Experimental study of surface roughness, dimensional accuracy and time of fabrication of parts produced by fused deposition modelling

2020 ◽  
Vol 26 (9) ◽  
pp. 1535-1554
Author(s):  
Swapnil Vyavahare ◽  
Shailendra Kumar ◽  
Deepak Panghal
Keyword(s):  
Experimental Study ◽  
Surface Roughness ◽  
Layer Thickness ◽  
Process Parameters ◽  
Dimensional Accuracy ◽  
Fused Deposition Modelling ◽  
Content Type ◽  
Build Orientation ◽  
Fused Deposition ◽  
Significant Process

Purpose This paper aims to focus on an experimental study of surface roughness, dimensional accuracy and time of fabrication of parts produced by fused deposition modelling (FDM) technique of additive manufacturing. The fabricated parts of acrylonitrile butadiene styrene (ABS) material have pyramidal and conical features. Influence of five process parameters of FDM, namely, layer thickness, wall print speed, build orientation, wall thickness and extrusion temperature is studied on response characteristics. Furthermore, regression models for responses are developed and significant process parameters are optimized. Design/methodology/approach Comprehensive experimental study is performed using response surface methodology. Analysis of variance is used to investigate the influence of process parameters on surface roughness, dimensional accuracy and time of fabrication in both outer pyramidal and inner conical regions of part. Furthermore, a multi-response optimization using desirability function is performed to minimize surface roughness, improve dimensional accuracy and minimize time of fabrication of parts. Findings It is found that layer thickness and build orientation are significant process parameters for surface roughness of parts. Surface roughness increases with increase in layer thickness, while it decreases initially and then increases with increase in build orientation. Layer thickness, wall print speed and build orientation are significant process parameters for dimensional accuracy of FDM parts. For the time of fabrication, layer thickness and build orientation are found as significant process parameters. Based on the analysis, statistical non-linear quadratic models are developed to predict surface roughness, dimensional accuracy and time of fabrication. Optimization of process parameters is also performed using desirability function. Research limitations/implications The present study is restricted to the parts of ABS material with pyramidal and conical features only fabricated on FDM machine with delta configuration. Originality/value From the critical review of literature it is found that some researchers have made to study the influence of few process parameters on surface roughness, dimensional accuracy and time of fabrication of simple geometrical parts. Also, regression models and optimization of process parameters has been performed for simple parts. The present work is focussed on studying all these aspects in complicated geometrical parts with pyramidal and conical features.

Effect of process parameters on flexural strength and surface roughness in fused deposition modeling of PC-ABS material

2021 ◽  
pp. 251659842110311
Author(s):  
Shrikrishna Pawar ◽  
Dhananjay Dolas1
Keyword(s):  
Surface Roughness ◽  
Flexural Strength ◽  
Response Surface ◽  
Layer Thickness ◽  
Process Parameters ◽  
Surface Finish ◽  
Fused Deposition Modeling ◽  
Build Orientation ◽  
Fused Deposition ◽  
Deposition Modeling

Fused deposition modeling (FDM) is one of the most commonly used additive manufacturing (AM) technologies, which has found application in industries to meet the challenges of design modifications without significant cost increase and time delays. Process parameters largely affect the quality characteristics of AM parts, such as mechanical strength and surface finish. This article aims to optimize the parameters for enhancing flexural strength and surface finish of FDM parts. A total of 18 test specimens of polycarbonate (PC)-ABS (acrylonitrile–butadiene–styrene) material are printed to analyze the effect of process parameters, viz. layer thickness, build orientation, and infill density on flexural strength and surface finish. Empirical models relating process parameters with responses have been developed by using response surface regression and further analyzed by analysis of variance. Main effect plots and interaction plots are drawn to study the individual and combined effect of process parameters on output variables. Response surface methodology was employed to predict the results of flexural strength 48.2910 MPa and surface roughness 3.5826 µm with an optimal setting of parameters of 0.14-mm layer thickness and 100% infill density along with horizontal build orientation. Experimental results confirm infill density and build orientation as highly significant parameters for impacting flexural strength and surface roughness, respectively.

