Set Of Process Parameters Research Articles

Investigations on hardness and surface roughness of 3D printed ABS-ZrO2 composite structures for post processing applications

The present research aims to develop composite materials made from acrylonitrile butadiene styrene (ABS) as the matrix with Zirconia (ZrO2) as the filler material. ABS-ZrO2 composite test samples were fabricated using a fused filament fabrication (FFF) based 3D Printer, using Taguchi’s L9 orthogonal array (OA). The ABS-ZrO2 composite 3D printed samples were supported by shore D hardness and surface roughness tests, which revealed that 230˚C barrel temperature, 100% infill, and octet infill pattern are the best set of FFF parameters for obtaining maximum Shore D hardness of 80.50 Shore D. This set of process parameters provide the good conditions for 3D Printing of ABS-ZrO2 composite, and it may be used as potential material for post-processing applications, whereas 240˚C barrel temperature, 60 % infill percentage, and linear infill pattern are best conditions for minimum surface roughness.

Process parameter assessment on the dissimilar deposition of AA2024-T351 on AA7475-T761 by friction surfacing

Friction surfacing as a solid-state deposition process allows the joining of materials with different chemical and physical properties at temperatures below their respective melting points. This experimental work focuses on generating sound, defect-free metallurgical joints between single friction surfacing deposits and substrate surfaces from dissimilar Al alloys of the 2xxx and 7xxx series. In this context, the influence of axial force and deposition speed on surface morphology and deposit geometry of the two heat-treatable Al alloys AA7475 as substrate and AA2024 as deposit are investigated. Process parameter variation shows that an increase in axial force from 8 to 12 kN, in conjunction with a deposition speed of 8 mm/s, leads to smooth surface morphology and consistent deposit width along its length. The AA2024 deposits consist of fine-grained microstructure with higher hardness at the top and lower hardness at the deposit-substrate interface. The joining mechanism is by interdiffusion, with a 7.5 μm thick diffusion zone across the dissimilar interface. Three-point bending tests reveal excellent bonding in the lateral surface of the advancing side due to the absence of delamination for all conditions tested. Minor delamination appears predominantly on the retreating side region for process parameter sets with low axial force. Tensile test results reveal that the AA2024 deposit on the AA7475 substrate presents an ultimate tensile strength equivalent to the AA7475-T651 base material and an increase of 37 % in ductility.

Optimization of Wire EDM Process Parameters for Machining Hybrid Composites Using Grey Relational Analysis

The materials used in engineering have seen a significant transformation in the contemporary world. Numerous composites are employed to overcome these problems because conventional materials are unable to meet the needs of current applications. For quite some time, professional engineers and researchers have been captivated by the problem of choosing the best machining parameters for new composite materials. Wire electrical discharge machining is a popular unconventional machining process that is often used for making complex shapes. Numerous process parameters influence the WEDM process. Thus, to achieve affordable and high-quality machining, the right set of process parameters must be provided. Finding the wire cut EDM optimized settings for the fabricated LM5/ZrO2/Gr composite is the main aim of this research. The chosen input parameters are the wire feed, pulse on and pulse off times, the gap voltage, and the reinforcing percentage. In this study, LM5/ZrO2/Gr composites were made from stir casting with 6-weight percent ZrO2 as the reinforcement and varying graphite percentages of 2, 3, and 4 wt%. Then they were machined in WEDM using L27 OA to seek the best parameters for machining by adjusting the input parameters. The findings were analysed by means of grey relation analysis (GRA) to achieve the supreme material removal rate (MRR), lowest surface roughness (SR), and a smaller kerf width (Kw) simultaneously. GRA determines the impact of the machining variables on the standard characteristics and tests the impact of the machining parameters. Confirmation experiments were performed finally to acquire the best findings. The experimental findings and GRA show that the ideal process conditions for achieving the highest grey relational grade (GRG) are 6% ZrO2 with 2% graphite reinforcement, a wire feed of 6 m/min, a pulse off time (Toff) of 40 µs, a pulse on time (Ton) of 110 µs, and a gap voltage (GV) of 20 V. The gap voltage (22.87%) has the greatest impact on the GRG according to analysis of variance (ANOVA), subsequent to the interaction between the pulse on time and the gap voltage (16.73%), pulse on time (15.28%), and pulse off time (14.42%). The predicted value of the GRG is 0.679; however, the experimental GRG value is 0.672. The values are well-aligned between the expected and the experimental results. The error is only 3.29%, which is really little. Finally, mathematical models were created for each response.

