scholarly journals A New Approach For Calculating Inherent Strain and Distortion in Additive Manufacturing of Metal Parts

2021 ◽  
Author(s):  
Hong-Seok Park ◽  
Hwa Seon Shin ◽  
Ngoc-Hien TRAN
Keyword(s):  
Additive Manufacturing ◽  
Prediction Method ◽  
Industrial Applications ◽  
Scale Model ◽  
Design Stage ◽  
Design Engineers ◽  
Part Distortion ◽  
Metallic Parts ◽  
Inherent Strain ◽  
Is Value

Abstract Additive manufacturing (AM) of metallic parts is widely utilized for industrial applications. However, quality issues of the printed parts, including part distortion and cracks caused by high temperature and fast cooling, result in high residual stress. This is a challenge that limits the industry acceptance of AM. To overcome this challenge, a numerical modeling method for predicting part distortion at the design stage plays an important role, and enables design engineers to remove failures before printing, as well as determine the optimal printing process parameters to minimize part deformation. This research proposes an inherent strain-based part deformation prediction method. To determine the inherent strain (IS) value, a micro-scale model for analyzing the temperature distribution is constructed. The IS value is calculated from the temperature gradient. Then, the IS value is used for determining the part deformation. The proposed methodology has been developed and evaluated, using a 316L stainless steel cantilever beam, in both simulations and experimental results.

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.

A Methodology for Predicting Porosity From Thermal Imaging of Melt Pools in Additive Manufacturing Thin Wall Sections

2017 ◽  
Author(s):  
Mojtaba Khanzadeh ◽  
Sudipta Chowdhury ◽  
Linkan Bian ◽  
Mark A. Tschopp
Keyword(s):  
Additive Manufacturing ◽  
Prediction Method ◽  
Pool Analysis ◽  
Industrial Applications ◽  
In Situ Monitoring ◽  
Thin Wall ◽  
Structure Property ◽  
Thermal Profile ◽  
Self Organizing Maps ◽  
Melt Pool

The microstructure and mechanical properties of Laser Based Additive Manufacturing (LBAM) are often inconsistent and unreliable for many industrial applications. One of the key technical challenges is the lack of understanding of the underlying process-structure-property relationship. The objective of the present research is to use the melt pool thermal profile to predict porosity within the LBAM process. Herein, we propose a novel porosity prediction method based on morphological features and the temperature distribution of the top surface of the melt pool as the LBAM part is being built. Self-organizing maps (SOM) are then used to further analyze the 2D melt pool dataset to identify similar and dissimilar melt pools. The performance of the proposed method of porosity prediction uses X-Ray tomography characterization, which identified porosity within the Ti-6Al-4V thin wall specimen. The experimentally identified porosity locations were compared to the porosity locations predicted based on the melt pool analysis. Results show that the proposed method is able to predict the location of porosity almost 85% of the time when the appropriate SOM model is selected. The significance of such a methodology is that this may lead the way towards in situ monitoring and on-the-fly modification of melt pool thermal profile to minimize or eliminate pores within LBAM parts.

Multi-Objective Design Problem of Tire Wear and Visualization of Its Pareto Solutions2

2006 ◽  
Vol 34 (3) ◽  
pp. 170-194 ◽  
Author(s):  
M. Koishi ◽  
Z. Shida
Keyword(s):  
Inverse Problems ◽  
Conceptual Design ◽  
Dimensional Space ◽  
Design Stage ◽  
Objective Functions ◽  
Pareto Solutions ◽  
Design Problems ◽  
Multi Objective ◽  
Design Engineers ◽  
Design Variables

Abstract Since tires carry out many functions and many of them have tradeoffs, it is important to find the combination of design variables that satisfy well-balanced performance in conceptual design stage. To find a good design of tires is to solve the multi-objective design problems, i.e., inverse problems. However, due to the lack of suitable solution techniques, such problems are converted into a single-objective optimization problem before being solved. Therefore, it is difficult to find the Pareto solutions of multi-objective design problems of tires. Recently, multi-objective evolutionary algorithms have become popular in many fields to find the Pareto solutions. In this paper, we propose a design procedure to solve multi-objective design problems as the comprehensive solver of inverse problems. At first, a multi-objective genetic algorithm (MOGA) is employed to find the Pareto solutions of tire performance, which are in multi-dimensional space of objective functions. Response surface method is also used to evaluate objective functions in the optimization process and can reduce CPU time dramatically. In addition, a self-organizing map (SOM) proposed by Kohonen is used to map Pareto solutions from high-dimensional objective space onto two-dimensional space. Using SOM, design engineers see easily the Pareto solutions of tire performance and can find suitable design plans. The SOM can be considered as an inverse function that defines the relation between Pareto solutions and design variables. To demonstrate the procedure, tire tread design is conducted. The objective of design is to improve uneven wear and wear life for both the front tire and the rear tire of a passenger car. Wear performance is evaluated by finite element analysis (FEA). Response surface is obtained by the design of experiments and FEA. Using both MOGA and SOM, we obtain a map of Pareto solutions. We can find suitable design plans that satisfy well-balanced performance on the map called “multi-performance map.” It helps tire design engineers to make their decision in conceptual design stage.

