scholarly journals ANALYSIS OF THE CAUSE AND EFFECTS OF PART DEFECTS IN ABS SAMPLES MADE USING ADDITIVE MANUFACTURING

2020 ◽  
Author(s):  
Arshad Mohammed ◽  
Boppana Chowdary
Keyword(s):  
Compressive Strength ◽  
Additive Manufacturing ◽  
Stress Relief ◽  
Compressive Failure ◽  
Post Processing ◽  
Processing Parameter ◽  
Road Width ◽  
Pattern Number ◽  
Cause And Effect Diagram

This study highlights the cause and effects of part defects in ABS-Based samples using an additive manufacturing process. The parameters that were investigated include build orientation, infill pattern, number of contours, airgap, road width and annealing as a post-processing parameter. Samples were made, and their compressive strength was tested. Additionally, the tested samples were investigated using optical microscopy and the classification of their defects was done. This study is unique in investigating the effect of stress relief annealing along with build process parameters. Furthermore, the various defects associated with compressive failure in additively manufactured artefacts were categorized and a cause and effect diagram was derived which would enable designers to predict the areas of failure of a part.

scholarly journals PoreAnalyzer—An Open-Source Framework for the Analysis and Classification of Defects in Additive Manufacturing

2021 ◽  
Vol 11 (13) ◽  
pp. 6086
Author(s):  
Nils Ellendt ◽  
Fabian Fabricius ◽  
Anastasiya Toenjes
Keyword(s):  
Additive Manufacturing ◽  
Open Source ◽  
Total Porosity ◽  
Shape Accuracy ◽  
Process Maps ◽  
Defect Type ◽  
Open Source Framework ◽  
New Material ◽  
High Cooling Rates

Additive manufacturing processes offer high geometric flexibility and allow the use of new alloy concepts due to high cooling rates. For each new material, parameter studies have to be performed to find process parameters that minimize microstructural defects such as pores or cracks. In this paper, we present a system developed in Python for accelerated image analysis of optical microscopy images. Batch processing can be used to quickly analyze large image sets with respect to pore size distribution, defect type, contribution of defect type to total porosity, and shape accuracy of printed samples. The open-source software is independent of the microscope used and is freely available for use. This framework allows us to perform such an analysis on a circular area with a diameter of 5 mm within 10 s, allowing detailed process maps to be obtained for new materials within minutes after preparation.

scholarly journals Poly(HDDA)-Based Polymers for Microfabrication and Mechanobiology

MRS Advances ◽  
2017 ◽  
Vol 2 (24) ◽  
pp. 1315-1321 ◽  
Author(s):  
Daniela Espinosa-Hoyos ◽  
Huifeng Du ◽  
Nicholas X. Fang ◽  
Krystyn J. Van Vliet
Keyword(s):  
Polyethylene Glycol ◽  
Additive Manufacturing ◽  
Progenitor Cell ◽  
Materials Processing ◽  
Biological Applications ◽  
Post Processing ◽  
Mechanical Stiffness ◽  
Processing Times ◽  
Low Stiffness ◽  
Cell Material Interactions

ABSTRACTMaterials processing and additive manufacturing afford exciting opportunities in biomedical research, including the study of cell-material interactions. However, some of the most efficient materials for microfabrication are not wholly suitable for biological applications, require extensive post-processing or exhibit high mechanical stiffness that limits the range of applications. Conversely, materials exhibiting high cytocompatibility and low stiffness require long processing times with typically decreased spatial resolution of features. Here, we investigated the use of hexanediol diacrylate (HDDA), a classic and efficient polymer for stereolithography, for oligodendrocyte progenitor cell (OPC) culture. We developed composite HDDA-polyethylene glycol acrylate hydrogels that exhibited high biocompatibility, mechanical stiffness in the range of muscle tissue, and high printing efficiency at ∼5 μm resolution.

scholarly journals Laser peening: A tool for additive manufacturing post-processing

2018 ◽  
Vol 24 ◽  
pp. 67-75 ◽  
Author(s):  
Lloyd Hackel ◽  
Jon R. Rankin ◽  
Alexander Rubenchik ◽  
Wayne E. King ◽  
Manyalibo Matthews
Keyword(s):  
Additive Manufacturing ◽  
Laser Peening ◽  
Post Processing

A deep neural network for classification of melt-pool images in metal additive manufacturing

2018 ◽  
Vol 31 (2) ◽  
pp. 375-386 ◽  
Author(s):  
Ohyung Kwon ◽  
Hyung Giun Kim ◽  
Min Ji Ham ◽  
Wonrae Kim ◽  
Gun-Hee Kim ◽  
...  
Keyword(s):  
Neural Network ◽  
Additive Manufacturing ◽  
Deep Neural Network ◽  
Metal Additive Manufacturing ◽  
Melt Pool ◽  
Metal Additive

scholarly journals FEASIBILITY STUDY OF MICRO-LATTICE STRUCTURES BY MULTIPHOTON LITHOGRAPHY

2019 ◽  
Vol 25 ◽  
pp. 83-88
Author(s):  
Markus Wimmer ◽  
Zoltan Major
Keyword(s):  
Additive Manufacturing ◽  
Laser Beam ◽  
Constant Density ◽  
Lattice Structures ◽  
Post Processing ◽  
Constant Frequency ◽  
Layer Height ◽  
Lithography Process ◽  
Multiphoton Lithography ◽  
Laser Firing

The paper describes the possibilities of additive manufacturing with multiphoton lithography. The basis of this technology is that a laser beam (with a certain wavelength) is fired into the mixture of a monomer and a photo-initiator. When the energy of the laser is high enough, the latter acts as a catalyser for the polymerization of the monomer compound. This study focuses on the influences of certain parameters of the multiphoton lithography process. One of the important aspects is the choice of the solvent for the post processing. In sequence to the solvent problem, the influence of the layer height is examined. Furthermore the limits and possibilities of the setup in use are investigated. As an example the differences in fabrication with the laser firing with "constant frequency" and "constant density" were subject of this investigation. The second goal of the study was to compare three different structures consisting of periodically repeating elements, scaled in size and number of elements per side.

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