A Thermomechanical Model for Time-Varying Deformations of Spigot Interference Connection under Shrink-Fitting Assembly

The interference fit connection structure is widely employed in various industries. Different from the conventional connection structure, the aero-engine rotor connection has a spigot-bolt structure. The quality of the shrink-fitting assembly process directly affects the final assembly performance of the rotor. The complexity of the connection structure and the time-varying thermal deformation bring great challenges in analyzing the formation patterns of connection performance. However, existing methods of interference connection analysis are mainly used in the wide range of interference connection structures, which makes them difficult to apply in low height interference connection for aero-engine rotors. This paper introduces a thermomechanical interference fit pressure model. First, a theoretical model for interference fit pressure considering temperature-variable loads is established to obtain the time-varying pressure during the assembly process. Second, a finite element model is established to explore the influence of interference and temperature loads on the spigot pressure and the mounting edge deformation. Finally, the experiments validate the accuracy of both the theoretical model and the finite element analysis. The results indicate that during the shrink-fitting assembly process, the interference fit pressure exhibits a nonlinear evolution trend, and the warping deformation of the mounting edge is a result of the combined influence of temperature and interference fit pressure. The law found in this paper has an application prospect in the process parameter setting of shrink-fitting assembly for special structures.

Optimizing solidification dendrites and process parameters for laser powder bed fusion additive manufacturing of GH3536 superalloy by finite volume and phase-field method

Investigating the surface morphology and microstructure of laser powder bed fusion (L-PBF) in solidification and optimizing process parameters is crucial for improving the accuracy and performance of cladding parts of GH3536 superalloy. In this study, a computational model incorporating Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM) was utilized to simulate the mesoscale evolution of the molten pool in L-PBF for GH3536 superalloy. Furthermore, the growth of columnar dendrites along the fusion boundary under transient conditions was simulated utilizing a quantitative phase-field model. The impact of scanning speed and laser power on temperature distribution, molten pool size, surface morphology of cladding layer, and columnar dendrite spacing during solidification of single-track L-PBF were examined. The findings suggest that the molten pool undergoes a fast process characterized by significant temperature gradients. Increasing the laser power or reducing the scanning speed results in higher maximum molten pool temperature, as well as increased molten pool depth and width. Overlarge or undersized scanning speed and laser power can result in poor surface quality of the cladding layer. When the laser power was 120 W and the scan speed was 0.4 m/s, the cladding layer exhibited improved surface morphology, with finer columnar dendrites observed at the molten pool's base. This study delved into understanding the evolution characteristics of the molten pool and the growth process of columnar dendrites at the molten pool's base, providing valuable insights for determining appropriate experimental process parameters for L-PBF of GH3536 superalloy.

Processability of High-Speed Steel by Coaxial Laser Wire Deposition Technology for Additive Remanufacturing of Cutting Tool

The recently introduced Coaxial Laser Wire Deposition technology can become a new promising method for remanufacturing high-complexity and expensive cutting tools (e.g., flat broach), which will have a significant impact on their service life. In addition, it is an innovative approach to tool management. An analysis of the feasibility of processing cobalt-added HSS powder steels was carried out for single clads and multilayer structures. The effect of process parameters (laser, beam power, travel speed, wire feed rate) on geometric properties, hardness and microstructure was discussed. In order to avoid cracking during multilayer deposition, an additional preheating to 320 °C was applied. Two sets of process parameters with high and low heat input were obtained. Both sets lead to crack-free structures that fulfill geometric (≥2.5 mm in height) and hardness (≥700 HV) requirements.

Numerical Simulations of Carbon-Fibre Impregnation with a Polymer as an Anisotropic Permeability Medium.