Multi-objective optimization of dimensional accuracy, surface roughness and hardness of hybrid investment cast components

2017 ◽  
Vol 23 (5) ◽  
pp. 845-857 ◽  
Author(s):  
Parlad Kumar Garg ◽  
Rupinder Singh ◽  
IPS Ahuja
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Surface Finish ◽  
Dimensional Accuracy ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Fused Deposition ◽  
Taguchi Design Of Experiments ◽  
Investment Cast

Purpose The purpose of this paper is to optimize the process parameters to obtain the best dimensional accuracy, surface finish and hardness of the castings produced by using fused deposition modeling (FDM)-based patterns in investment casting (IC). Design/methodology/approach In this paper, hip implants have been prepared by using plastic patterns in IC process. Taguchi design of experiments has been used to study the effect of six different input process parameters on the dimensional deviation, surface roughness and hardness of the implants. Analysis of variance has been used to find the effect of each input factor on the output. Multi-objective optimization has been done to find the combined best values of output. Findings The results proved that the FDM patterns can be used successfully in IC. A wax coating on the FDM patterns improves the surface finish and dimensional accuracy. The improved dimensional accuracy, surface finish and hardness have been achieved simultaneously through multi-objective optimization. Research limitations/implications A thin layer of wax is used on the plastic patterns. The effect of thickness of the layer has not been considered. Further research is needed to study the effect of the thickness of the wax layer. Practical implications The results obtained by the study would be helpful in making decisions regarding machining and/or coating on the parts produced by this process. Originality/value In this paper, multi-objective optimization of dimensional accuracy, surface roughness and hardness of hybrid investment cast components has been performed.

scholarly journals Multi-Response Optimization of Process Parameter in Fused Deposition Modelling by Response Surface Methodology

2019 ◽  
Vol 8 (3) ◽  
pp. 327-338 ◽  
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Ambient Temperature ◽  
Response Surface ◽  
Layer Thickness ◽  
Dimensional Accuracy ◽  
Fused Deposition Modelling ◽  
Cross Sectional ◽  
Factors Affecting ◽  
Fused Deposition

This paper reported on the effect of ambient temperature, layer thickness, and part angle on the surface roughness and dimensional accuracy. The response surface methodology (RSM) was employed by using historical data in the experiment to determine the significant factors and their interactions on the fused deposition modelling (FDM) performance. Three controllable variables namely ambient temperature (30 °C, 45 °C, 60 °C), layer thickness (0.178 mm, 0.267 mm, 0.356 mm) and part angle (22.5°, 45°, 67.5°) have been studied. A total of 29 numbers of experiments had been conducted, including two replications at the center point. The results showed that all the parameter variables have significant effects on the part surface roughness and dimensional accuracy. Layer thickness is the most dominant factors affecting surface roughness. Meanwhile, the ambient temperature was the most dominant in determining part dimensional accuracy. The responses of various factors had been illustrated in the cross-sectional sample analysis. The optimum parameter required for minimum surface roughness and dimensional accuracy was at ambient temperature 30 °C, layer thickness 0.18 mm and part angle 67.38°. The optimization has produced maximum productivity with RaH 3.21 µm, RaV 11.78 µm, and RaS 12.79 µm. Meanwhile, dimensional accuracy height eror 3.21%, width error 3.70% and angle 0.38°

An experimental methodology to analyse the structural behaviour of FDM parts with variable process parameters

2020 ◽  
Vol 26 (9) ◽  
pp. 1615-1625
Author(s):  
Steffany N. Cerda-Avila ◽  
Hugo Iván Medellín-Castillo ◽  
Theodore Lim
Keyword(s):  
Process Parameters ◽  
Numerical Models ◽  
Experimental Methodology ◽  
Machine Learning Techniques ◽  
Uniaxial Tensile ◽  
Fused Deposition Modelling ◽  
Structural Behaviour ◽  
Content Type ◽  
Build Orientation ◽  
Fused Deposition

