Fused Deposition Modeling Process Parameters Research Articles

Optimization and experimental analysis of mechanical properties and porosity on FDM based 3D printed ABS sample

A basic thermoplastic used in Fused Deposition Modeling (FDM) additive manufacturing methods is acrylonitrile–butadiene–styrene (ABS). However, the mechanical qualities of ABS components may be regulated by their porosity. This study aims to optimize the FDM process parameters to minimize porosity and increase ABS parts' tensile and compressive strengths. The experiment has been designed based on Taguchi's philosophy. The machining parameters have been considered as Extrusion multiplier, Temperature (oC), and Layer thickness (mm). The machining output has been analyzed using the mean effect plot. Furthermore, a hybrid optimization called grey relational analysis (GRA) and genetic algorithm (GA) is used to obtain the optimum parameter setting. the multi-optimization parameter setting is achieved as extrusion multiplier = 1, temperature = 240 °C, and layer thickness = 0.1 mm. The confirmation is also conducted to verify the optimum parameter setting. The findings showed that the suggested approach effectively enhanced the FDM process parameters for ABS components, leading to better mechanical characteristics and decreased porosity.

Improvement of tensile strength of fused deposition modelling (FDM) part using artificial neural network and genetic algorithm techniques

PurposeThis paper presents an experimental investigation in establishing the relationship between FDM process parameters and tensile strength of polycarbonate (PC) samples using the I-Optimal design.Design/methodology/approachI-optimal design methodology is used to plan the experiments by means of Minitab-17.1 software. Samples are manufactured using Stratsys FDM 400mc and tested as per ISO standards. Additionally, an artificial neural network model was developed and compared to the regression model in order to select an appropriate model for optimisation. Finally, the genetic algorithm (GA) solver is executed for improvement of tensile strength of FDM built PC components.FindingsThis study demonstrates that the selected process parameters (raster angle, raster to raster air gap, build orientation about Y axis and the number of contours) had significant effect on tensile strength with raster angle being the most influential factor. Increasing the build orientation about Y axis produced specimens with compact structures that resulted in improved fracture resistance.Research limitations/implicationsThe fitted regression model has a p-value less than 0.05 which suggests that the model terms significantly represent the tensile strength of PC samples. Further, from the normal probability plot it was found that the residuals follow a straight line, thus the developed model provides adequate predictions. Furthermore, from the validation runs, a close agreement between the predicted and actual values was seen along the reference line which further supports satisfactory model predictions.Practical implicationsThis study successfully investigated the effects of the selected process parameters - raster angle, raster to raster air gap, build orientation about Y axis and the number of contours - on tensile strength of PC samples utilising the I-optimal design and ANOVA. In addition, for prediction of the part strength, regression and ANN models were developed. The selected ANN model was optimised using the GA-solver for determination of optimal parameter settings.Originality/valueThe proposed ANN-GA approach is more appropriate to establish the non-linear relationship between the selected process parameters and tensile strength. Further, the proposed ANN-GA methodology can assist in manufacture of various industrial products with Nylon, polyethylene terephthalate glycol (PETG) and PET as new 3DP materials.

Research Status of and Prospects for 3D Printing for Continuous Fiber-Reinforced Thermoplastic Composites.

Continuous fiber-reinforced thermoplastic composites (CFRTPCs) have advantages such as high specific strength, high specific modulus, corrosion resistance, and recyclability and are widely used in the fields of aerospace, rail transit, new energy, and so on. However, traditional methods for preparing CFRTPCs, such as placement and molding, rely more on forming molds, resulting in high manufacturing costs and a slow response speed, which limits the promotion and application of the new generation of CFRTPCs with complex configurations and designable performance. Three-dimensional printing can efficiently create products with multiple materials, complex structures, and integrated functions, introducing new ways and opportunities for the manufacturing of CFRTPCs. However, poor mechanical properties are the bottleneck problem in achieving 3D printing of CFRTPCs. This paper summarizes the research status of the fused deposition modeling (FDM) 3D printing process and the corresponding mechanical properties of CFRTPCs. The focus is on analyzing the influences of the FDM process parameters, such as the material type, printing temperature, speed parameters, layer thickness, scanning space, stacking direction, and fiber volume content, on the mechanical properties of CFRTPCs. Finally, the main problems and future prospects of current CFRTPCs-FDM are analyzed and forecasted, providing new references and ideas for 3D printing of high-performance CFRTPCs.