The impregnation process of carbon fibres with polymers is challenging to model due to the system's complexity, particularly concerning the following aspects: the complex rheology of the polymeric matrices and the presence of solid, continuous fibres, both with anisotropic properties, and the interaction between solid and fluid, which can change the displacement of fibres into a cyclic dependence. In this work, an interesting approach was considered by setting the fibres as a porous medium whose properties were calculated with microscale/macroscale cycle modelling. In the microscale modelling stage, two main assumptions can be made: (i) a homogeneous distribution with a representative cell or (ii) a stochastic distribution of fibres. The solution to the abovementioned flow and fibre distribution problem can severely differ with only a slight change in a single parameter for a given set of processing parameters. Therefore, the influence of some of them during the fibre impregnation process was evaluated, allowing a shortcut for the polymer through a gap between fibres and the bottom wall of the extrusion die. The range of investigated values regarding the gap enables one to cover good impregnation conditions up to the occurrence of the shortcut and consequent poor impregnation quality. These studies were performed with numerical simulations with circa 126,000 degrees of freedom, considering the discretisation mesh elements and the unknowns (pressure and two velocity components).

Research on the integral forming process of thin walled and thick mouth seamless gas cylinders

There is a considerable difference in wall thickness between the mouth and the cavity of thin-walled and thick-mouthed seamless gas cylinders, and the existing manufacturing processes are unable to effectively meet product requirements. To overcome such issue, a step-by-step boring-necking-spinning solution for gas cylinders was proposed, in which sufficient wall thickness is reserved for the mouth area of the cylinder blank, followed by necking-spinning to realize the overall forming of thin-walled, thick-mouthed seamless gas cylinders. The stress–strain distribution and geometric dimensional changes of gas cylinders during the spinning process were investigated by means of finite element simulation, and the effects of different process parameters on the stress and wall thickness of the bottle mouth were analyzed. Further, multi-objective optimization of the response surface model was performed using the NSGA-II algorithm to derive a set of optimal process parameters. Finally, the correctness of the simulation and optimization results was verified experimentally, and the expected geometry and optimal strain state of the gas cylinder were obtained. The newly developed processing solution represents a groundbreaking advancement in the manufacturing of thin-walled and thick-mouthed gas cylinders.

Effect of laser surface remelting on Microstructure, mechanical properties and tribological properties of metals and alloys: A review

Surface defects like porosity, cracks, coarse grains, surface roughness, etc. have a huge impact on the strength and performance of materials. Due to this, surface treatments have become an important part in the field of materials to attain certain desirable mechanical properties and surface properties. Surface of parts treated with laser surface remelting exhibits excellent surface and mechanical properties. It is a computer-based technique which provides the advantage of treating selective surfaces. Laser surface remelting tends to enhance corrosion resistance, microhardness, wear resistance, fatigue strength, and tensile strength of the materials. To achieve certain mechanical properties with laser surface remelting, an optimized set of laser processing parameters is essential. Laser surface remelting has become a compulsory treatment for parts manufactured by Additive Manufacturing (AM) processes as these processes provide poor surface, porosity, and hot cracking defects which ultimately affect the performance of parts. This paper critically evaluates the advancements which have been made in the field of laser surface remelting to get better surface quality, improved mechanical and tribological properties.

Machine learning-based multi-objective parameter optimization for indium electrorefining

A novel approach utilizing support vector regression algorithm (SVR) is presented for developing forecast models of Cu and Pb concentrations in indium electrolysis products. These models are based on a subset of process parameters and purity data. The optimization of Cu and Pb content is achieved through the integration of the forecast models with a multi-objective genetic algorithm. Consequently, a set of optimal electrolysis process parameters is identified for the electrolytic refining of high-purity indium. The determined optimal parameters are as follows: In3+ concentration of 80–90 g·L-1, NaCl concentration of 85–120 g·L-1, gelatin concentration of 0.5–0.6 g·L-1, current density of 65–70 A·m−2, pH value of 2.5, and pole pitch of 40–60 mm. To validate the effectiveness of these optimized parameters, experimental tests are conducted to confirm that the Cu and Pb contents conform to the national standard for 5 N indium. By employing this innovative approach, the study not only provides insights into the forecast modeling of Cu and Pb concentrations in indium electrolysis products but also contributes to the advancement of the electrolytic refining process for achieving high-purity indium.

