeling for laser powder bed fusion additive manufacturing using parallel computing and adaptive mesh

In this article, an innovative 3-dimensional (3D) heat-transfer finite element parallel-computing model with adaptive mesh capability, named LPBFSim, for Laser Powder Bed Fusion (LPBF) additive manufacturing is introduced for high precision prediction of melt pool dimensions and single-layer part-level process simulations. Numerical modeling can significantly reduce the expense of the sole deployment of trial-and-error experiments for achieving optimal process parameters. The previously developed single-track model [1] is highly accurate to predict melt pool dimensions for different combinations of process parameters. However, without using parallel computing and an adaptive mesh, it is very challenging to scale it up to a multi-track model or even a part-level model due to the high computational cost. The proposed model is parallelized to be able to run on a cluster and aimed to solve this difficulty while keeping all the accuracy from the previous version. Single-track, multi-track, and single-layer part-level models have been implemented to demonstrate its efficiency and accuracy.

Numerical simulation of closed plastic impeller molding process and its parameter optimization

Aiming at the warping deformation and volume shrinkage of the closed plastic impeller, the relevant compression molding process parameters were optimized.Based on the theoretical equation of the pressing pressure for general sheet plastics, the theoretical derivation of the pressing pressure suitable for cylindrical cavities was carried out, and the theoretical derivation of the pressing pressure suitable for closed plastic impeller molding was derived, and the pressing pressure was calculated to be 15 MPa. The warpage deformation and shrinkage rates under different combinations of process parameters were obtained, and the influence of process parameters on warpage deformation and shrinkage rates, as well as the two combinations of process parameters that satisfy the best warpage deformation and shrinkage rates, respectively, were obtained by extreme difference analysis. A GA-BP neural network model was established for the prediction of the process parameters of closed plastic impeller compression molding, and the prediction curves were fitted into a function to obtain a set of process parameter combinations with optimal warpage and shrinkage at the same time by using the multi-objective optimization function of NSGA-II algorithm.

Research on the Forming Process of a Selective Laser Melting-Manufactured 316L Stainless Steel Based on Multi-Index Evaluation

This paper investigate a laser processing parameters effects on the tensile properties and surface roughness of a SLM-manufactured 316L stainless steel sample. A multi-index weight model was established using the orthogonal test and entropy weight method. Then, the model assessed the effect of three process factors (scanning speed v, filling laser power P, and scan spacing s). The influence of different combinations of processing parameters on tensile properties and surface roughness was also analyzed. The results revealed that the level of the effects on the sample’s properties from high to low was P, v, and s (P > v > s), respectively. Tensile properties were influenced by laser power and scanning speed first with an increase, followed by a decrease, while scan spacing affected tensile properties with a decrease followed by an increase; the maximum tensile strength was 693 MPa. Surface roughness was affected by filling laser power and scanning power and scanning speed first with a decrease, followed by an increase, while scan spacing affected surface roughness with an increase followed by a decrease. Under experimental conditions, when the laser energy density (E) was 69.44 J·mm−3, the surface roughness of formed parts was the best; Ra was 2.04 μm.

Thermal conductivity analysis of porous NiAl materials manufactured by spark plasma sintering: Experimental studies and modelling

This work presents a comprehensive analysis of heat transfer and thermal conductivity of porous materials manufactured by spark plasma sintering. Intermetallic nickel aluminide (NiAl) has been selected as the representative material. Due to the complexity of the studied material, the following investigation consists of experimental, theoretical and numerical sections. The samples were manufactured in different combinations of process parameters, namely sintering temperature, time and external pressure, and next tested using the laser flash method to determine the effective thermal conductivity. Microstructural characterisation was extensively examined by use of scanning electron microscopy and micro-computed tomography (micro-CT) with a special focus on the structure of cohesive bonds (necks) formed during the sintering process. The experimental results of thermal conductivity were compared with theoretical and numerical ones. Here, a finite element framework based on micro-CT imaging was employed to analyse the macroscopic (effective thermal conductivity, geometrical and thermal tortuosity) and microscopic parameters (magnitude and deviation angle of heat fluxes, local tortuosity). The comparison of different approaches toward effective thermal conductivity evaluation revealed the necessity of consideration of additional thermal resistance related to sintered necks. As micro-CT analysis cannot determine the particle contact boundaries, a special algorithm was implemented to identify the corresponding spots in the volume of finite element samples; these are treated as the resistance phase, marked by lower thermal conductivity. Multiple simulations with varying content of the resistance phase and different values of thermal conductivity of the resistance phase have been performed, to achieve consistency with experimental data. Finally, the Landauer relation has been modified to take into account the thermal resistance of necks and their thermal conductivity, depending on sample densification. Modified theoretical and finite element models have provided updated results covering a wide range of effective thermal conductivities; thus, it was possible to reconstruct experimental results with satisfactory accuracy.