scholarly journals Influence of Deposition Patterns on Distortion of H13 Steel by Wire-Arc Additive Manufacturing

Metals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 485
Author(s):  
Xufeng Li ◽  
Jian Lin ◽  
Zhidong Xia ◽  
Yongqiang Zhang ◽  
Hanguang Fu
Keyword(s):  
Additive Manufacturing ◽  
Temperature History ◽  
H13 Steel ◽  
Deposition Patterns ◽  
Field Distortion ◽  
Set Up ◽  
Manufacturing Technologies ◽  
Inherent Strain ◽  
Inherent Strain Method ◽  
Wire Arc Additive Manufacturing

Wire-arc additive manufacturing (WAAM) has been considered as one of the potential additive-manufacturing technologies to fabricate large components. However, its industrial application is still limited by the existence of stress and distortion. During the process of WAAM, the scanning pattern has an important influence on the temperature field, distortion and final quality of the part. Four kinds of deposition patterns, including sequence, symmetry, in–out and out–in, were designed to deposit H13 steel in this study. An in situ measurement system was set up to record the temperature history and the progress of accumulated distortion of the parts during deposition. An S value was proposed to evaluate the distortion of the substrate. It was shown that the distortion of the part deposited by sequence was significantly larger than those of other parts. The distortion deposited by the out–in pattern decreased by 68.6% compared with sequence. The inherent strain method and strain parameter were introduced to expose the mechanism of distortion reduction caused by pattern variation.

scholarly journals Wire Arc Additive Manufacturing: Review on Recent Findings and Challenges in Industrial Applications and Materials Characterization

Metals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 939
Author(s):  
Mukti Chaturvedi ◽  
Elena Scutelnicu ◽  
Carmen Catalina Rusu ◽  
Luigi Renato Mistodie ◽  
Danut Mihailescu ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Structural Integrity ◽  
Industrial Applications ◽  
Raw Material ◽  
Continuous Increase ◽  
Control Optimization ◽  
Modern Manufacturing ◽  
Directed Energy ◽  
Manufacturing Technologies ◽  
Wire Arc Additive Manufacturing

Wire arc additive manufacturing (WAAM) is a fusion manufacturing process in which the heat energy of an electric arc is employed for melting the electrodes and depositing material layers for wall formation or for simultaneously cladding two materials in order to form a composite structure. This directed energy deposition-arc (DED-arc) method is advantageous and efficient as it produces large parts with structural integrity due to the high deposition rates, reduced wastage of raw material, and low consumption of energy in comparison with the conventional joining processes and other additive manufacturing technologies. These features have resulted in a constant and continuous increase in interest in this modern manufacturing technique which demands further studies to promote new industrial applications. The high demand for WAAM in aerospace, automobile, nuclear, moulds, and dies industries demonstrates compatibility and reflects comprehensiveness. This paper presents a comprehensive review on the evolution, development, and state of the art of WAAM for non-ferrous materials. Key research observations and inferences from the literature reports regarding the WAAM applications, methods employed, process parameter control, optimization and process limitations, as well as mechanical and metallurgical behavior of materials have been analyzed and synthetically discussed in this paper. Information concerning constraints and enhancements of the wire arc additive manufacturing processes to be considered in terms of wider industrial applicability is also presented in the last part of this paper.

scholarly journals Additive manufacturing of PLA-based scaffolds intended for bone regeneration and strategies to improve their biological properties

e-Polymers ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 571-599
Author(s):  
Ricardo Donate ◽  
Mario Monzón ◽  
María Elena Alemán-Domínguez
Keyword(s):  
Mechanical Properties ◽  
Tissue Engineering ◽  
Additive Manufacturing ◽  
Bone Regeneration ◽  
Polylactic Acid ◽  
State Of The Art ◽  
Biological Properties ◽  
Design Stage ◽  
Bone Scaffolds ◽  
Regeneration Of Bone

AbstractPolylactic acid (PLA) is one of the most commonly used materials in the biomedical sector because of its processability, mechanical properties and biocompatibility. Among the different techniques that are feasible to process this biomaterial, additive manufacturing (AM) has gained attention recently, as it provides the possibility of tuning the design of the structures. This flexibility in the design stage allows the customization of the parts in order to optimize their use in the tissue engineering field. In the recent years, the application of PLA for the manufacture of bone scaffolds has been especially relevant, since numerous studies have proven the potential of this biomaterial for bone regeneration. This review contains a description of the specific requirements in the regeneration of bone and how the state of the art have tried to address them with different strategies to develop PLA-based scaffolds by AM techniques and with improved biofunctionality.

