Role of process parameters during additive manufacturing by direct metal deposition of Inconel 718

2017 ◽  
Vol 23 (5) ◽  
pp. 919-929 ◽  
Author(s):  
Bo Chen ◽  
Jyoti Mazumder
Keyword(s):  
Additive Manufacturing ◽  
Cooling Rate ◽  
Process Parameters ◽  
Manufacturing Process ◽  
Inconel 718 ◽  
Processing Parameters ◽  
Forming Quality ◽  
Content Type ◽  
Forming Characteristics ◽  
The Relationship

Purpose The aim of this research is to study the influence of laser additive manufacturing process parameters on the deposit formation characteristics of Inconel 718 superalloy, the main parameters that influence the forming characteristics, the cooling rate and the microstructure were studied. Design/methodology/approach Orthogonal experiment design method was used to obtain different deposit shape and microstructure using different process parameters by multiple layers deposition. The relationship between the processing parameters and the geometry of the cladding was analyzed, and the dominant parameters that influenced the cladding width and height were identified. The cooling rates of different forming conditions were obtained by the secondary dendrite arm spacing (SDAS). Findings The microstructure showed different characteristics at different parts of the deposit. Cooling rate of different samples were obtained and compared by using the SDAS, and the influence of the process parameters to the cooling rate was analyzed. Finally, micro-hardness tests were done, and the results were found to be in accordance with the micro-structure distribution. Originality/value Relationships between processing parameters and the forming characteristics and the cooling rates were obtained. The results obtained in this paper will help to understand the relationship between the process parameters and the forming quality of the additive manufacturing process, so as to obtain the desired forming quality by appropriate parameters.

Quality detection of laser additive manufacturing process based on coaxial vision monitoring

Sensor Review ◽  
2019 ◽  
Vol 39 (4) ◽  
pp. 512-521 ◽  
Author(s):  
Bo Chen ◽  
Yongzhen Yao ◽  
Yuhua Huang ◽  
Wenkang Wang ◽  
Caiwang Tan ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Process Parameters ◽  
Molten Pool ◽  
Laser Power ◽  
Laser Additive Manufacturing ◽  
Content Type ◽  
Melt Pool ◽  
Forming Defects ◽  
The Relationship ◽  
Pool Area

Purpose This paper aims to explore the influences of different process parameters, including laser power, scanning speed, defocusing distance and scanning mode, on the shape features of molten pool and, based on the obtained relationship, realize the diagnosis of forming defects during the process. Design/methodology/approach Molten pool was captured on-line based on a coaxial CCD camera mounted on the welding head, then image processing algorithms were developed to obtain melt pool features that could reflect the forming status, and it suggested that the molten pool area was the most sensitive characteristic. The influence of the processing parameters such as laser power, traverse speed, powder feed rate, defocusing distance and the melt pool area was studied, and then the melt pool area was used as the characteristic to detect the forming defects during the cladding and additive manufacturing process. Findings The influences of different process parameters on molten pool area were explored. Based on the relationship, different types of defects were accurately detected through analyzing the relationship between the molten pool area and time. Originality/value The findings would be helpful for the quality control of laser additive manufacturing.

A model of bead size based on the dynamic response of CMT-based wire and arc additive manufacturing process parameters

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xuewei Fang ◽  
Chuanqi Ren ◽  
Lijuan Zhang ◽  
Changxing Wang ◽  
Ke Huang ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Dynamic Response ◽  
Prediction Model ◽  
Process Parameters ◽  
Manufacturing Process ◽  
Critical Issue ◽  
Cold Metal Transfer ◽  
Bead Width ◽  
Content Type ◽  
Bead Size

Purpose This paper aims at fabricating large metallic components with high deposition rates, low equipment costs through wire and wire and arc additive manufacturing (WAAM) method, in order to achieve the morphology and mechanical properties of manufacturing process, a bead morphology prediction model with high precision for ideal deposition of every pass was established. Design/methodology/approach The dynamic response of the process parameters on the bead width and bead height of cold metal transfer (CMT)-based AM was analyzed. A laser profile scanner was used to continuously capture the morphology variation. A prediction model of the deposition bead morphology was established using response surface optimization. Moreover, the validity of the model was examined using 15 groups of quadratic regression analyzes. Findings The relative errors of the predicted bead width and height were all less than 5% compared with the experimental measurements. The model was then preliminarily used with necessary modifications, such as further considering the interlayer process parameters, to guide the fabrication of complex three-dimensional components. Originality/value The morphology prediction of WAAMed bead is a critical issue. Most research has focused on the formability and defects in CMT-based WAAM and little research on the effect of process parameters on the morphology of the deposited layer in CMT-based WAAM has been conducted. To test the sensitivities of the processing parameters to bead size, the dynamic response of key parameters was investigated. A regression model was established to guide the process parameter optimization for subsequent multi-layer or component deposition.

