Fused Deposition Modeling Machine Research Articles

Fabrication and Testing of Hybrid Polymer Composite Material by Using Carbon, Glass, Kevlar Fibers

Composites which made up of fiber reinforcements are universally endorsed option for the automobiles with a lightweight. Due to the unique properties of fiber-reinforced composites, it became a perfect alternative for traditionally used materials. Most of the automobile industries prefer polymer matrix fiber-reinforced composites for the reason that its light weight helps in carbon emission reduction and Additive manufacturing (AM) produces a complex shaped product from its data, layer by layer, with high precision and much less material wastage. As compared to the conventional manufacturing process, there are many positive environmental advantages of additive manufacturing technologies. Most importantly, there is less waste of raw material and the use of new and smart materials. In this work, we first focused on creating the composite material utilizing the Hand Lay-Up method with materials such as Carbon Fiber/Epoxy Composite with Copper Oxide (CuO) Nanoparticles and Banana Glass Fiber. Following that, we readied ASTMD638 specimens for both compressive and tensile testing. We created an ASTMD638 model for the investigation's tensile and compressive tests using Solid Works design program, and we then saved the design model in STL format. This STL format was uploaded into the CURA software for slicing. The slicing model was then saved into G-code format, and it was printed in a fused deposition modeling machine. Lastly, we tested both specimens using a compressive test setup in a Universal Testing Machine model (INSTRON-3369) UTM, and the results showed 3D printed files. Keywords: Glass Fiber, Banana Fiber, Carbon Fiber, Copper Oxide Nano filler, 3D printing Machine,Corbon Fiber Filament.

Numerical and experimental study of attenuation inspection during FDM with ultrasonic leaky waveguide

ABSTRACT This work proposes an ultrasonic leaky waveguide (ULWG) for in-situ structural integrity inspection during fused deposition modeling (FDM). Since the ultrasonic wave propagation speed (m·s−1) is much higher than the deposition speed (mm·s−1), a quasi-static finite element model is first established to simulate the wave propagation during this dynamic process. The amplitude and energy attenuation coefficients (α and ζ) are chosen as the inspection features. Processing parameters including deposition layer thickness and number, inspection frequency, plate thickness and interface impedance are explored. For the first layer printing, a thinner thickness, higher frequency and proper interface impedance will enable a better inspection with high sensitivity. For multilayer printing, the multimodal dispersion curves change continuously and α oscillation is observed due to waveform aliasing that ζ is more reliable. Printing failures such as detachment can be predicted as well from the model established. The ULWG is then integrated into a commercial FDM machine to capture the attenuation coefficients of an “S” shape sample. The poor adhesion, local and global detachments, path planning impact can all be revealed by ζ experimentally. Moreover, being consistent to the simulation, the fluctuation of α in multilayer printing increases, which prevents a further printing evaluation.

Numerical and experimental study of attenuation inspection during FDM with ultrasonic leaky waveguide

ABSTRACT This work proposes an ultrasonic leaky waveguide (ULWG) for in-situ structural integrity inspection during fused deposition modeling (FDM). Since the ultrasonic wave propagation speed (m·s−1) is much higher than the deposition speed (mm·s−1), a quasi-static finite element model is first established to simulate the wave propagation during this dynamic process. The amplitude and energy attenuation coefficients (α and ζ) are chosen as the inspection features. Processing parameters including deposition layer thickness and number, inspection frequency, plate thickness and interface impedance are explored. For the first layer printing, a thinner thickness, higher frequency and proper interface impedance will enable a better inspection with high sensitivity. For multilayer printing, the multimodal dispersion curves change continuously and α oscillation is observed due to waveform aliasing that ζ is more reliable. Printing failures such as detachment can be predicted as well from the model established. The ULWG is then integrated into a commercial FDM machine to capture the attenuation coefficients of an “S” shape sample. The poor adhesion, local and global detachments, path planning impact can all be revealed by ζ experimentally. Moreover, being consistent to the simulation, the fluctuation of α in multilayer printing increases, which prevents a further printing evaluation.