Optimization of Abrasive Waterjet Cutting by Using the CODAS Method with Regard to Interdependent Processing Parameters

The paper shows performance optimization effects of steel machining by abrasive water jet (AWJ). An innovative combinative distance-based assessment method (CODAS) is implemented for the optimization of cutting parameters like pump pressure, feed rate, and abrasive flow rate over cutting depth, and cut kerf surface roughness. The CODAS algorithm is among those based on measuring the distance between a scenario (in this case processing parameters in terms of performance and quality indicators) - and a certain benchmark. A benchmark is a specific hypothetical set of processing parameters devised or determined from available data. To determine the best set of process control parameters, a CODAS approach was performed with some weighting determinations. To set the initial parameters of the weights, it was proposed to calculate based on entropy weight method (EWM), that measures output value dispersion in cutting process. This technique simplifies multiple compound responses by preserving a single response.

A study of the particle-reinforced bonded joint performance

In this study, a systematic study has been performed to explore the influence of the adhesive particle fillers on the mechanical performance of bonded joints. Three-dimensional finite element models were established to analyse the strength of bonded joints. Based on response surface methodology, experiments were designed with three parameters and three levels. Experimental results were applied to develop response surface models between parameters (adhesive layer thickness, particle size, and particle volume fraction) and response values (shear strength and peel strength). Response surface models incorporating genetic algorithms were applied to find the optimal set of input parameters. These findings indicated that the interaction between volume fraction and adhesive layer thickness has the most significant influence on the shear strength of joints, and the interaction between particle size and adhesive layer thickness has a major effect on the peel strength of joints. The optimal set of process parameters is: adhesive layer thickness 0.54 mm, particle size 69 µm, and volume fraction 4.0%.

Fabrication process optimization of nHA–CNTs-reinforced PEEK hybrid nanocomposite

Compression molding is the leading fabrication process for polymer composites. The settings of process parameters highly influence the mechanical properties of composites. This study optimized the ball-mixing and compression-molding process parameters for the fabrication of hybrid nanocomposites based on polyetheretherketone (PEEK), multiwalled carbon nanotubes (MWCNTs) and nano-hydroxyapatite using the Taguchi method. The elastic modulus examined using the nanoindentation method of static mechanical analysis was taken as the output response variable. The optimum levels of mixing time, mold temperature, mold pressure and holding time process parameters for the maximum elastic modulus were found to be 90 min, 400°C, 150 bar and 15 min, respectively. The analysis of variance technique showed that the mold temperature had the highest contribution (46.82%) in enhancing the elastic modulus to the largest value. The elastic modulus and hardness of the PEEK-based hybrid nanocomposite with 30 wt.% nHA and 3 wt.% MWCNTs were observed to be 83 and 65% higher than those of pure PEEK, respectively. The hydrophilicity of PEEK was improved with the reinforcement of nHA, attributed to the presence of oxygen-containing functional groups in the chemical structure of nHA.

Influence of fused deposition modelling printing parameters on tablet disintegration times: a design of experiments study.

Despite the importance of process parameters in the printing of solid dosage forms using fused deposition modelling (FDM) technology, the field is still poorly explored. A design of experiment study was conducted to understand the complete set of process parameters of a custom developed FDM 3D printer and their influence on tablet disintegration time. Nine settings in the Simplify 3D printing process design software were evaluated with further experimental investigation conducted on the influence of infill percentage, infill pattern, nozzle diameter, and layer height. The percentage of infill was identified as the most impactful parameter, as increasing it parabolically affected the increase of disintegration time. Furthermore, a larger nozzle diameter prolonged tablet disintegration, since thicker extruded strands are generated through wider nozzles during the printing process. Three infill patterns were selected for in-depth analysis, demonstrating the clear importance of the geometry of the internal structure to resist mechanical stress during the disintegration test. Lastly, layer height did not influence the disintegration time. A statistical model with accurate fit (R 2 = 0.928) and predictability (Q 2 = 0.847) was created. In addition, only the infill pattern and layer height influenced both the uniformity of mass and uniformity of the disintegration time, which demonstrates the robustness of the printing process.

