scholarly journals Theoretical and Experimental Investigation on the 3D Surface Roughness of Material Extrusion Additive Manufacturing Products

Polymers ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 293
Author(s):  
Shijie Jiang ◽  
Ke Hu ◽  
Yang Zhan ◽  
Chunyu Zhao ◽  
Xiaopeng Li
Keyword(s):  
Surface Roughness ◽  
Additive Manufacturing ◽  
Surface Defects ◽  
Raw Materials ◽  
Fiber Direction ◽  
Layer By Layer ◽  
Forming Process ◽  
Material Extrusion ◽  
Proposed Model ◽  
Wide Range

Material extrusion (ME), one of the most widely used additive manufacturing technique, has the advantages of freedom of design, wide range of raw materials, strong ability to manufacture complex products, etc. However, ME products have obvious surface defects due to the layer-by-layer manufacturing characteristics. To reveal the generation mechanism, the three-dimensional surface roughness (3DSR) of ME products was investigated theoretically and experimentally. Based on the forming process of bonding neck, the 3DSR theoretical model in two different directions (vertical and parallel to the fiber direction) was established respectively. The preparation of ME samples was then completed and a series of experimental tests were performed to determine their surface roughness with the laser microscope. Through the comparison between theoretical and experimental results, the proposed model was validated. In addition, sensitivity analysis is implemented onto the proposed model, investigating how layer thickness, extrusion temperature, and extrusion width influence the samples’ surface roughness. This study provides theoretical basis and technical insight into improving the surface quality of ME products.

Ti6Al4V Parts Produced by Electron Beam Melting: Analysis of Dimensional Accuracy and Surface Roughness

2020 ◽  
Vol 19 (01) ◽  
pp. 107-130 ◽  
Author(s):  
R. Borrelli ◽  
S. Franchitti ◽  
C. Pirozzi ◽  
L. Carrino ◽  
L. Nele ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Electron Beam ◽  
Additive Manufacturing ◽  
Electron Beam Melting ◽  
Complex Shape ◽  
Electron Beam Welding ◽  
Raw Materials ◽  
Dimensional Accuracy ◽  
High Energy ◽  
Quality Certification

Additive manufacturing (AM), applied to metal industry, is a family of processes that allows complex shape components to be realized from raw materials in the form of powders. Electron beam melting (EBM) is a relatively new additive manufacturing (AM) technology. Similar to electron-beam welding, EBM utilizes a high-energy electron beam as a moving heat source to melt metal powder, and 3D parts are produced in a layer-building fashion by rapid self-cooling. By EBM, it is possible to realize metallic complex shape components, e.g. fine network structures, internal cavities and channels, which are difficult to make by conventional manufacturing means. This feature is of particular interest in titanium industry in which numerous efforts are done to develop near net shape processes. In the field of mechanical engineering and, in particular, in the aerospace industry, it is crucial for quality certification purpose that components are produced through qualified and robust manufacturing processes ensuring high product repeatability. The contribution of the present work is to experimentally identify the EBM job parameters (sample orientation, location of the sample in the layer and height in the build chamber) that influence the dimensional accuracy and the surface roughness of the manufactured parts in Ti6Al4V. The repeatability of EBM is investigated too.

Green-State Micromilling of Additive Manufactured AISI316 L

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Sandeep Kuriakose ◽  
Paolo Parenti ◽  
Salvatore Cataldo ◽  
Massimiliano Annoni
Keyword(s):  
Surface Roughness ◽  
Surface Quality ◽  
Surface Defects ◽  
Three Dimensional ◽  
Cutting Speed ◽  
Force Sensor ◽  
Depth Of Cut ◽  
Green State ◽  
Air Supply ◽  
Wide Range