Optimal space filling for additive manufacturing

2016 ◽  
Vol 22 (4) ◽  
pp. 660-675 ◽  
Author(s):  
Sajan Kapil ◽  
Prathamesh Joshi ◽  
Hari Vithasth Yagani ◽  
Dhirendra Rana ◽  
Pravin Milind Kulkarni ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Manufacturing Process ◽  
Layered Manufacturing ◽  
Closed Curve ◽  
Numerical Control ◽  
Surface Finishing ◽  
Content Type ◽  
Single Pass ◽  
Connected Area ◽  
Area Filling

Purpose In additive manufacturing (AM) process, the physical properties of the products made by fractal toolpaths are better as compared to those made by conventional toolpaths. Also, it is desirable to minimize the number of tool retractions. The purpose of this study is to describe three different methods to generate fractal-based computer numerical control (CNC) toolpath for area filling of a closed curve with minimum or zero tool retractions. Design/methodology/approach This work describes three different methods to generate fractal-based CNC toolpath for area filling of a closed curve with minimum or zero tool retractions. In the first method, a large fractal square is placed over the outer boundary and then rest of the unwanted curve is trimmed out. To reduce the number of retractions, ends of the trimmed toolpath are connected in such a way that overlapping within the existing toolpath is avoided. In the second method, the trimming of the fractal is similar to the first method but the ends of trimmed toolpath are connected such that the overlapping is found at the boundaries only. The toolpath in the third method is a combination of fractal and zigzag curves. This toolpath is capable of filling a given connected area in a single pass without any tool retraction and toolpath overlap within a tolerance value equal to stepover of the toolpath. Findings The generated toolpath has several applications in AM and constant Z-height surface finishing. Experiments have been performed to verify the toolpath by depositing material by hybrid layered manufacturing process. Research limitations/implications Third toolpath method is suitable for the hybrid layered manufacturing process only because the toolpath overlapping tolerance may not be enough for other AM processes. Originality/value Development of a CNC toolpath for AM specifically hybrid layered manufacturing which can completely fill any arbitrary connected area in single pass while maintaining a constant stepover.

Optimization of built-part distortion in laser powder bed fusion processing of Inconel 718

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
You-Cheng Chang ◽  
Hong-Chuong Tran ◽  
Yu-Lung Lo
Keyword(s):  
Cooling Rate ◽  
Cantilever Beam ◽  
Laser Power ◽  
Scanning Speed ◽  
Processing Parameters ◽  
Laser Powder Bed Fusion ◽  
Simulation Framework ◽  
Content Type ◽  
Powder Bed ◽  
Simulation Results

Purpose Laser powder bed fusion (LPBF) provides the means to produce unique components with almost no restriction on geometry in an extremely short time. However, the high-temperature gradient and high cooling rate produced during the fabrication process result in residual stress, which may prompt part warpage, cracks or even baseplate separation. Accordingly, an appropriate selection of the LPBF processing parameters is essential to ensure the quality of the built part. This study, thus, aims to develop an integrated simulation framework consisting of a single-track heat transfer model and a modified inherent shrinkage method model for predicting the curvature of an Inconel 718 cantilever beam produced using the LPBF process. Design/methodology/approach The simulation results for the curvature of the cantilever beam are calibrated via a comparison with the experimental observations. It is shown that the calibration factor required to drive the simulation results toward the experimental measurements has the same value for all settings of the laser power and scanning speed. Representative combinations of the laser power and scanning speed are, thus, chosen using the circle packing design method and supplied as inputs to the validated simulation framework to predict the corresponding cantilever beam curvature and density. The simulation results are then used to train artificial neural network models to predict the curvature and solid cooling rate of the cantilever beam for any combination of the laser power and scanning speed within the input design space. The resulting processing maps are screened in accordance with three quality criteria, namely, the part density, the radius of curvature and the solid cooling rate, to determine the optimal processing parameters for the LPBF process. Findings It is shown that the parameters lying within the optimal region of the processing map reduce the curvature of the cantilever beam by 17.9% and improve the density by as much as 99.97%. Originality/value The present study proposes a computational framework, which could find the parameters that not only yield the lowest distortion but also produce fully dense components in the LPBF process.

scholarly journals Modelling of Rotary EDM Process Parameters of Inconel 718 Using Artificial Neural Networks

Mechanika ◽  
2020 ◽  
Vol 26 (6) ◽  
pp. 540-544
Author(s):  
Jayaraj JEEVAMALAR ◽  
Sundaresan RAMABALAN ◽  
Chinnamuthu SENTHILKUMAR
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Process Parameters ◽  
Inconel 718 ◽  
Machining Process ◽  
Artificial Neural ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Matlab Programming ◽  
The Relationship

Modelling is used for correlating the relationship between the input process parameters and the output responses during the machining process. To characterize real-world systems of considerable complexity, an Artificial Neural Network (ANN) model is regularly used to replace the mathematical approximation of the relationship. This paper explains the methodological procedure and the outcome of the ANN modeling process for Electrical Discharge Drilling of Inconel 718 superalloy and hollow tubular copper as tool electrode. The most important process parameters in this work are peak current, pulse on time and pulse off time with machining performances of material removal rate and surface roughness. The experiments were performed by L20 Orthogonal Array. In such conditions, an Artificial Neural Network model is developed using MATLAB programming on the Feed Forward Back Propagation technique was used to predict the responses. The experimental data were separated into three parts to train, test the network and validate the model. The developed model has been confirmed experimentally for training and testing in considering the number of iterations and mean square error convergence criteria. The developed model results are to approximate the responses fairly exactly. The model has the mean correlation coefficient of 0.96558. Results revealed that the proposed model can be used for the prediction of the complex EDM drilling process.