The role of robotics in additive manufacturing: review of the AM processes and introduction of an intelligent system

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
J. Norberto Pires ◽  
Amin S. Azar ◽  
Filipe Nogueira ◽  
Carlos Ye Zhu ◽  
Ricardo Branco ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Computer Aided Design ◽  
Intelligent System ◽  
Material Selection ◽  
High Strength Steels ◽  
Industrial Applications ◽  
Layer By Layer ◽  
Content Type ◽  
Functional Components

Purpose Additive manufacturing (AM) is a rapidly evolving manufacturing process, which refers to a set of technologies that add materials layer-by-layer to create functional components. AM technologies have received an enormous attention from both academia and industry, and they are being successfully used in various applications, such as rapid prototyping, tooling, direct manufacturing and repair, among others. AM does not necessarily imply building parts, as it also refers to innovation in materials, system and part designs, novel combination of properties and interplay between systems and materials. The most exciting features of AM are related to the development of radically new systems and materials that can be used in advanced products with the aim of reducing costs, manufacturing difficulties, weight, waste and energy consumption. It is essential to develop an advanced production system that assists the user through the process, from the computer-aided design model to functional components. The challenges faced in the research and development and operational phase of producing those parts include requiring the capacity to simulate and observe the building process and, more importantly, being able to introduce the production changes in a real-time fashion. This paper aims to review the role of robotics in various AM technologies to underline its importance, followed by an introduction of a novel and intelligent system for directed energy deposition (DED) technology. Design/methodology/approach AM presents intrinsic advantages when compared to the conventional processes. Nevertheless, its industrial integration remains as a challenge due to equipment and process complexities. DED technologies are among the most sophisticated concepts that have the potential of transforming the current material processing practices. Findings The objective of this paper is identifying the fundamental features of an intelligent DED platform, capable of handling the science and operational aspects of the advanced AM applications. Consequently, we introduce and discuss a novel robotic AM system, designed for processing metals and alloys such as aluminium alloys, high-strength steels, stainless steels, titanium alloys, magnesium alloys, nickel-based superalloys and other metallic alloys for various applications. A few demonstrators are presented and briefly discussed, to present the usefulness of the introduced system and underlying concept. The main design objective of the presented intelligent robotic AM system is to implement a design-and-produce strategy. This means that the system should allow the user to focus on the knowledge-based tasks, e.g. the tasks of designing the part, material selection, simulating the deposition process and anticipating the metallurgical properties of the final part, as the rest would be handled automatically. Research limitations/implications This paper reviews a few AM technologies, where robotics is a central part of the process, such as vat photopolymerization, material jetting, binder jetting, material extrusion, powder bed fusion, DED and sheet lamination. This paper aims to influence the development of robot-based AM systems for industrial applications such as part production, automotive, medical, aerospace and defence sectors. Originality/value The presented intelligent system is an original development that is designed and built by the co-authors J. Norberto Pires, Amin S. Azar and Trayana Tankova.

Design for Additive Manufacturing in the Cloud Platform

2017 ◽  
Author(s):  
Yuanbin Wang ◽  
Robert Blache ◽  
Xun Xu
Keyword(s):  
Knowledge Management ◽  
Decision Support ◽  
Additive Manufacturing ◽  
Full Advantage ◽  
New Technologies ◽  
Design Stage ◽  
Design For Additive Manufacturing ◽  
Cloud Platform ◽  
Am Processes

Additive manufacturing (AM) has experienced a phenomenal expansion in recent years and new technologies and materials rapidly emerge in the market. Design for Additive Manufacturing (DfAM) becomes more and more important to take full advantage of the capabilities provided by AM. However, most people still have limited knowledge to make informed decisions in the design stage. Therefore, an interactive DfAM system in the cloud platform is proposed to enable people sharing the knowledge in this field and guide the designers to utilize AM efficiently. There are two major modules in the system, decision support module and knowledge management module. A case study is presented to illustrate how this system can help the designers understand the capabilities of AM processes and make rational decisions.

scholarly journals Fatigue life prediction in a door hinge system under uni-axial and multi-axial loading conditions

2021 ◽  
Author(s):  
Sacheen Bekah
Keyword(s):  
Axial Loading ◽  
Fatigue Analysis ◽  
Design Stage ◽  
Fe Model ◽  
Preliminary Design ◽  
Standard Requirement ◽  
Ground Vehicle ◽  
Design Engineers ◽  
Door Hinge ◽  
Preliminary Design Stage

This thesis presents the use of Finite Element (FE) based fatigue analysis to locate the critical point of crack initiation and predict life in a door hinge system that is subjected to both uni-axial and multi-axial loading. The results are experimentally validated. The FE model is further used to obtain an optimum design per the standard requirement in the ground vehicle industry. The accuracy of the results showed that FE based fatigue analysis can be successfully employed to reduce costly and time-consuming experiments in the preliminary design stage. Numerical analysis also provides the product design engineers with substantial savings, enabling the testing of fewer prototypes.

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