Purpose This paper aims to investigate the structural behaviour of polylactic acid (PLA) parts fabricated by fused deposition modelling (FDM) to support the development of analytical and numerical models to predict the structural performance of FDM components and categories of similar additive manufactured parts. Design/methodology/approach A new methodology based on uniaxial tensile tests of filaments and FDM specimens, infill measurement and normalization of the results is proposed and implemented. A total of 396 specimens made of PLA were evaluated by using variable process parameters. Findings The infill and the build orientation have a large influence on the elastic modulus and ultimate tensile stress, whereas the layer thickness and the infill pattern have a low influence on these properties. The elongation at break is not influenced by the process parameters except by the build orientation. Furthermore, the infill values measured on the test specimens differ from the nominal values provided by the system. Research limitations/implications The analysis of the structural properties of FDM samples is limited to uniaxial loading conditions. Practical implications The obtained results are valuable for the structural analysis and numerical simulation of FDM components and for potential studies using machine learning techniques to predict the structural response of FDM parts. Originality/value A new experimental methodology that considers the measurement of the real infill percentage and the normalization of the results for inter-comparison with other studies is proposed. Moreover, a new set of experimental results of FDM-PLA parts is presented and extends the existing results in the literature.

Effect of fused deposition modelling process parameters on mechanical properties of 3D printed parts

2019 ◽  
Vol 16 (4) ◽  
pp. 550-559 ◽  
Author(s):  
Abhinav Chadha ◽  
Mir Irfan Ul Haq ◽  
Ankush Raina ◽  
Rana Ratna Singh ◽  
Narendra Babu Penumarti ◽  
...  
Keyword(s):  
Tensile Strength ◽  
Flexural Strength ◽  
Layer Thickness ◽  
Process Parameters ◽  
Fused Deposition Modelling ◽  
Content Type ◽  
Fused Deposition ◽  
Primary Layer ◽  
Bed Temperature ◽  
3D Printed

Purpose This paper aims to explore the effect of bed temperature, primary layer thickness and infill pattern (rectilinear, honeycomb, triangular) on the mechanical properties of tensile strength and bending strength of 3D printed parts. Design/methodology/approach Samples in accordance to various ASTM standards were printed by fused deposition modelling (FDM) method by varying the various input paramaters such as bed temperature, primary layer thickness and infill pattern (rectilinear, honeycomb, triangular). Tensile and bending testing was carried out on the printed parts, and post to the testing, fractography has been carried out using scanning electron microscope. Findings With increase in bed temperature tensile strength and flexural strength first increases then decreases. With the increase in primary layer thickness, tensile strength and flexural strength increase. With regard to infill patterns, triangular and honeycomb exhibit better tensile strength and better flexural strength. Practical implications The 3D printing is increasingly becoming important for manufacturing of engineering parts, determining the process parameters which could result in better mechanical and physical properties shall certainly help designers and manufacturers globally. Originality/value This work elucidates the effect of various process parameters of FDM on tensile and flexural properties of the samples.

Effect of cold vapour treatment on geometric accuracy of fused deposition modelling parts

2017 ◽  
Vol 23 (6) ◽  
pp. 1226-1236 ◽  
Author(s):  
Ashu Garg ◽  
Anirban Bhattacharya ◽  
Ajay Batish
Keyword(s):  
Surface Roughness ◽  
Surface Finish ◽  
Fused Deposition Modelling ◽  
Curved Surfaces ◽  
Geometric Accuracy ◽  
Content Type ◽  
Fused Deposition ◽  
Cold Vapour ◽  
Side Face ◽  
Functional Components

Purpose The purpose of this paper is to investigate the influence of low-cost chemical vapour treatment process on geometric accuracy and surface roughness of different curved and freeform surfaces of fused deposition modelling (FDM) specimens build at different part building orientations. Design/methodology/approach Parts with different primitive and curved surfaces are designed and modelled to build at three different part orientations along X orientation (vertical position resting on side face), Y orientation (horizontal position resting on base) and Z orientation (upright position). Later, the parts are post-processed by cold vapours of acetone. Geometric accuracy and surface roughness are measured both before and after the chemical treatment to investigate the change in geometric accuracy, surface roughness of FDM parts. Findings The results indicate that surface roughness is reduced immensely after cold vapour treatment with minimum variation in geometric accuracy of parts. Parts build vertically over its side face (X orientation) provides the overall better surface finish and geometric accuracy. Originality/value The present study provides an approach of post-built treatment for FDM parts and observes a significant improvement in surface finish of the components. The present approach of post-built treatment can be adopted to enhance the surface quality as well as to achieve desired geometric accuracy for different primitive, freeform/curved surfaces of FDM samples suitable for functional components as well as prototypes.