Additive manufacturing (AM) of metal offers matchless design sovereignty to manufacture metallic microcomponents from a wide range of materials. Green-state micromilling is a promising method that can be integrated into the AM of metallic feedstock microcomponents in typical extrusion-based AM methods for compensating the inability to generate microfeatures. The integration enables the manufacturing of complex geometries, the generation of good surface quality, and can provide exceptional flexibility to new product shapes. This work is a micromachinability study of AISI316 L feedstock components produced by extrusion-based AM where the effects of workpiece temperature and the typical micromilling parameters such as cutting speed, feed per tooth, axial depth of cut, and air supply are studied. Edge integrity and surface roughness of the machined slots, as well as cutting forces, are analyzed using three-dimensional microscopy and piezoelectric force sensor, respectively. Green-state micromilling results were satisfying with good produced quality. The micromilling of heated workpieces (45 °C), with external air supply for debris removal, showed the best surface quality with surface roughness values that reached around Sa = 1.5 μm, much smaller than the average metal particles size. Minimum tendency to borders breakage was showed but in some cases microcutting was responsible of the generation of surface defects imputable to lack of adhesion of deposited layers. Despite this fact, the integrability of micromilling into extrusion-based AM cycles of metallic feedstock is confirmed.

scholarly journals Denoising of Images Using Deep Convolutional Autoencoders for Brain Tumor Classification

2021 ◽  
Vol 35 (6) ◽  
pp. 489-496
Author(s):  
Revathi Vankayalapati ◽  
Akka Lakshmi Muddana
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Brain Mri ◽  
Model Performance ◽  
The Body ◽  
Resonance Imaging ◽  
Forming Process ◽  
Medical Sector ◽  
Proposed Model ◽  
Wide Range

In the acquisition of images of the human body, medical imaging devices are crucial. The Magnetic Resonance Imaging (MRI) system detects tissue anomalies and tumours in the body of people. During the forming process, the MRI images are degraded by different kind of noises. It is difficult to remove certain noises, accompanied by the segmentation of images in order to classify anomalies. The most commonly explored areas of this period are automatic tumour detection systems using Magnetic Resonance Imaging. In the medical sector, timely and exact identification of frequencies is a problem. Automated systems are efficient that reduce human errors when tumour is detected. In recent years, many approaches have been proposed to do this, but there are still several drawbacks and a wide range of improvements on these methodologies are still needed. The image processing mechanism is widely used to improve early detection and treatment stages in the field of medical sciences. Sometimes the doctor can misdiagnose the image of MRI because of noise levels. To date, Deep Convolution Neural Networks (DCNN) have demonstrated excellent classification and segmentation efficiency. This paper proposes a technique for the image denoising using DCNN based Auto Encoders (DCNNAE) for achieving better accuracy rates in brain tumour prediction. In this paper we propose a deep convolution denoising auto encoder to remove noise from images and over fit the model problem by developing a deep convolution neural network for brain MRI image tumour prediction. The proposed model is compared with the existing methods and the results exhibits that the proposed model performance levels are better than the existing ones.

scholarly journals The Influence of Different Slicer Software on 3d Printing Products Accuracy and Surface Roughness

2021 ◽  
Vol 12 (2) ◽  
pp. 371-380
Author(s):  
Sally Cahyati ◽  
◽  
Haris Risqy Aziz
Keyword(s):  
Surface Roughness ◽  
Additive Manufacturing ◽  
3D Printing ◽  
3D Model ◽  
High Surface ◽  
3D Printer ◽  
Layer By Layer ◽  
Additive Manufacturing Technology ◽  
Printing Machine

Rapid Prototyping (RP) is a manufacturing process that produces a 3D model CAD to be a real product rapidly by using additive manufacturing technology. In this case, the product will print layer by layer uses a 3D printer machine. The 3D printer requires slicer software to convert CAD data into data that a 3D printer machine can read. Research is done to analyze the effect of three kinds of slicer software on 3D printing objects on the accuracy and surface roughness of the product. The 3D model CAD is sliced using three different slicer software, namely Ideamaker, Repetier Host, and Cura. The slice model result from each slicer will be printed on a 3D printer machine with the same process parameters to be compared. Then the product's dimensional and surface roughness will be measured to determine the effect of each slicer on product quality. The best quality of the product reflected the most suitable slicer software for the 3D printing machine that used. The best results achieved by Cura slicer because it has resulted in small dimensional deviations (max 0,0308±0,0079) and stabile high surface roughness of the product (max 1,585+059).

scholarly journals Processing of Aluminium-Silicon Alloy with Metal Carbide as Reinforcement through Powder-Based Additive Manufacturing: A Critical Study

