Increasing deposition height stability in robotic GTA additive manufacturing based on arc voltage sensing and control

2020 ◽  
Vol 65 ◽  
pp. 101977 ◽  
Author(s):  
Beibei Zhu ◽  
Jun Xiong
Keyword(s):  
Additive Manufacturing ◽  
Voltage Sensing ◽  
Arc Voltage ◽  
And Control ◽  
Deposition Height

Fractal Pattern Recognition of Image Profiles for Manufacturing Process Monitoring and Control

2018 ◽  
Author(s):  
Farhad Imani ◽  
Bing Yao ◽  
Ruimin Chen ◽  
Prahalada Rao ◽  
Hui Yang
Keyword(s):  
Additive Manufacturing ◽  
Process Monitoring ◽  
Manufacturing Process ◽  
Manufacturing Systems ◽  
Experimental Studies ◽  
Precision Machining ◽  
Monitoring And Control ◽  
Process Monitoring And Control ◽  
Ultra Precision ◽  
And Control

Nowadays manufacturing industry faces increasing demands to customize products according to personal needs. This trend leads to a proliferation of complex product designs. To cope with this complexity, manufacturing systems are equipped with advanced sensing capabilities. However, traditional statistical process control methods are not concerned with the stream of in-process imaging data. Also, very little has been done to investigate nonlinearity, irregularity, and inhomogeneity in image stream collected from manufacturing processes. This paper presents the multifractal spectrum and lacunarity measures to characterize irregular and inhomogeneous patterns of image profiles, as well as detect the hidden dynamics of the underlying manufacturing process. Experimental studies show that the proposed method not only effectively characterizes the surface finishes for quality control of ultra-precision machining but also provides an effective model to link process parameters with fractal characteristics of in-process images acquired from additive manufacturing. This, in turn, will allow a swift response to processes changes and consequently reduce the number of defective products. The proposed fractal method has strong potentials to be applied for process monitoring and control in a variety of domains such as ultra-precision machining, additive manufacturing, and biomanufacturing.

scholarly journals A Review on Development of Bio-Inspired Implants Using 3D Printing

Biomimetics ◽  
2021 ◽  
Vol 6 (4) ◽  
pp. 65
Author(s):  
Ansheed A. Raheem ◽  
Pearlin Hameed ◽  
Ruban Whenish ◽  
Renold S. Elsen ◽  
Aswin G ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
3D Printing ◽  
Layer By Layer ◽  
Medical Implants ◽  
3D Print ◽  
Metal Implants ◽  
Natural Tissue ◽  
And Control ◽  
Natural Architecture ◽  
Fine Tune

Biomimetics is an emerging field of science that adapts the working principles from nature to fine-tune the engineering design aspects to mimic biological structure and functions. The application mainly focuses on the development of medical implants for hard and soft tissue replacements. Additive manufacturing or 3D printing is an established processing norm with a superior resolution and control over process parameters than conventional methods and has allowed the incessant amalgamation of biomimetics into material manufacturing, thereby improving the adaptation of biomaterials and implants into the human body. The conventional manufacturing practices had design restrictions that prevented mimicking the natural architecture of human tissues into material manufacturing. However, with additive manufacturing, the material construction happens layer-by-layer over multiple axes simultaneously, thus enabling finer control over material placement, thereby overcoming the design challenge that prevented developing complex human architectures. This review substantiates the dexterity of additive manufacturing in utilizing biomimetics to 3D print ceramic, polymer, and metal implants with excellent resemblance to natural tissue. It also cites some clinical references of experimental and commercial approaches employing biomimetic 3D printing of implants.

Additive Manufacturing of Porous Ceramics with Foaming Agent

2021 ◽  
pp. 1-21
Author(s):  
Zipeng Guo ◽  
Lu An ◽  
Sushil Lakshmanan ◽  
Jason Armstrong ◽  
Shenqiang Ren ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Ambient Pressure ◽  
Experimental Studies ◽  
Three Dimensional ◽  
Cost Effective ◽  
Tensile Tests ◽  
Porous Ceramics ◽  
Foaming Agent ◽  
Printing Quality ◽  
And Control