Parametric optimization of fused deposition modelling process using Grey based Taguchi and TOPSIS methods for an automotive component

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sakthivel Murugan R. ◽  
Vinodh S.
Keyword(s):  
Taguchi Method ◽  
Process Parameters ◽  
Parametric Optimization ◽  
Multiple Objective ◽  
Fused Deposition Modelling ◽  
Automotive Component ◽  
Content Type ◽  
Fused Deposition ◽  
Relative Closeness ◽  
Ranking Order

Purpose This paper aims to optimize the process parameters of the fused deposition modelling (FDM) process using the Grey-based Taguchi method and the results to be verified based on a technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) calculation. Design/methodology/approach The optimization of process parameters is gaining a potential role to develop robust products. In this context, this paper presents the parametric optimization of the FDM process using Grey-based Taguchi, TOPSIS and AHP method. The effect of slice height (SH), part fill style (PFS) and build orientation (BO) are investigated with the response parameters machining time, surface roughness and hardness (HD). Multiple objective optimizations were performed with weights of w1 = 60%, w2 = 20% and w3 = 20%. The significance of the process parameters over response parameters is identified through analysis of variance (ANOVA). Comparisons are made in terms of rank order with respect to grey relation grade (GRG), relative closeness and AHP index values. Response table, percentage contributions of process parameters for both GRG and TOPSIS evaluation are done. Findings The optimum factor levels are identified using GRG via the Grey Taguchi method and TOPSIS via relative closeness values. The optimized factor levels are SH (0.013 in), PFS (solid) and BO (45°) using GRG and SH (0.013 in), PFS (sparse-low density) and BO (45°) using TOPSIS relative closeness value. SH has higher significance in both Grey relational analysis and TOPSIS which were analysed using ANOVA. Research limitations/implications In this research, the multiple objective optimizations were done on an automotive component using GRG, TOPSIS and AHP which showed a 27% similarity in their ranking order among the experiments. In the future, other advanced optimization techniques will be applied to further improve the similarity in ranking order. Practical implications The study presents the case of an automotive component, which illustrates practical relevance. Originality/value In several research studies, optimization was done on the standard test specimens but not on a real-time component. Here, the multiple objective optimizations were applied to a case automotive component using Grey-based Taguchi and verified with TOPSIS. Hence, an effort has been taken to find optimum process parameters on FDM, for achieving smooth, hardened automotive components with enhanced printing time. The component can be explored as a replacement for the existing product.

Investigations for partial denture casting by fused deposition modelling-assisted chemical vapour smoothing

2020 ◽  
Vol 40 (5) ◽  
pp. 745-754
Author(s):  
Gurpartap Singh ◽  
Rupinder Singh ◽  
S.S. Bal
Keyword(s):  
Ph Value ◽  
Low Cost ◽  
Chemical Vapour ◽  
Dimensional Accuracy ◽  
Acrylonitrile Butadiene Styrene ◽  
Fused Deposition Modelling ◽  
View Point ◽  
Content Type ◽  
Fused Deposition ◽  
Set Up

Purpose The purpose of this study is to investigate dimensional accuracy (Δd), surface roughness (Ra) and micro hardness (HV) of partial dentures (PD) prepared with synergic combination of fused deposition modelling (FDM) assisted chemical vapour smoothing (CVS) patterns and conventional dental casting (DC) from multi-factor optimization view point. Design/methodology/approach The master pattern for PD was prepared with acrylonitrile butadiene styrene (ABS) thermoplastic on FDM set-up (one of the low cost additive manufacturing process) followed by CVS process. The final PD as functional prototypes was casted with nickel–chromium-based (Ni-Cr) alloy by varying Ni% (Z). The other input parameters were powder to water ratio P/W (X) and pH value (Y) of water used. Findings The results of this study suggest that for controlling the Δd and Ra of the PD, most important factor is X, followed by Z. For hardness of PD, the most important factor is Z. But from overall optimization viewpoint, the best settings are X-100/12, Y-10 and Z-61% (in Ni-Cr alloy). Further, based upon X-bar chart (for HV), the FDM-assisted DC process used for preparation of PD is statistically controlled. Originality/value This study highlights that PD prepared with X-100/12, Y-10 and Z-61% gives overall better results from multi-factor optimization view point. Finally, X-bar chart has been plotted to understand the statistical nature of the synergic combination of FDM, CVS and DC.

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