3D Printing Technology for Short-continuous Carbon Fiber Synchronous Reinforced Thermoplastic Composites: A Comparison between Towpreg Extrusion and In Situ Impregnation Processes

Three-dimensional (3D) printing of carbon fiber-reinforced thermoplastic composites (CFRTPs) provides an effective method for manufacturing the CFRTPs parts with complex structures. To increase the mechanical performance of these parts, a 3D printing technology for short-continuous carbon fiber synchronous-reinforced thermoplastic composites (S/C-CFRTPs) has been proposed. However, the synchronous reinforcement that existed only at particular positions led to a limited improvement in the mechanical performance of the 3D-printed S/C-CFRTP part, which made it challenging to meet the engineering requirements. To solve this problem, two methods for achieving synchronous reinforcement at all the positions of the 3D-printed S/C-CFRTP part are proposed. To determine a suitable printing process for the S/C-CFRTP part, a comprehensive comparison between the two methods was conducted through theoretical analysis and experimental verification, involving the printing mechanism, fiber content, impregnation percentage, and mechanical performance. The results indicated that the towpreg extrusion process was suitable for manufacturing the 3D-printed S/C-CFRTP part. Compared with the in situ impregnation process, the towpreg extrusion process led to a fiber content increase of approximately 7% and void rate reduction of approximately 6%, resulting in 19% and 20% increases in the tensile and flexural strengths of the 3D-printed S/C-CFRTPs, respectively. Additionally, an optimized process parameter setting for fabricating an S/C-CFRTP prepreg filament with excellent mechanical performance was proposed. The findings of this study can provide a new approach for further improving the mechanical performance of the 3D-printed advanced composites.

Experimental Investigation and Optimization of Blow Molding Process Parameters of HDPE Material

Abstract: Optimization of machining processes is essential for achieving higher productivity and high-quality products in order to remain competitive. The objective of this study is to optimize the process parameter of extrusion blow molding process of high density polyethylene (HDPE). In this paper three process parameters namely barrel temperature, Mandrel Position, Screw Rotation. Taguchi Method is a statistical method to improve the process parameters and improve the quality of components that are manufactured. ANOVA has been carried out to identify importance of the operating parameters on the performance characteristics considered. Further the verification experiment has been carried out to confirm the performance of optimum parameters. The results from this study will be useful for selecting appropriate set of process parameters to epoxy coating has been selected. The analysis of variance (ANOVA) has been used to determine effect of each parameter on wear rate so Finally, the confirmation test has been carried out to compare the predicted value of wear rate with the experimental value.

Multi-objective robust parameter optimization using the extended and weighted k-means (EWK-means) clustering in laser powder bed fusion (LPBF)

Metal additive manufacturing (AM) technology, especially laser powder bed fusion (LPBF), has received abundant interest from industries and the research community. Process optimization methods have thus multiplied to improve the overall quality of the final parts. However, little attention has been given to the quality repeatability issue. This paper proposes a novel multi-objective robust parameter optimization framework to explore optimal process parameters with respect to relative density and dimensional accuracy of LPBF-fabricated parts. Specifically, a modified k-means clustering, named the Extended and Weighted K-means (EWK-means), was constructed to simultaneously optimize the mean and the variance of the multiple responses. Experiments were conducted to verify the effectiveness of the proposed optimization framework. In addition, the effects of the process parameters, environment-related parameters, and physical properties on the hardness of the parts were analyzed using several machine learning models. The results showed that the proposed method achieved a set of optimal process parameters with better quality and satisfactory variability in the printed parts compared with other robust parameter optimization methods.

Effects of Powder Characteristics and Chemical Composition on the Properties of 25Cr7Ni Stainless Steel Fabricated by Laser-Powder Bed Fusion and Evaluation of Process Simulation