Abstract The macro-porous ceramics has promising durability and thermal insulation performance. As porous ceramics find more and more applications across many industries, a cost-effective and scalable additive manufacturing technique for fabricating macro-porous ceramics is highly desirable. Herein, we reported a facile additive manufacturing approach to fabricate porous ceramics and control the printed porosity. Several printable ceramic inks were prepared, the foaming agent was added to generate gaseous bubbles in the ink, followed by the direct ink writing and the ambient-pressure and room-temperature drying to create the three-dimensional geometries. A set of experimental studies were performed to optimize the printing quality. The results revealed the optimal process parameters for printing the foamed ceramic ink with a high spatial resolution and fine surface quality. Varying the concentration of the foaming agent enables the controllability of the structural porosity. The maximum porosity can reach 85%, with a crack-free internal porous structure. The tensile tests showed that the printed macro-porous ceramics possessed enhanced durability with the addition of fiber. With a high-fidelity 3D printing process and the precise controllability of the porosity, we showed that the printed samples exhibited a remarkably low thermal conductivity and durable mechanical strength.

Low Voltage Sensing and Control Applied to the Electrical Distribution Grid

2021 ◽  
Author(s):  
Tiago R. Chaves ◽  
Marcos A. Izumida Martins ◽  
Renata Callegaro ◽  
Diego Henrique Nunes ◽  
Kennedy A. Martins ◽  
...  
Keyword(s):  
Low Voltage ◽  
Distribution Grid ◽  
Voltage Sensing ◽  
Electrical Distribution ◽  
And Control

Energy Efficient Multi-Robotic 3D Printing for Large-Scale Construction – Framework, Challenges, and a Systematic Approach

2021 ◽  
Author(s):  
Azadeh Haghighi ◽  
Abdullah Mohammed ◽  
Lihui Wang
Keyword(s):  
Additive Manufacturing ◽  
3D Printing ◽  
Energy Efficient ◽  
Large Scale ◽  
Systematic Approach ◽  
Smart Manufacturing ◽  
Energy Aware ◽  
Robot Positioning ◽  
Novel Concept ◽  
And Control

Abstract An emerging trend in smart manufacturing of the future is robotic additive manufacturing or 3D printing which introduces numerous advantages towards fast and efficient printing of high-quality customized products. In the case of the construction industry, and specifically in large-scale settings, multi-robotic additive manufacturing (i.e., adopting a team of 3D printer robots) has been found to be a promising solution in order to overcome the existing size limitations. Consequently, several research efforts regarding the development and control of such robotic additive manufacturing solutions have been reported in the literature. However, given the increasing environmental concerns, establishing novel methodologies for energy-efficient processing and planning of these systems towards higher sustainability is necessary. This paper presents a novel framework towards energy-efficient multi-robotic additive manufacturing and describes the overall challenges with respect to the energy efficiency. The energy module of the proposed framework is implemented in a simulation environment. In addition, a systematic approach for energy-aware robot positioning is introduced based on the novel concept of reciprocal energy map. The reciprocal energy map is established based on the original energy map calculated by the energy module and can be used for identifying the low energy zones for positioning and relocation of robots during the printing process.

In-Process Data Fusion for Process Monitoring and Control of Metal Additive Manufacturing

2021 ◽  
Author(s):  
Zhuo Yang ◽  
Yan Lu ◽  
Simin Li ◽  
Jennifer Li ◽  
Yande Ndiaye ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Process Control ◽  
Data Fusion ◽  
Real Time ◽  
Process Data ◽  
Multi Scale ◽  
And Control ◽  
Fusion Framework ◽  
Scale Data ◽  
Metal Additive

Abstract To accelerate the adoption of Metal Additive Manufacturing (MAM) for production, an understanding of MAM process-structure-property (PSP) relationships is indispensable for quality control. A multitude of physical phenomena involved in MAM necessitates the use of multi-modal and in-process sensing techniques to model, monitor and control the process. The data generated from these sensors and process actuators are fused in various ways to advance our understanding of the process and to estimate both process status and part-in-progress states. This paper presents a hierarchical in-process data fusion framework for MAM, consisting of pointwise, trackwise, layerwise and partwise data analytics. Data fusion can be performed at raw data, feature, decision or mixed levels. The multi-scale data fusion framework is illustrated in detail using a laser powder bed fusion process for anomaly detection, material defect isolation, and part quality prediction. The multi-scale data fusion can be generally applied and integrated with real-time MAM process control, near-real-time layerwise repairing and buildwise decision making. The framework can be utilized by the AM research and standards community to rapidly develop and deploy interoperable tools and standards to analyze, process and exploit two or more different types of AM data. Common engineering standards for AM data fusion systems will dramatically improve the ability to detect, identify and locate part flaws, and then derive optimal policies for process control.

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