Optimizing time in additive manufacturing: a hybrid fused deposition modeling and photopolymerization approach

PurposeThis study aims to address the challenge of reducing the build time of a fused deposition modeling (FDM) system while maintaining part strength, proposing a hybrid technique combining photopolymerization and FDM.Design/methodology/approachFor developing the hybrid system, a standard FDM machine was modified to incorporate necessary components so that the whole system can be operated with a single interface; further, the samples were fabricated with conventional and modified process to evaluate the efficacy of the developed system, to determine the extent of time reduction that the proposed methodology can obtain, additionally different sort of 3D models were selected and their build time was compared.FindingsThe modified hybrid mechanism can successfully fabricate parts with a modified G-code. The simulation of the technique shows that a reduction of 34%–87% can be achieved for simpler models such as cube while a reduction ranging from 30.6%–87.8% was observed for complex models. An increase in strength of 6.58%, 11.51% and 37.32% was observed in X, Y and Z directions, along with a significant increase in toughness as compared with FDM parts for parts fabricated with the developed mechanism.Practical implicationsThe modified mechanism could be used for fast fabrication purposes, which could be very useful for serving situations such as emergency health care, rapid tooling.Originality/valueThis research contributes a novel hybrid technique for additive manufacturing, offering a substantial reduction in build time without compromising mechanical properties, even increasing them.

Effect of Fillers on Mechanical Properties of FDM printed PLA Components

Fused Deposition Modelling (FDM) is the most accessible additive technology nowadays, because it combines the low cost and simplicity of the machine with the low cost and availability of the thermoplastic polymers. This class of polymers are however limited and in order to increase the application range of the products, mixing polymeric matrix with various fillers can be a solution.The purpose of this study is to identify the effect of the functional fillers incorporated in PLA thermoplastic on the mechanical properties of the obtained components. In addition, the layer orientation in relation to the loading direction will be considered as a study variable. All samples were manufactured under the same conditions using the same FDM machine. The effect of carbon / glass fibers and bronze particle fillers on the PLA matrix in comparison with the pure PLA filament was evidenced by tensile and flexural testes. The results were then interpreted based on the two criteria: filler type and layer deposition in accordance to the loading direction. It was determined that regardless of the type of test (tensile or flexural), the mechanical behavior is strongly influenced by the type of filler in the matrix. The most ductile behavior was showed by the pure PLA samples, and the most brittle by the PLA reinforced with carbon fibers.

Micromechanical Models for FDM 3D-Printed Polymers: A Review.

Due to its large number of advantages compared to traditional subtractive manufacturing techniques, additive manufacturing (AM) has gained increasing attention and popularity. Among the most common AM techniques is fused filament fabrication (FFF), usually referred to by its trademarked name: fused deposition modeling (FDM). This is the most efficient technique for manufacturing physical three-dimensional thermoplastics, such that FDM machines are nowadays the most common. Regardless of the 3D-printing methodology, AM techniques involve layer-by-layer deposition. Generally, this layer-wise process introduces anisotropy into the produced parts. The manufacturing procedure creates parts possessing heterogeneities at the micro (usually up to 1 mm) and meso (mm to cm) length scales, such as voids and pores, whose size, shape, and spatial distribution are mainly influenced by the so-called printing process parameters. Therefore, it is crucial to investigate their influence on the mechanical properties of FDM 3D-printed parts. This review starts with the identification of the printing process parameters that are considered to affect the micromechanical composition of FDM 3D-printed polymers. In what follows, their (negative) influence is attributed to characteristic mechanical properties. The remainder of this work reviews the state of the art in geometrical, numerical, and experimental analyses of FDM-printed parts. Finally, conclusions are drawn for each of the aforementioned analyses in view of microstructural modeling.

Comparative study on the influence of tool path variation in Fused Deposition Modeling Machine

Additive Manufacturing is one of the recent advancements in the manufacturing sector. It is the process of making three- dimensional solid objects from digital data. Fused Deposition Modelling (FDM) is one of the most commonly known printing types where the material is extruded to print an entity in which feedstock material is pushed through an extruder. It is mainly used for thermoplastics and polymers. In this process, the product is built by printing the tensile specimen in the form of a layer over another layer. This study is based on the comparative analysis of printing ABS specimens in commercial printers (Ultimaker, Stratasys) and a new indigenous printer. The tool path for the new printer is generated manually by using coded data and compared with commercial printers. This paper titled “Comparative Study on the Influence of Tool Path Variation in Fused Deposition Modelling Machines” focuses on the material consumption and the change in production time by varying the raster angles. The time taken for the production and the material consumption by the newly designed printer is lesser than the time taken in the existing ones.