Experimental investigation and Taguchi optimization of FDM process parameters for the enhancement of tensile properties of Bi-layered printed PLA-ABS

Additive manufacturing (AM) technology has gained significant popularity, among which Fused Deposition Modeling (FDM) has emerged as the predominant technique for 3D printing. FDM offers the unique ability to achieve the desired and tailored engineering properties required for specific applications. This experimental study investigates the influence of varying FDM process parameters on the mechanical properties and highlights the optimal set of parameters for better tensile strength for a bi-layered composite of PLA-ABS (polylactic acid and acrylonitrile butadiene styrene). Also, it investigates the most-to-least influential printing parameters. Four process parameters were played out i.e., Infill density (50%, 75%, and 100%), number of layers (20,25 and 30), printing speed (20 mm sec−1, 40 mm sec−1, and 60 mm sec−1), and bed temperature (90 °C, 95 °C, and 100 °C), while keeping other parameters constant. Taguchi optimization technique was used for optimization and experiments were designed according to Taguchi orthogonal array L9 (3 4). After printing, the samples were evaluated for tensile properties and the results were analyzed. It is found that the infill density is the most influential parameter while bed temperature is the least influential. Infill density of 75%, 30 layers per part, a printing speed of 20 mm sec−1, and a bed temperature of 100 °C are the optimal set of parameters for better tensile strength. Alongside, percent elongation, printing time, and strength-to-weight ratio were also analyzed and correlated.

Analyzing Surface Roughness Variations in Material Extrusion Additive Manufacturing of Nylon Carbon Fiber Composites.

In recent years, fused deposition modeling (FDM) based on material extrusion additive manufacturing technology has become widely accepted as a cost-effective method for fabricating engineering components with net-shapes. However, the limited exploration of the influence of FDM process parameters on surface roughness parameters, i.e., Ra (average surface roughness), Rq (root mean square surface roughness), and Rz (maximum height of the profile) across different sides (bottom, top, and walls) poses a challenge for the fabrication of functional parts. This research aims to bridge the knowledge gap by analyzing surface roughness under various process parameters and optimizing it for nylon carbon fiber printed parts. A definitive screening design (DSD) was employed for experimental runs. The Pareto chart highlighted the significant effects of layer height, part orientation, and infill density on all surface roughness parameters and respective sides. The surface morphology was analyzed through optical microscopy. Multi-response optimization was performed using an integrated approach of composited desirability function and entropy. The findings of the present study hold significant industrial applications, enhancing the quality and performance of 3D printed parts. From intricate prototypes to durable automotive components, the optimized surfaces contribute to production of functional and visually appealing products across various sectors.

Optimization of polylactic acid 3D printing parameters based on support vector regression and cuckoo search

Abstract3D printing, also known as additive manufacturing (AM), is evolving from a rapid prototyping tool to a pillar of the Industry 4.0 revolution and widely used in various industries, since it can quickly and efficiently create workpieces with complex structures and integrated functions. After analyzing the 3D printing principle of fused deposition modeling (FDM), this paper proposes a deformation control‐oriented optimization method for process parameters of FDM of the polylactic acid (PLA) materials, based on support vector regression (SVR) and cuckoo search (CS). First, FDM printing principle and its main process parameters were analyzed. Two key parameters, printing temperature and printing speed, were selected for research, with the maximum shrinkage deformation as the workpiece contour accuracy index. Combining Latin Hypercube Sampling (LHS) with Finite Element Analysis (FEA), finite sample sets were generated. Second, learning from the sample data, the SVR surrogate model was built to predict the workpiece contour accuracy, and the nonlinear relationship between FDM process parameters and PLA shrinkage deformation was obtained. Finally, taking the combination of printing temperature and speed as the design variable and minimizing the maximum shrinkage deformation as the optimization objective, the FDM process parameters optimization model was established, and CS was used to search for the optimal parameters combination. Experimental comparison showed that the FEA results and SVR model in this method are correct and effective, and the PLA workpiece shrinkage deformation is smaller under the optimal parameters combination, which effectively improves the shape accuracy of FDM workpieces.Highlights Combining support vector regression (SVR) and cuckoo search (CS) can optimize polymer 3D printing process parameters. Effective finite element model was built for polymer 3D printing. SVR model established by simulation data can predict workpiece deformation. The optimal process parameters were found using CS algorithm.