Scanning ◽  
2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
R. Raj Mohan ◽  
R. Venkatraman ◽  
S. Raghuraman ◽  
P. Manoj Kumar ◽  
Moti Lal Rinawa ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Raw Materials ◽  
Cast Alloy ◽  
Critical Study ◽  
Layer By Layer ◽  
Aircraft Structure ◽  
Composite Fabrication ◽  
Art Research ◽  
Automotive Brake ◽  
Comprehensive Study

Powder-based additive manufacturing (PAM) is a potential fabrication approach in advancing state-of-the-art research to produce intricate components with high precision and accuracy in near-net form. In PAM, the raw materials are used in powder form, deposited on the surface layer by layer, and fused to produce the final product. PAM composite fabrication for biomedical implants, aircraft structure panels, and automotive brake rotary components is gaining popularity. In PAM composite fabrication, the aluminium cast alloy is widely preferred as a metal matrix for its unique properties, and different reinforcements are employed in the form of oxides, carbides, and nitrides. However, for enhancing the mechanical properties, the carbide form is predominantly considered. This comprehensive study focuses on contemporary research and reveals the effect of metal carbide’s (MCs) addition to the aluminium matrix processed through various PAM processes, challenges involved, and potential scopes to advance the research.

Curved-layered material extrusion modeling for thin-walled parts by a 5-axis machine

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaojing Feng ◽  
Bin Cui ◽  
Yaxiong Liu ◽  
Lianggang Li ◽  
Xiaojun Shi ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Surface Roughness ◽  
Additive Manufacturing ◽  
Layered Material ◽  
Bottom Surface ◽  
Motion Mechanism ◽  
Content Type ◽  
Material Extrusion ◽  
Thin Walled ◽  
Five Axis

Purpose The purpose of this paper is to solve the problems of poor mechanical properties, high surface roughness and waste support materials of thin-walled parts fabricated by flat-layered additive manufacturing process. Design/methodology/approach This paper proposes a curved-layered material extrusion modeling process with a five-axis motion mechanism. This process has advantages of the platform rotating, non-support printing and three-dimensional printing path. First, the authors present a curved-layered algorithm by offsetting the bottom surface into a series of conformal surfaces and a toolpath generation algorithm based on the geodesic distance field in each conformal surface. Second, they introduce a parallel five-axis printing machine consisting of a printing head fixed on a delta-type manipulator and a rotary platform on a spherical parallel machine. Findings Mechanical experiments show the failure force of the five-axis printed samples is 153% higher than that of the three-axis printed samples. Forming experiments show that the surface roughness significantly decreases from 42.09 to 18.31 µm, and in addition, the material consumption reduces by 42.90%. These data indicate the curved-layered algorithm and five-axis motion mechanism in this paper could effectively improve mechanical properties and the surface roughness of thin-walled parts, and realize non-support printing. These methods also have reference value for other additive manufacturing processes. Originality/value Previous researchers mostly focus on printing simple shapes such as arch or “T”-like shape. In contrast, this study sets out to explore the algorithm and benefits of modeling thin-walled parts by a five-axis machine. Several validated models would allow comparability in five-axis printing.

Multiscale Modeling of the Laser Additive Manufacturing Process

2020 ◽  
pp. 235-248
Author(s):  
Seshadev Sahoo ◽  
Jyotirmoy Nandy
Keyword(s):  
Additive Manufacturing ◽  
Multiscale Modeling ◽  
Manufacturing Sector ◽  
Layer By Layer ◽  
Waste Production ◽  
Detailed Classification ◽  
Wide Range ◽  
Manufacturing Techniques ◽  
The Many ◽  
Efficient Manufacturing

Additive manufacturing (AM) has emerged as the most versatile process in the manufacturing sector. The advantages of AM such as applicability in a wide range of industries, ease of manufacturing, and reduction in waste production have increased its demand over the past decades. Out of the many techniques under AM, direct metal laser sintering (DMLS) is one of the most efficient manufacturing techniques that uses a high-powered laser beam to sinter metal powders in a layer-by-layer fashion. With the current usage of computational modeling, the prediction of microstructure evolution and other thermo-mechanical properties of different materials have been of great advantage to researchers. Along with a detailed classification of AM techniques, this chapter focuses on the use of continuum, phase field, and atomistic modeling under the DMLS process. The results show that multiscale modeling can be advantageous in gaining deeper insight into various phenomena like diffusion and sintering.