Effects of the process parameters on the formability and properties of Ni54(at.%) Ti alloys prepared by laser powder bed fusion

PurposeThe purpose of this paper is to supplement and upgrade existing research on LPBF of NiTi alloys. Laser powder bed fusion (LPBF) is a promising method for fabricating nickel–titanium (Ni–Ti) alloys. It is well known that the energy density is mainly adjusted through the scanning speed and laser power. Nevertheless, there is lack in research on the effects of separately adjusting the scanning speed and laser power on the properties of the final Ni–Ti components. On the other hand, although Ni-rich Ni–Ti alloys [such as Ni54(at.%)Ti] have great potential in structural applications because of their high hardness and good shape stability, at present, there are few studies focusing on this grade of Ni–Ti alloy.Design/methodology/approachIn this work, the energy density was adjusted by changing the laser power and scanning speed separately, and the corresponding process parameters were used to fabricate Ni54(at.%)Ti alloys. The formability (including the relative density, impurity content, etc.) and tensile properties of the LPBF Ni54(at.%)Ti alloys fabricated with different combinations of process parameters were analyzed.FindingsThe effects of increasing the laser power and reducing the scanning speed on the properties of the LPBF Ni54(at.%)Ti alloys and the property differences between components manufactured with different combinations of laser power and scanning speed under the same energy density were analyzed. The optimal process parameters were selected to fabricate the components that achieved the highest ultimate tensile strength of 537 MPa, a high relative density of 98.23%, a relatively low impurity content (0.073 Wt.% of carbon and 0.06 Wt.% of oxygen) and an ideal pseudoelasticity (95% recovery rate loaded at 300 MPa).Originality/valueThe effects of increasing the laser power and reducing the scanning speed on the properties of LPBF Ni54(at.%)Ti alloys were studied in this paper. This work is an upgrade and supplement to the existing research on fabricating Ni-rich Ni–Ti alloys by the LPBF method.

Comprehensive understanding of the mechanical properties and microstructure evolution of aluminum alloy/steel laminates during friction stir-assisted incremental forming with synchronous bonding process

Aluminum alloy/steel laminated parts can be fabricated by separated sheets based on a friction stir-assisted incremental sheet forming with synchronous bonding (FS-ISF&SB) method. The current work aims to realize comprehensive understanding of microstructure evolution during FS-ISF&SB and its effect on mechanical properties of the formed parts. Three typical sets of experiments with different combinations of process parameters are carried out, and three different regions are classified by grain feature, defined as deformed region, loading region and undeformed region. Recrystallization and recovery behaviors occur at all of the three regions on both sheets, which generate softening effect. However, the effect of work hardening keeps a dominant role on mechanical property compared with softening effect on steel, while the influence level of these effects on aluminum alloy is opposite during FS-ISF&SB. Besides, stratified structure and gradient distribution of grain size from the outer surfaces to the interface are observed. The microstructure evolutions greatly accelerate the atomic diffusion and subsequently promote the metallurgical bonding of the laminates. It is also found that Fe–Al intermetallic compounds (IMCs) consisting of FeAl3 and Fe2Al5 are generated on the dissimilar interface of the fabricated parts. The thickest IMCs are usually found at the loading regions. Moreover, the maximum nominal bonding stress obtained by peeling test of the laminated parts can reach 100.0 MPa with the moderate thickness of IMCs as of 13.1 μm.

Predictive model of the solder paste stencil printing process by response surface methodology

PurposeThis paper aims to establish the predictive equations of height, area and volume of printed solder paste during solder paste stencil printing (SPSP) process in surface mount technology (SMT) to better understand the effect of process parameters on the printing quality.Design/methodology/approachAn experiment plan is proposed based on the response surface method (RSM). Experiments with 30 different combinations of process parameters are performed using a solder paste printer. After printing, the volume, area and height of the printed SAC105 solder paste are measured by a solder paste inspection machine. Using RSM, the predictive equations associated with the printing parameters and the printing quality of the solder paste are formed.FindingsThe optimal printing parameters are 175.08 N printing pressure, 250 mm/s printing speed, 0.1 mm snap-off height and 15.7 mm/s stencil snap-off speed if the target height of solder paste is 100 µm. As the target printing area of solder paste is 1.1 mm × 1.3 mm, the optimized values of the printing parameters are 140.29 N, 100.52 mm/s, 0.63 mm and 20.25 mm/s. When both the target printing height and area are optimized together, the optimal values for the four parameters are 86.67 N, 225.76 mm/s, 0.15 mm and 1.82 mm/s.Originality/valueA simple RSM-based experimental method is proposed to formulate the predictive polynomial equations for height, area and volume of printed solder paste in terms of important SPSP parameters. The predictive equation model can be applied to the actual SPSP process, allowing engineers to quickly predict the best printing parameters during parameter setting to improve production efficiency and quality.

Corrosion and Microstructural Investigation on Additively Manufactured 316L Stainless Steel: Experimental and Statistical Approach.