A review on the melt extrusion-based fused deposition modeling (FDM): background, materials, process parameters and military applications

AbstractThe contemporary military sector needs a tailor-made product at a low cost and time. Fused Deposition Modeling (FDM) is a melt extrusion-based Additive Manufacturing technology for processing thermoplastics, composites, and biomaterials. FDM is competent in fabricating complex parts in different industries, including military, aerospace, automotive, biomedical, and jewellery. The FDM can process various materials and is ideal for fabrication prototypes, functional parts, visualization, concept proofs and fast product development. FDM is currently used in the military for novel components developments and maintenance, opening new logistics and supply chain management methods. Integrating sensors into weaponry for real-time physiological feedback and threat information is also possible. Additionally, FDM can fabricate trauma models for surgical planning and educating military surgeons. This paper presents the FDM background, filaments, and process parameters. Also, the work provides information to readers on the applications and possibilities of the FDM process from a military standpoint.

Understanding compressive viscoelastic properties of additively manufactured PLA for bone-mimetic scaffold design.

Bone tissue engineering has been recognized as a promising strategy to repair or replace damaged bone tissues. The mechanical properties of bone scaffolds play a critical role in successful bone regeneration, as it is essential to match the mechanical properties of the scaffold with the surrounding bone tissue. In this study, we investigated the effects of fused deposition modeling (FDM) process parameters, including printing speed, printing temperature, and layer thickness, on the compressive viscoelastic properties of polylactic acid (PLA) scaffolds. The compressive viscoelastic properties of bulk PLA specimens were characterized using a Zhu-Wang-Tang (ZWT) constitutive model under different compressive strain rates. A comprehensive statistical analysis comprising multivariate and univariate analysis of variance (MANOVA and ANOVA) and Tukey's post hoc analysis was utilized to quantify the effect of each FDM parameter on the viscoelastic mechanical properties of the PLA specimens. Subsequently, we fabricated modified face-centered cubic (MFCC) scaffolds using FDM and varied the FDM process parameters to achieve a compressive viscoelastic response that matched the natural trabecular bone tissue. The viscoelastic performance of the MFCC scaffolds was compared with traditional orthogonal cylindrical struts (OCS) scaffolds. Our methodology contributes to the design of bone-mimetic scaffolds with optimized mechanical properties by controlling FDM process parameters.

Wear prediction of 3D-printed acrylonitrile butadiene styrene-carbon nanotube nanocomposites at elevated temperatures

Abstract In this study, multi-wall carbon nanotube (MWCNT) reinforced acrylonitrile butadiene styrene (ABS) nanocomposite filaments are produced. Filaments are examined through thermogravimetric analysis (TGA) and definitive scanning calorimetry (DSC) analysis. Produced nanocomposite filaments are used in the fused deposition modeling (FDM) process to manufacture parts. Wear tests are conducted on 3D-printed parts using wear test apparatus with an attached heating module under different ambient temperatures. Hence, the influence of CNT reinforcement, along with different FDM process parameters and varying test conditions on the wear behavior of 3D-printed ABS-CNT parts, are examined. Worn surfaces of the specimens are examined by scanning electron microscopy (SEM). Nonlinear autoregressive exogenous (NARX) models are proposed for the prediction of the wear behavior of 3D-printed ABS-CNT nanocomposites. While wear rate is taken as output, ambient temperature and amount of nanofiller are accounted as input parameters along with the variation of coefficient of friction (COF) which is obtained from measured frictional force and three input-one output model structure is proposed for NARX. The use of multiple input-single output (MISO) model structure and examining the wear behavior of 3D-printed ABS-CNT samples under different wear test conditions with different FDM process parameters are the novelties in this work.