A Material-Recycling Unit for the Fused Deposition Modelling of Three-Dimensional Printing Systems

Fused deposition modelling (FDM) three-dimensional (3D) printing technology is one of the most common additive manufacturing (AM) technologies due to the relatively low cost of the printing units and materials. Although cost-effective, this technology is not conceived to convert 100% of the raw material into a complete product, creating a potential plastic waste problem. To recycle the plastic waste from the FDM machine into reusable filaments, the concept of a 3D printer material-recycling machine (3DP-MRM) was developed using CREO Parametric 9.0 software. A prototype with four systems, including a spooler system, extruder system, display system, and filament-positioning system, was manufactured in-house with complete run experiments. The tests of the 3DP-MRM were applied, and the machine worked successfully among all the designed functions with minor issues.

A hybrid mechanism-based and data-driven approach to forecast energy consumption of fused deposition modelling

Additive manufacturing (AM) has been recognized as a promising technology for achieving more secure and resilient supply chains to support social transitions to sustainable post-fossil carbon societies. AM is considered to be efficient and sustainable and its environmental impact is mainly from energy consumption. Therefore, it is of great significance to accurate predict and thus reduce the energy consumption of AM. However, current models to predict AM energy consumption are not sufficiently accurate. In this paper, a hybrid mechanism-based and data-driven approach is proposed to forecast the AM energy consumption. This approach accurately modelled the working time and power of each energy-consuming component of the FDM machine. Firstly, the physical model was used to establish the energy consumption prediction framework which documents the total energy into energy consumed by each component. Secondly, the data-driven method was leveraged via data fitting and deep learning to obtain the power and temporal model of the nozzle and the platform, considering their working states and interactions between them and the cooling fan. Thirdly, experimental measurements and G-code parsing were utilized to obtain data of the power model and the temporal model of the remaining components. In this work, the different types of parts were fabricated by the fused deposition modelling (FDM) printer and the energy consumption was measured and compared with the predicted values to verify the accuracy and effectiveness of the proposed method. Finally, the proposed method was compared with other methods to document the benefits of the proposed method. The results showed that the prediction accuracy of the proposed method for these four experiments was more than 94% accurate and it outperformed other methods. The proposed method can be used to guide process design to more accurately predict and thus reduce the energy consumption of AM parts during their manufacturing processes.

A comprehensive analysis and prediction of the effect of groove shape and volume fraction of multi-walled carbon nanotubes on the polymer 3D-printed parts in the friction stir welding process

Polymers have a wide application. Fused deposition modeling (FDM) is a ubiquitous additive manufacturing (AM) technique that enables producers to manufacture polymer parts in a cost-effective way. However, the bed size limitation in 3D printers restricts their applicability in a variety of industries; therefore, it seems essential to find a great approach to join 3D-printed parts. Friction stir welding (FSW) is an excellent solution to join 3D-printed parts to overcome bed size limitation. A friction welding joint is referred as interface, fusion, or bond and is a point or edge where two or more pieces are joined together by friction. In the first stage, the aim of this investigation is to study the effect of groove shape and volume fraction of the multi-wall carbon nanotube powder on the mechanical properties including angular distortion, tensile and flexural strength, and hardness as well as electrical properties of ABS parts manufactured by fused deposition modeling machine. Secondly, the impact of those parameters on tensile strength via two artificial neural networks (ANN and GMDH) was investigated. The results showed that not only greater tensile and flexural strength was achieved thanks to the carbon nanotube, but also hardness was improved. The lower amount of powder and square groove shape leads to greater tensile and flexural strength. The square groove shape and more volume fraction of MWCNTS also gave rise to lower angular distortion. The positive influence of adding MWCNTs on joining 3d-printed parts via FSW was not restricted to mechanical properties and adding only 4.16% of MWCNTs showed a significant increase in electrical properties. Finally, both ANN and GMDH have shown excellent results (R-value of 0.94 and 0.93 with the error of 8 and 20%, respectively) in predicting the tensile strength of welded specimens.