The 25Cr7Ni stainless steel alloy system is gaining increasing interest in the oil and gas industry because of its combination of high strength and corrosion resistance properties. However, very few studies on the effects of starting powder attributes and chemical composition on the as-printed properties of 25Cr7Ni stainless steel fabricated through laser-powder bed fusion (L-PBF) exist in the literature. This study examined the influence of powder attributes and chemical composition on the samples from gas atomized and water atomized 25Cr7Ni stainless steel powders, fabricated through L-PBF, on their as-printed microstructure and properties. The mechanical properties that were examined included ultimate tensile strength (UTS), elongation (%), and hardness. The corrosion behavior was also studied using linear sweep voltammetry in 3.5 wt.% NaCl solution. The evolved phases were characterized using optical and scanning electron microscopy, as well as through X-ray diffraction. The gas atomized powders, with their spherical and uniform morphology, yielded as-printed parts of higher relative densities when compared to water atomized powders, with irregular morphology due to better powder bed compaction. The higher densification obtained in the L-PBF samples from gas atomized powders translated into the highest UTS, hardness, and yield strength among the L-PBF samples from water atomized powders and wrought–annealed 25Cr7Ni stainless steel. The presence of higher amounts of N and Mn in the chemical composition of the gas atomized powders over water atomized powders promoted the presence of retained austenite in the corresponding L-PBF samples. Higher amounts of Mo, combined with austenite content, yielded a higher corrosion resistance in the L-PBF samples from the gas atomized powder than in the L-PBF samples from the water atomized powders. The latter part of the work is focused on the evaluation of simulation parameters for analyzing the fabrication procedure for the L-PBF process using Simufact software. For a given set of process parameters, Simufact provides the distortion and internal stresses developed in the printed parts as output. The present study sought to evaluate the process simulation by comparing the experimental observations in terms of the part distortion achieved in a stainless steel cube fabricated through L-PBF with Simufact process simulation obtained using the same set of process parameters.

Dimensional Accuracy of 3D Printed Dog-bone Tensile Samples: A Case Study

Three-dimensional (3D) printing technology has revolutionized manufacturing by enabling the rapid production of complex objects. However, ensuring dimensional accuracy in 3D printed parts remains a significant challenge due to various factors, including the selection of appropriate parameters during the Fused Deposition Modeling (FDM) process. Achieving dimensional accuracy is crucial in determining the reliability of a printing machine to produce objects that meet the expected results. This study aims to investigate the influence of FDM parameters (filling percentage and layer thickness) on the final dimensions of 3D printed parts made from polylactic acid (PLA) through a systematic experimental and statistical approach. The goal is to identify the optimal process parameter settings that minimize the error percentage in the dimensions of the printed parts using the Taguchi method. Overall higher dimensional accuracy was obtained, influenced mainly by the layer thickness parameter (in the case of Y direction dimensions) and by the filling percentage (in the case of Z direction dimensions – corresponding to sample thickness). The findings of this study provide valuable insight into identifying the optimal configuration for producing PLA 3D-printed components.

Optimization of Selective Laser Sintering Three-Dimensional Printing of Thermoplastic Polyurethane Elastomer: A Statistical Approach

This research addresses the challenge of determining the optimal parameters for the selective laser sintering (SLS) process using thermoplastic polyurethane elastomer (TPU) flexa black powder to achieve high-quality SLS parts. This study focuses on two key printing process parameters, namely layer thickness and the laser power ratio, and evaluates their impact on four output responses: density, hardness, modulus of elasticity, and time required to produce the parts. The primary impacts and correlations of the input factors on the output responses are evaluated using response surface methodology (RSM). A particular response optimizer is used to find the optimal settings of input variables. Additionally, the rationality of the model is verified through an analysis of variance (ANOVA). The research identifies the optimal combination of process parameters as follows: a 0.11 mm layer thickness and a 1.00 laser power ratio. The corresponding predicted values of the four responses are 152.63 min, 96.96 Shore-A, 2.09 MPa, and 1.12 g/cm3 for printing time, hardness, modulus of elasticity, and density, respectively. These responses demonstrate a compatibility of 66.70% with the objective function. An experimental validation of the predicted values was conducted and the actual values obtained for printing time, hardness, modulus of elasticity, and density at the predicted input process parameters are 159.837 min, 100 Shore-A, 2.17 MPa, and 1.153 g/cm3, respectively. The errors between the predicted and experimental values for each response (time, hardness, modulus of elasticity, and density) were found to be 4.51%, 3.04%, 3.69%, and 2.69%, respectively. These errors are all below 5%, indicating the adequacy of the model. This study also comprehensively describes the influence of process parameters on the responses, which can be helpful for researchers and industry practitioners in setting process parameters of similar SLS operations.