Multi-Objective Optimization of Fused Deposition Modeling for Mechanical Properties of Biopolymer Parts Using the Grey-Taguchi Method

The urgent need to develop customized functional products only possible by 3D printing had realized when faced with the unavailability of medical devices like surgical instruments during the coronavirus-19 disease and the on-demand necessity to perform surgery during space missions. Biopolymers have recently been the most appropriate option for fabricating surgical instruments via 3D printing in terms of cheaper and faster processing. Among all 3D printing techniques, fused deposition modelling (FDM) is a low-cost and more rapid printing technique. This article proposes the fabrication of surgical instruments, namely, forceps and hemostat using the fused deposition modeling (FDM) process. Excellent mechanical properties are the only indicator to judge the quality of the functional parts. The mechanical properties of FDM-processed parts depend on various process parameters. These parameters are layer height, infill pattern, top/bottom pattern, number of top/bottom layers, infill density, flow, number of shells, printing temperature, build plate temperature, printing speed, and fan speed. Tensile strength and modulus of elasticity are chosen as evaluation indexes to ascertain the mechanical properties of polylactic acid (PLA) parts printed by FDM. The experiments have performed through Taguchi's L27 orthogonal array (OA). Variance analysis (ANOVA) ascertains the significance of the process parameters and their percent contributions to the evaluation indexes. Finally, as a multi-objective optimization technique, grey relational analysis (GRA) obtains an optimal set of FDM process parameters to fabricate the best parts with comprehensive mechanical properties. Scanning electron microscopy (SEM) examines the types of defects and strong bonding between rasters. The proposed research ensures the successful fabrication of functional surgical tools with substantial ultimate tensile strength (42.6 MPa) and modulus of elasticity (3274 MPa).

Additive manufacturing of carbon nanotube/polylactic acid films with efficient electromagnetic interference shielding and electrical heating performance via fused deposition modeling

In the wake of developments in 5th generation mobile communication technology and Internet of Things, traditional electromagnetic interference (EMI) shielding materials are not satisfied with the booming demand of suppressing electromagnetic pollution. In view of the characteristics of low-cost, easy-operating and functional materials applicability of fused deposition modeling (FDM), in this work, a multifunctional carbon nanotube (CNT)/ polylactic acid (PLA) film with electromagnetic shielding and electric heating properties was prepared by using FDM process. The effects of CNT content, FDM-printed film thickness, and FDM process parameters on electromagnetic shielding performance were studied. The results indicate that the additions of CNT increase the EMI shielding performance by forming the conductive paths in the CNT/PLA FDM-printed films. The EMI shielding value of the 4 wt% CNT/PLA film with a thickness of 4 mm is 68 dB at 12.3Ghz. In addition, the improved electrical conductivity provides the good electric heating performance of the CNT/PLA film. At a safe voltage (16 V), the heating temperature of the 4 wt% and 8 wt% CNT/PLA films reached 67.8 °C and 139 °C, respectively. The good repeatability and stability of CNT/PLA films for electric heating were verified. The obtained CNT/PLA FDM-printed films have excellent electromagnetic shielding and low-voltage electric heating properties by adjusting the CNT contents and the FDM process parameters, which expands the application potential of EMI shielding materials and FDM technology.