APPLICATION OF TAGUCHI METHOD TO OPTIMIZE FUSED DEPOSITION MODELING PROCESS PARAMETERS FOR SURFACE ROUGHNESS

Surface quality is one of the limiting aspects of additive manufacturing (AM). This paper presents the findings from a study to optimize Fused Deposition Modeling (FDM) process parameters to improve the surface roughness of the printed test specimen. Taguchi 3⁴ and L9 orthogonal array were used to design the experiment. Samples models of the same size were fabricated with an open source FDM printer using acrylonitrile butadiene styrene (ABS) material and were examined to see the structural differences. Taguchi method S/N ratio and means analysis was used to find the optimum process parameter for surface roughness. The results indicate that flow rate is the most influential process parameter towards better surface roughness, followed by layer height, printing temperature and print speed. The surface roughness of printed test specimen was found to be rougher with the increase in levels of flow rate. The flow rate is responsible for the unevenly aligned section of the deposited filament. It was discovered that the optimal proses parameter levels for surface roughness by the CR-10S Pro FDM machine are 0.1 mm of layer height, 90% of flow rate, 230°C of printing temperature, and 35mm/s of print speed. Thus, Taguchi method has proven to be a useful approach for optimizing parameters to improve the surface roughness of printed parts.

The properties of 3D printed poly (lactic acid) (PLA)/poly (butylene-adipate-terephthalate) (PBAT) blend and oil palm empty fruit bunch (EFB) reinforced PLA/PBAT composites used in fused deposition modelling (FDM) 3D printing

Abstract Poly (lactic acid) (PLA) is amongst the preferable materials used in 3D printing (3DP), especially in fused deposition modelling (FDM) technique because of its unique properties such as good appearance, higher transparency, less toxicity, and low thermal expansion that help reduce the internal stresses caused during cooling. However, PLA is brittle and has low toughness and thermal resistance that affect its printability and restricts its industrial applications. Therefore, PLA was blended with various content of polybutylene adipate terephthalate (PBAT) at 20, 50 and 80 wt% via twin-screw extruder to improve the ductility and impact properties of PLA. The addition of PBAT increased the elongation at break of PLA with a linear increasing amount of PBAT. However, 20 wt% PBAT was selected as the most promising and balance properties of PLA/PBAT because although it has a slight increment in its elongation at break but it exhibits higher impact strength than that of PLA. The tensile strength and tensile modulus of sample with 20 wt% PBAT is greater than 50 and 80 wt% PBAT. Then, PLA/PBAT (80/20, 50/50 and 20/80) and PLA/PBAT/EFB (80/20/10) were printed using FDM machine and were characterized in tensile, impact and morphological properties. The tensile result indicated that the addition of PBAT decreased the tensile strength and tensile modulus of PLA/PBAT-3DP. The terephthalate group in the PBAT affects the mechanical properties of PLA/PBAT-3DP, resulting in high elongation at break but relatively low tensile strength. Besides, the tensile strength and tensile modulus of PLA/PBAT/EFB-3DP decreased and lower than PLA-3DP and PLA/PBAT-3DP. The impact test resulted in high impact strength in PLA/PBAT-3DP, where 50/50-3DP and 20/80-3DP are unbreakable. The impact strength of PLA/PBAT/EFB-3DP is also increased from PLA-3DP but lower than PLA/PBAT-3DP. The scanning electron microscopy (SEM) results revealed that the filament layering on 80/20-3DP was oriented than 50/50-3DP and 20/80-3DP. Besides, the SEM images of PLA/PBAT/EFB-3DP revealed the inhomogeneous and large agglomeration of EFB particle in PLA/PBAT matrix. Therefore, in the future, the polymer blend and polymer blend composite from PLA, PBAT and EFB can be developed where the properties will be based on the study and this study also shed light on the importance of extrusion settings during the manufacture of filament for 3D printing.

Four Rs Framework for the development of a digital twin: The implementation of Representation with a FDM manufacturing machine

This work considers the conceptualization and design of a 4 Rs framework for creating a general purpose, modular Digital Twin. The 4 Rs, correspond to the 4 different phases of a Digital Twin implementation, namely Representation, Replication, Reality, and Relational. Representation is about understanding the physical system, its behavior, actions, components, relationships and describing the significant features for the identified use case as data and algorithms. Replication duplicates the chosen components/variables in a virtual environment from a set of inputs identified in Representation. Reality employs machine learning to produce a virtual device that runs independent of the physical device with the ability to make predictions, enhance models, provide alternative scenarios and optimizations. Reality enhances the virtual system to become autonomous and self-aware with the ability to make decisions and take corrective actions. We introduce these phases and outline their core elements and principles. We showcase the implementation of phase 1, Representation, using a Fused Deposition Modeling (FDM) additive manufacturing machine via temperature and position sensors. We evaluate their precision in representing the actual FDM machine and lay the foundation work for the implementation of the 4R framework in our next work.