The use of metal additive manufacturing (AM) has strongly increased in the industry during the last years. More specifically, selective laser melting (SLM) is one of the most used techniques due to its numerous advantages compared to conventional processing methods. The purpose of this study is to investigate the effects of process parameters on the microstructural and corrosion properties of the additively manufactured AISI 316L stainless steel. Porosity, surface roughness, hardness, and grain size were studied for specimens produced with energy densities ranging from 51.17 to 173.91 J/mm3 that resulted from different combinations of processing parameters. Using experimental results and applying the Taguchi model, 99.38 J/mm3 was determined as the optimal energy density needed to produce samples with almost no porosity. The following analysis of variance ANOVA confirmed the scanning speed as the most influential factor in reducing the porosity percentage, which had a 74.9% contribution, followed by the position along the building direction with 22.8%, and finally, the laser energy with 2.3%. The influence on corrosion resistance was obtained by performing cyclic potentiodynamic polarization tests (CPP) in a 3.5 wt % NaCl solution at room temperature for different energy densities and positions (Z axis). The corrosion properties of the AM samples were studied and compared to those obtained from the traditionally manufactured samples. The corrosion resistance of the samples worsened with the increase in the percentage of porosity. The process parameters have consequently been optimized and the database has been extended to improve the quality of the AM-produced parts in which microstructural heterogeneities were observed along the building direction.

Effect of process parameters on density and mechanical behaviour of a selective laser melted 17-4PH stainless steel alloy

Abstract 17-4 PH stainless steel alloy has been widely used in the field of defence industry such as weapon equipment, aerospace, nuclear energy, and so on because of its high strength, high toughness, high temperature resistance, and corrosion resistance. In order to meet the flexible manufacturing requirements of multi-variety small batch complex structure products with lower cost and higher efficiency, selective laser-melted 17-4PH stainless steel alloy has become the focus of research in the field of rapid alloy manufacturing in recent years. In this article, the density characteristics and the distribution characteristics of holes and spheroidization phenomena of 17-4 PH pre-alloyed powder subjected to multidimensional temperature conduction under selective laser melting are studied, and the mechanism of defect generation under temperature conduction is proposed. Finally, the optimal selection of the combination of different process parameters was carried out by orthogonal test, and it was found that the comprehensive mechanical behaviour of the 17-4 PH stainless steel alloy after being formed exceeded the ASTM A564 standard (the yield strength is 1,132 MPa, the tensile strength is 1,323 MPa, and the elongation is 16.6%).

Effects of processing parameters on the performance of carbon fiber reinforced polyphenylene sulfide laminates manufactured by laser-assisted automated fiber placement

In situ consolidation of thermoplastic composites can be realized through laser-assisted automated fiber placement (AFP) technology, and the properties of composites were significant affected by the process parameters. In this work, the effects of process parameters on the properties of continuous carbon fiber–reinforced polyphenylene sulfide (CF/PPS) composites manufactured by laser-assisted AFP were investigated. Four-plies CF/PPS prepreg was laid under the combination of different process parameters and the morphology, void content, crystallinity, and inter-laminar shear strength (ILSS) of the composites were characterized. It turned out that the resin distribution on the surface of the composites could be significantly improved by increasing the laser temperature and compaction pressure. The highest crystallinity of the composites reached 46% at tool temperature of 120°C while the value was only 18% when the tool temperature was 40°C. Meanwhile, with the increasing compaction force ranging of 500–2000 N, the void content of the composites decreased obviously. The ILSS was evaluated through double notch tensile shear test. The results indicated that the mechanical properties of the composites were dominated by void content rather than crystallinity.

Machine learning application for evaluating the friction stir processing behavior of dissimilar aluminium alloys joint

This paper reports on the employment of the machine learning (ML) techniques, namely support vector machine (SVM), artificial neural networks (ANN), and random forest (RF), for predicting the tensile behavior of friction stir processed (FSP) dissimilar aluminium alloys joints (6083-T651 and 8011-H14). The dissimilar aluminium joints are fabricated using the friction stir welding (FSW) process. After that, the friction-stir welded joints are subjected to the FSP procedure at different combinations of process parameters. The rotational speed, traverse speed, and tilt angle are used as the input parameters, while tensile strength and grain size are used as the output parameters. In addition, three performance characteristics (i.e., coefficient of correlation (CC), mean absolute error (MAE), and root mean square error (RMSE)) are used to check the adequacy of the developed model of ML techniques. It is observed that support vector machine_radial basis function kernel is the most accurate modeling technique for predicting the tensile behavior of processes samples. Furthermore, the optical microscope is also utilized to check the grain size of the nugget zone (NZ) of the weld bead for FSP. It is found that the minimum grain size (i.e., 5.06 µm) is obtained for the FSP sample and this grain size corresponded to the high ultimate tensile strength (UTS). Moreover, the fractographic analysis showed the ductile behavior of FSW and FSP samples.