Experimental investigation of process parameters in polyether ether ketone 3D printing

In the past two decades, polyether ether ketone (PEEK) has been vastly used in different industries such as automotive, aerospace, and medical sectors due to its mechanical strength, high heat stability, and excellent chemical resistance. Since this semi-crystalline polymer has a high melting temperature, the standard procedure to select extrusion-based 3D printing working parameters has many challenges to ensure each bespoke product with the best quality. Slight shift from optimum process parameters in fused deposition modeling (FDM) of PEEK has a remarkable impact on the final product quality. The present research addresses the long-standing problem of selecting a working setup quickly and accurately which is not dependent on the user's knowledge. In this article, to identify the best arrangement of FDM process parameters, an orthogonal matrix of Taguchi Design of Experiments (DoEs) is applied. Different values of bed, chamber, and nozzle temperatures, print speed, and layer thickness were thoroughly examined for the printing of standard tensile specimens. The mechanical properties and the fracture morphology of samples are examined in different printing conditions to explore a roadmap tool for designing better process parameters which satisfy mechanical requirements of products. In this study, the interpretation of the experimental results is investigated based on analysis of variance (ANOVA). The obtained results show that the best working set up for nozzle temperature, bed temperature, print speed, and layer thickness are 415°C, 160°C, 50 mm s−1, and 0.2 mm, respectively. This article consists of five sections. After introduction in the first section, the effects of working parameters on the strength of final fused products are investigated in Experimental setup section. The results and the confirmation test are considered in seperate sections, respectively. The research is summarized in the conclusion section.

Investigation of Fused Deposition Modelling Process Parameters in 3D Printing for Composite Material (Poly Lactic Acid and Banana Fibre)

Additive manufacturing is gaining popularity nowadays due to its applications in the automotive, medical, aerospace industries, and sports to manufacture complex parts. Fused deposition modelling is an additive manufacturing process utilised widely due to its lower cost, fast prototyping and faster production time. The present study focuses on applying FDM to the composite material filament and the impact of parameters of FDM on the part quality. A composite filament material was prepared to combine PLA (Poly-lactic Acid) and banana fibre. Specimens were prepared using this composite filament by varying various parameters such as layer thickness, infiltration and build orientation. Flexural and tensile tests were performed as per standards. It was found that the material properties considered are significantly affected by percentage infill and build orientation. The ‘on edge’ build orientation provides better material properties as compared to the other two orientations. The tensile strength is observed to be 73% and 77% more in flat orientation and ‘on edge’ orientation, respectively, as compared to upright orientation. Also, the flat orientation and ‘on edge’ orientation respectively showed 60% and 70% more flexural strength than the upright orientation.

Fused deposition modelling (FDM) process parameter optimization to minimize residual stresses of 3 d printed carbon fiber nylon 12 hip joint implant

AbstractResidual stresses induced during the layer‐by‐layer fabrication process affect mechanical properties and dimensional accuracy of additively manufactured components. Some of these effects cannot be corrected by post processing like heat treatment. This work aims at optimizing fused deposition modelling process parameters for the least residual stresses during 3D printing of carbon fiber reinforced nylon 12 hip implant. Taguchi design of experiment was used to study the effect of printing temperature, layer thickness and print speed on the residual stresses using the Digimat‐ additive manufacturing software. The results show that the optimal factor setting levels for minimizing part residual stresses were printing temperature of 255 °C, layer thickness of 0.3 mm, and a print speed of 50 mm/s. Printing temperature has the most significant influence on the residual stresses. The combination of the optimum parameter levels yielded the least simulation residual stresses of (41.75 6.53) MPa while the experimental residual stress results were (40.7 7.7) MPa. The simulated and experimental results agreed with minimal percentage difference of (2.51 0.04) %. Tensile and compressive properties of 3D printed carbon fiber nylon 12 composite hip implant matched those of cortical bone. The fracture surface of failed tensile specimens revealed that failure occurred through fiber pull‐out and matrix fracture

The Effect of Infill Pattern on Tensile Strength of PLA Material in Fused Deposition Modeling (FDM) Process