Optimization of FDM 3D printing parameters for high strength PEEK using the Taguchi method and experimental validation

PurposePolyetheretherketone (PEEK) is used to manufacture biomedical implants because it has a high strength-to-weight ratio and high strength and is biocompatible. However, the use of fused deposition modeling to print a PEEK results in low strength and crystallinity. This study aims to use the Taguchi method to optimize the printing factors to obtain the highest tensile strength of the printed PEEK object. The annealing effect on printed PEEK object and crystallinity are also investigated.Design/methodology/approachThis study determines the printing factors including the printing speed, layer thickness, printing temperature and extrusion width. Taguchi experimental design with a L9 orthogonal array is used to print the tensile specimen and carried out the tensile test to compare the tensile strength and porosity. Analysis of variance (ANOVA) is used to determine the experimental error and to determine the optimization printing parameters to obtain the highest tensile strength. A multivariate linear regression analysis is used to obtain the linear regression equation for predicting the theoretical tensile strength. An X-ray analysis is achieved to evaluate the crystalline of printed object. The effect of annealing is investigated to improve the tensile strength of printed part. An intervertebral lumber device is printed to demonstrate the feasibility of the obtained optimization parameters for practical application.FindingsTaguchi experiment designs nine sets of parameters to print the PEEK tensile specimen. The experimental results and the ANOVA present that the order in which the factors affect the tensile strength for printed PEEK parts is the layer thickness, the extrusion width, the printing speed and the printing temperature. The optimized printing parameters are a printing speed of 5 mm/s, a layer thickness of 0.1 mm, a printing temperature of 395 °C and an extrusion strand width of 0.44 mm. The average tensile strength of printed specimen with the optimized printing parameters is 91.48 MPa, which is slightly less than the theoretical predicted value of 94.34 MPa. After annealing, the tensile strength increases to 98.85 MPa, which is comparable to that for molded PEEK and the porosity decreases to 0.3 from 3.9%. X-ray diffraction results show that all printed and annealed specimens have a high degree of crystallinity. The printed intervertebral lumber device has ultimate compressive load of 13.42 kN.Originality/valueThe optimized printing parameters is suitable for low-price fused deposition modeling machine because it does not involve a table at high temperature and can print the PEEK object with high tensile strength and good crystalline. Annealing parameters offer a good solution for tensile strength improvement.

Model of Production System Evaluation with the Influence of FDM Machine Reliability and Process-Dependent Product Quality.

This paper investigates the Job Shop Scheduling Problem (JSSP) with FDM (Fused Deposition Modeling) machine unavailability constraints due to Predictive Maintenance (PdM) tasks, under the objective of minimizing the makespan, total tardiness and machine idle time. The Ant-Colony Optimization (ACO) algorithm is elaborated to deal with the JSSP. The reliability characteristics of the critical machine (FDM) influence the product as well as the production system quality. PdM periods are estimated based on historical data on failure-free times of the FDM machine components and deviations from the standards established for the key process parameters: infill density, layer thickness and extruder temperature. The standards for the key process parameters are identified based on investigation of the mechanical properties of printed elements. The impact of failure time and the number of nonstandard measurements of parameters on the quality of the Job Shop System (JSS) are observed. Failure rate of the FDM machine is corrected with the probability of a stoppage in the future period due to the “outlier” in measurements of any key parameters of the additive process. The quality robustness of production schedules increases with the disturbance-free operation of the FDM up to the peak value. After reaching the peak value the quality robustness decreases. The original issue of this paper is a model of scheduling production and maintenance tasks in a job shop system with an FDM machine as a bottleneck using ACO. Additionally, an original FDM-reliability model is also proposed. The model is based on weighted p-moving averages of the observed number of deviations from the norms, established for key process parameters such as fill density, layer thickness and extruder temperature.

Electrical properties of 3D printed continuous carbon fibre composites made using the FDM process

Fused deposition modelling (FDM) is an additive manufacturing process for the 3D printing of continuous fibre-thermoplastic composite laminates. The electrical conductivity of continuous carbon fibre (CF)-nylon filaments and laminates printed with a Markforged MarkTwo® FDM machine is experimentally investigated. The axial electrical conductivity of single filaments measured before, during and following the FDM process reveal a large reduction (∼40%) due mostly to breakage of carbon fibres. The electrical conductivity of 3D printed laminates made by the layer-by-layer deposition of the single filaments were determined in the longitudinal, transverse and through-thickness directions, and compared to the electrical properties of a hot moulded composite with a near-equivalent carbon fibre content. The longitudinal conductivity of the 3D printed laminate was only ∼50% that of the hot moulded composite, and this was due mostly to fibre breakages caused by the FDM process. However, the transverse and through-thickness electrical conductivities of the 3D printed laminate were higher (∼13 times and ∼3 times, respectively) than the hot moulded composite due to higher fibre waviness causing increased fibre-to-fibre contact which aids the flow of electrical current in these two directions.