Effect of system compliance on weld power in ultrasonic additive manufacturing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gowtham Venkatraman ◽  
Adam Hehr ◽  
Leon M. Headings ◽  
Marcelo J. Dapino
Keyword(s):  
Additive Manufacturing ◽  
Electrical Power ◽  
Three Dimensional ◽  
Power Input ◽  
Material Strength ◽  
Content Type ◽  
Ultrasonic Additive Manufacturing ◽  
Linear Elastic ◽  
Mechanical Compliance ◽  
The Relationship

Purpose Ultrasonic additive manufacturing (UAM) is a solid-state joining technology used for three-dimensional printing of metal foilstock. The electrical power input to the ultrasonic welder is a key driver of part quality in UAM, but under the same process parameters, it can vary widely for different build geometries and material combinations because of mechanical compliance in the system. This study aims to model the relationship between UAM weld power and system compliance considering the workpiece (geometry and materials) and the fixture on which the build is fabricated. Design/methodology/approach Linear elastic finite element modeling and experimental modal analysis are used to characterize the system’s mechanical compliance, and linear system dynamics theory is used to understand the relationship between weld power and compliance. In-situ measurements of the weld power are presented for various build stiffnesses to compare model predictions with experiments. Findings Weld power in UAM is found to be largely determined by the mechanical compliance of the build and insensitive to foil material strength. Originality/value This is the first research paper to develop a predictive model relating UAM weld power and the mechanical compliance of the build over a range of foil combinations. This model is used to develop a tool to determine the process settings required to achieve a consistent weld power in builds with different stiffnesses.

Learning Algorithm Based Modeling and Process Parameters Recommendation System for Binder Jetting Additive Manufacturing Process

2015 ◽  
Author(s):  
Han Chen ◽  
Yaoyao F. Zhao
Keyword(s):  
Additive Manufacturing ◽  
Product Quality ◽  
Process Parameters ◽  
Manufacturing Process ◽  
Process Model ◽  
Recommendation System ◽  
Powder Materials ◽  
Quality Properties ◽  
Binder Jetting ◽  
Printing Time

Binder Jetting (BJ) process is an additive manufacturing process in which powder materials are selectively joined by binder materials. Products can be manufactured layer by layer directly from 3D model data. It is not always easy for manufacturing engineers to choose proper BJ process parameters to meet the end-product quality and fabrication time requirements. This is because the quality properties of the products fabricated by BJ process are significantly affected by the process parameters. And the relationships between process parameters and quality properties are very complicated. In this paper, a process model is developed by Backward Propagation (BP) Neural Network (NN) algorithm based on 16 groups of orthogonal experiment designed by Taguchi Method to express the relationships between 4 key process parameters and 2 key quality properties. Based on the modeling results, an intelligent parameters recommendation system is developed to predict end-product quality properties and printing time, and to recommend process parameters selection based on the process requirements. It can be used as a guideline for selecting the proper printing parameters in BJ to achieve the desired properties and help to reduce the printing time.

Free Abrasive Machining in Slicing Brittle Materials With Wiresaw

2000 ◽  
Vol 123 (3) ◽  
pp. 254-259 ◽  
Author(s):  
Fuqian Yang ◽  
Imin Kao
Keyword(s):  
Process Parameters ◽  
Manufacturing Process ◽  
Brittle Materials ◽  
Stochastic Approach ◽  
Abrasive Machining ◽  
Photovoltaic Applications ◽  
Indentation Crack ◽  
Microelectronics Fabrication ◽  
The Relationship ◽  
Free Abrasive

Wiresaw has emerged as a leading technology in wafer preparation for microelectronics fabrication, especially in slicing large silicon wafers (diameter⩾300 mm) for both microelectronic and photovoltaic applications. Wiresaw has also been employed to slice other brittle materials such as alumina, quartz, glass, and ceramics. The manufacturing process of wiresaw is a free abrasive machining (FAM) process. Specifically, the wiresaw cuts brittle materials through the “rolling-indenting” and “scratch-indenting” processes where the materials removal is resulting from mechanical interactions between the substrate of the workpiece and loss abrasives, which are trapped between workpiece and wire. Built upon results of previous investigation in modeling of wiresaw, a model of wiresaw slicing is developed based on indentation crack as well as the influence of wire carrying the abrasives. This model is used to predict the relationship between the rate of material removal and the mechanical properties of the workpiece together with the process parameters. The rolling, indenting, and scratching modes of materials removal are considered with a simple stochastic approach. The model provides us with the basis for improving the efficiency of the wiresaw manufacturing process based on the process parameters.

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