Fused deposition modeling (FDM) is an additive manufacturing (AM) process often used to build geometrically complex prototypes and parts. It is becoming more popular since it improves products by eliminating the need for high-priced equipment. Materials, printing methods, and printing variables all impact the mechanical characteristics of printed items. The process parameters of FDM affect the parts' quality and functionality. This study examines the influence of different infill patterns on test specimens made of polylactic acid (PLA) tensile strength. Total of 10 different infill patterns (IPs): Grid, Lines, Triangles, Tri-Hexagon, Cubic, Gyroid, Zig-zag, Concentric, Octet, and Cubic subdivision were taken as process variables. Samples were printed using processing parameters (speed 60 mm/s, layer height 0.1 mm, infill density 80%, extruded at 200◦C). The ASTM D638 tensile test was used to determine the tensile strength based on this printing parameter. According to tensile test results, the infill pattern significantly affects the tensile strength. The results showed that the concentric infill pattern has a higher tensile strength of 32.174 MPa, whereas the triangles infill pattern has a lower tensile strength of 20.934 MPa.

Optimisation of the additive manufacturing parameters of polylactic acid (PLA) cellular structures for biomedical applications

Fused deposition modelling (FDM) is an additive manufacturing technology used to create functional and complex geometries directly from computer-generated models. This technique can be utilised to generate cellular structures with controllable pore size, pore shape, and porosity. Cellular structures are fundamental in orthopaedics scaffolds because of its low elastic modulus, high compressive strength, and adequate cell accommodation spaces. This paper aims at investigating and optimising the FDM additive manufacturing process parameters of polylactic Acid (PLA) for two lattice structures namely Schoen Gyroid and Schwarz Primitive. The effect of additive manufacturing critical process parameters including layer height, flow rate, and print speed on the geometrical accuracy and compressive strength of the specimens were analysed. In addition, other parameters that have minimal effect on the geometrical accuracy of the printed parts were discussed. A Full Factorial Analysis (FFA) using Minitab software was undertaken to identify the perfect combination of printing parameters to provide the most geometrically accurate structure. In this study, samples of the Schoen Gyroid and the Schwarz Primitive lattices and a solid control cylinder were 3D printed using the ideal printing combination to assess the manufacturability, the geometrical accuracy, and the mechanical behaviour of both designs. It was found that the optimised FDM process parameters for the studied cellular structures were a layer height of 0.16 mm, a printing speed of 50 mm/s and a flow rate of 90%. As a result of using these parameters, the solid, Schoen Gyroid and Schwarz Primitive specimens demonstrated elastic moduli values of 951 MPa, 264 MPa, and 221 MPa, respectively. In addition, the Schoen Gyroid and the Schwarz Primitive have reached their stress limits at around 8.68 MPa and 7.06 MPa, respectively. It was noticed that the Schoen Gyroid structure exhibited ∼ 18% higher compressive strength and ∼ 16% higher elastic modulus compared to the Schwarz Primitive structure for the same volume fraction of porosity, overall dimensions, and the manufacturing process parameters. Although both structures revealed mechanical properties that fall within the range of the human trabecular bone, but Schoen Gyroid exhibited improved structural integrity performance that is evident by its post-yield behaviour.

A Comprehensive Review on the Optimization of the Fused Deposition Modeling Process Parameter for Better Tensile Strength of PLA-Printed Parts

Fused Deposition Modeling (FDM) is a kind of Additive Manufacturing technology, which can produce complex parts by adding layer-by-layer mold automatically from 3D computer-aided design (CAD) data. Although the FDM process has its obvious merits, a fundamental backward factor of its professional enterprise acceptance is the inadequacy of higher mechanical properties and heavy structure of the manufactured product. For that reason, the properties of the manufactured product by FDM are highly dependent upon the choice of FDM parameters. Several studies are investigated to look at the effect of various FDM process parameters to improve print quality characteristics such as mechanical properties, build time, dimensional accuracy, and surface finish of the manufactured parts with having convenient process parameter settings. However, the progress has been gradual and not well organized because of the complex attributes of the FDM process and conflicting process parameters. This paper aims to comprehensively summarize recent studies of advanced statistical and experimental design techniques for better tensile strength of polylactic acid (PLA)-printed parts, the effect of process parameters on tensile strength, and the existing work on the optimization of process parameters.