Influence of Infill Patterns Generated by CAD and FDM 3D Printer on Surface Roughness and Tensile Strength Properties

Fused deposition modeling (FDM) is a capable technology based on a wide range of parameters. The goal of this study is to make a comparison between infill pattern and infill density generated by computer-aided design (CAD) and FDM. Grid, triangle, zigzag, and concentric patterns with various densities following the same structure of the FDM machine were designed by CAD software (CATIA V5®). Polylactic acid (PLA) material was assigned for both procedures. Surface roughness (SR) and tensile strength analysis were conducted to examine their effects on dog-bone samples. Also, a finite element analysis (FEA) was done on CAD specimens to find out the differences between printing and simulation processes. Results illustrated that CAD specimens had a better surface texture compared to the FDM machine while tensile tests showed patterns generated by FDM were stronger in terms of strength and stiffness. In this study, samples with concentric patterns had the lowest average SR (Ra) while zigzag was the worst with the value of 6.27 µm. Also, the highest strength was obtained for concentric and grid samples in both CAD and FDM procedures. These techniques can be useful in producing highly complex sandwich structures, bone scaffolds, and various combined patterns to achieve an optimal condition.

Investigation of Investment Casting Pattern Using Fused Deposition Modeling

In today's economic climate, various organizations fight with decreasing sales and increasing costs. However, industries that have implemented the process of investment casting are one of the ways of manufacturing complex metallic parts at a low cost. High tooling costs and long manufacturing time are associated with the metal molds production for producing investment casting wax (sacrificial) patterns. It leads to a problem with cost justification for personalized single casting or production of small lots. The present study evaluates the suitability of the fused deposition modeling (FDM) fabricated pattern for investment casting. For this, a case study on a part was also conducted to collect experimental data regarding the process. A trial component was fabricated in an FDM machine and then cast by the investment method. This research resulted in reduced process time and cost for the small and medium size of the batch.

Effect of processing parameters on mechanical properties of FDM filament prepared on single screw extruder

Fused deposition modeling (FDM) using Acrylonitrile Butadiene Styrene (ABS) polymer as filament is gaining a distinct advantage in manufacturing industries because of its ability to manufacture parts with complex shapes without any tooling requirement and human interface. Present research work aims to develop an alternative FDM filament using nylon 6, Al powder, and Al2O3 powder, which is to be used in existing original equipment manufacturer (OEM) FDM system without changing hardware/software of the system. Taguchi L9, orthogonal array approach, has been used to study the effect of input process parameters, i.e., proportions of filament ingredient, barrel temperature, and die temperature on mechanical properties of filament developed. Proportions of filament ingredients are found to have a significant effect on tensile strength, Young's modulus, and percentage elongation. The required filament has been successfully developed, having more improved properties. The resulting composite filament prepared by extrusion was found to work well with an FDM machine.

Optimization Of Process Parameters In 3d Printing-Fused Deposition Modeling Using Taguchi Method

3D printing or Rapid Prototyping (RP) or Additive Manufacturing (AM) is an innovative manufacturingmethod that is mostly used for prototypes in various Industries such as Aerospace, Defense, Medical, Automotive, etc. One of the worthy and widely used 3 D printing techniques is Fused Deposition Modeling (FDM), which involves adding melted material layer by layer. FDM has several benefits over other manufacturing methods. While setting the 3 D printing options, we have to take several parameters into account, such as speed, layer thickness and infill density, etc. The present experimental work illustrates the performance of ABS built parts fabricated by AION 500 make FDM machine. The quality of parts produced by FDM process mainly depends on the selection of process parameters. The present research work consists of process parameters such as layer thickness, infill density and speed of deposition, etc. This study aims to find effects of process parameters on different performance parameters i.e., mechanical considerations (impact strength), build time, surface roughness in a systematic manner with less number of experimental runs. Taguchi design of experiment (DOE) approach has been used to save cost and time of experimentation. Statistical significance of process parameters is analyzed using analysis of variance (ANOVA). The significant parameters for optimum results and optimal parameter setting has been suggested using S/N ratio.