IMPACT OF ADDITIVE MANUFACTURING ON INTERNAL COOLING CHANNELS WITH VARYING DIAMETERS AND BUILD DIRECTIONS

2021 ◽  
pp. 1-52
Author(s):  
Alexander J. Wildgoose ◽  
Karen A. Thole ◽  
Paul Sanders ◽  
Lieke Wang
Keyword(s):  
Surface Roughness ◽  
Nusselt Number ◽  
Additive Manufacturing ◽  
Friction Factor ◽  
Internal Cooling ◽  
Pressure Losses ◽  
Wide Range ◽  
Geometric Deviations ◽  
Different Diameters ◽  
The Impact

Abstract The use of additive manufacturing (AM) processes, such as direct metal laser sintering, provides the design freedom required to incorporate complex cooling schemes in gas turbine components. Additively manufactured turbine components have a range of cooling feature sizes and, because of the inherent three-dimensionality, a wide range of build angles. Previous studies have shown that AM build directions influence internal channel surface roughness that, in turn, augment heat transfer and pressure loss. This study investigates the impact of additive manufacturing on channel feature size and build direction relative to tolerance, surface roughness, pressure losses, and convective cooling. Multiple AM coupons were built from Inconel 718 consisting of channels with different diameters and a variety of build directions. An experimental rig was used to measure pressure drop to calculate friction factor and was used to impose a constant surface temperature boundary condition to collect Nusselt number over a range of Reynolds numbers. Significant variations in surface roughness and geometric deviations from the design intent were observed for distinct build directions and channel sizes. These differences led to notable impacts in friction factor and Nusselt number augmentations, which were a strong function of build angle.

A Review Paper on Product Surface Defect Detection of Ironing Process

2016 ◽  
Vol 836 ◽  
pp. 147-152
Author(s):  
Akhmad Faizin ◽  
Arif Wahjudi ◽  
I. Made Londen Batan ◽  
Agus Sigit Pramono
Keyword(s):  
Image Processing ◽  
Surface Roughness ◽  
Defect Detection ◽  
Surface Defect ◽  
Surface Defects ◽  
Forming Process ◽  
Metal Forming Process ◽  
Surface Defect Detection ◽  
Product Surface ◽  
Processing Techniques

The quality of product of manufacturing industries depends on dimension accurately and surface roughness quality. There are many types of surface defects and levels of surface roughness quality. Ironing process is one type of metal forming process, which aims to reduce the wall thickness of the cup-shaped or pipes products, thus increasing the height of the wall. Manually surface inspection procedures are very inadequate to ensure the surface in guaranteed quality. To ensure strict requirements of customers, the surface defect inspection based on image processing techniques has been found to be very effective and popular over the last two decades. The paper has been reviewed some papers based on image processing for defect detection. It has been tried to find some alternatives of useful methods for product surface defect detection of ironing process.

scholarly journals Mechanical and Thermal Analyses of Metal-PLA Components Fabricated by Metal Material Extrusion

Inventions ◽  
2020 ◽  
Vol 5 (3) ◽  
pp. 44 ◽  
Author(s):  
Mahdi Mohammadizadeh ◽  
Hao Lu ◽  
Ismail Fidan ◽  
Khalid Tantawi ◽  
Ankit Gupta ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Thermal Analyses ◽  
Microstructural Analysis ◽  
Industrial Applications ◽  
Mechanical And Thermal Properties ◽  
Aluminum Powders ◽  
Material Extrusion ◽  
Metal Material ◽  
Wide Range ◽  
Metallic Parts

Metal additive manufacturing (AM) has gained much attention in recent years due to its advantages including geometric freedom and design complexity, appropriate for a wide range of potential industrial applications. However, conventional metal AM methods have high-cost barriers due to the initial cost of the capital equipment, support, and maintenance, etc. This study presents a low-cost metal material extrusion technology as a prospective alternative to the production of metallic parts in additive manufacturing. The filaments used consist of copper, bronze, stainless steel, high carbon iron, and aluminum powders in a polylactic acid matrix. Using the proposed fabrication technology, test specimens were built by extruding metal/polymer composite filaments, which were then sintered in an open-air furnace to produce solid metallic parts. In this research, the mechanical and thermal properties of the built parts are examined using tensile tests, thermogravimetric, thermomechanical and microstructural analysis.

Sign in / Sign up

Export Citation Format

Share Document