Tensile, three-point bending and impact strength of 3D printed parts using PLA and recycled PLA filaments: A statistical investigation

In this study, the Taguchi methodology was used to investigate the effects of Fused Deposition Modeling (FDM) production parameters tensile strength, three-point bending strength, and impact strength of three-dimensional (3D) printed polylactic acid (PLA) and recycled polylactic acid (Re-PLA) test parts. As FDM process parameters, filaments (PLA, Re-PLA), three different layer thicknesses (0.15–0.20–0.25 mm), occupancy rates (30%, 50% and 70%), and filling structure (Rectilinear) were determined in the experimental design. The FDM technique was used to print the test parts. The tensile, three-point bending, and impact strength of the test parts were determined using the ISO 527, ISO 180, and ISO 178 test standards, respectively. The results showed that layer thickness is the most efficient factor for improving tensile strength, three point bending strength, and impact strength rather than occupancy rate or filament materials. The optimum results were obtained in layer thickness (0.25 mm), occupancy rate (70%), and filament material (PLA), respectively. They were calculated to be as 60.006 MPa at tensile strength, 125.423 MPa at three-point bending strength, 16.961 kJ/m2 at izod impact strength. Also, Scanning Electron Microscopy (SEM) has been utilized to investigate the morphology and topography alterations in the fractured surface of test parts. The study demonstrates the possibility of 3DP with Re-PLA filament and environmental awareness was noted by using recycled filament. The study demonstrates the possibility of 3DP with Re-PLA filament and environmental awareness was noted by using recycled filament. The research shows that 3D printing with Re-PLA is feasible.

Parametric optimization of FDM using the ANN-based whale optimization algorithm

AbstractSurface roughness (SR) is one of the major parameters used to govern the quality of the fused deposition modeling (FDM)-printed products, and the FDM process parameters can be easily regulated in order to obtain a good surface finish. The surface quality of the product produced by the FDM is generally affected by the staircase effect that needs to be managed. Also, the production time (PT) to fabricate the product and volume percentage error (VPE) should be minimized to make the FDM process more efficient. The aim of this paper is to accomplish these three objectives with the use of the parametric optimization technique integrating the artificial neural network (ANN) and the whale optimization algorithm (WOA). The FDM parameters which have been taken into consideration are layer thickness, nozzle temperature, printing speed, and raster width. Experimentation has been conducted on printed samples to examine the impact of the input parameters on SR, VPE, and PT according to Taguchi's L27 orthogonal array. The ANN model has been built up using the experimental data, which was further used as an objective function in the WOA with an aim to minimize output responses. The robustness of the proposed method has been validated on the optimal combinations of FDM process parameters.

A grey‐based Taguchi method to optimize fused deposition modelling process parameters for manufacture of a hip joint implant

AbstractControlling process parameters to configure a component has long been regarded as a value‐added function of additive manufacturing. Factors that contribute to the quality of total hip prostheses are the degree of dimensional accuracy, surface finish, and manufacturing time. In this study, Digmat‐additive manufacturing software has been used for finite element analysis to determine the quality of a fused deposition modelling printed carbon fiber polyamide 12 composite hip joint implant. The influence of three process parameters namely, printing temperature, layer height, print speed together with interactions were investigated using Taguchi's orthogonal array. The grey relational Taguchi method was used to optimize the process parameters on the part deflection and build time. The results showed that a printing temperature of 255 °C, a high layer thickness of 0.3 mm, and a print speed of 50 mm/s were optimum settings for both responses. Experimental work was carried out and the results used to validate the finite element results which showed good agreement. Microstructural analyses and surface analysis of printed parts were performed using scanning electron microscopy. The results identified that the surface texture of the manufactured implant was rough within the acceptable range for better bone‐to‐implant contact.