2023 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2023): Wire-fed DED: Geometric and Path Optimization
Program Organizers: Joseph Beaman, University of Texas at Austin
Monday 1:30 PM
August 14, 2023
Room: 615 AB
Location: Hilton Austin
Session Chair: Somayeh Pasebani, Oregon State University
1:30 PM
A Spherical Test Artifact to Evaluate Three-dimensional Form Accuracy for Wire Arc Additive Manufacturing: Sakufu Ko1; Takayuki Sagawa1; Yuka Yamagata1; Shigeru Aoki1; Takeyuki Abe2; 1Institute of Technology, Shimizu Corporation; 2Saitama University
Additive manufacturing, including the wire arc additive manufacturing (WAAM), is gradually gaining attraction and providing benefits in the aerospace and construction industries. In both industries, large-scale manufacturing capability and quality consistency of manufactured 3D parts are crucial. As part of quality evaluation, test artifacts for the geometric capability assessment are specified in ISO/ASTM52902-2019(E). On the other hand, the test artifact for curved wall is left undefined. This paper proposes a sphere shape wall as a representative of three-dimensional shapes that are supportless and feature large overhangs, for testing the geometric capability. A universally applicable mechanical configuration and deposition strategy for depositing large scale curved walls, is proposed. A quality evaluation process for the sphere deposition was also described and experimentally demonstrated.Keywords: Wire arc additive manufacturing (WAAM), Test artifact, Inspection method, Sphere.
1:50 PM
Hybrid Metal Manufacturing of Large Freeform Geometries: Bradley Jared1; Ross Zameroski1; Joshua Penney1; Aaron Cornelius1; Tiffany Quigley1; Devon Goodspeed1; Eduardo Miramontes1; Tony Schmitz1; William Hamel1; 1University Of Tennessee, Knoxville
The timely fabrication of large, complex metallic structures is a persistent challenge for America’s industrial base as schedules for large parts, i.e one to two feet cube and larger, are routinely defined in months and years; introducing unacceptable risk and cost for most products. On-going work is addressing these challenges using a large-scale hybrid metal manufacturing system which combines multi-material metal inert gas (MIG) deposition, robotic fringe projection scanning metrology, part handling and five-axis machining. The integration, capabilities, challenges and operation of the hybrid process flow will be demonstrated through the processing of multiple structures. Geometric control of final part shape is a research focus as work is addressing multiple elements associated with part distortion due to internal stresses, complex geometry path planning, real-time process monitoring and control, and finish machining.
2:10 PM
In-situ Geometric Characterization via Embedded 3D Scanning and Implicit Modeling: Tadeusz Kosmal1; Samuel Pratt1; Christopher Williams1; 1Virginia Tech DREAMS Lab
Additive Manufacturing’s (AM) layer-wise construction is susceptible to intrinsic process variation and fabrication errors. In-situ monitoring techniques have been proposed to detect errors, but limit inspection to a localized deposition or final part state, failing to capture how formed layers change throughout processing. Embedded 3D scanning can address these limitations, yet conducting layer-wise evaluation of high-resolution scans presents significant data management and optical challenges for compatibility with a production environment. We present a novel methodology to rapidly capture and characterize error using a digitally integrated Structured Light Scanning (SLS) system and Signed Distance Function (SDF) approach. Using this approach, in-situ deviation of printed structures can be analyzed within seconds over relatively large areas (250 cm2) at a high spatial resolution (0.3mm). The proposed method is process agnostic and is validated in a layer-by-layer analysis of hybrid Wire-Arc AM processing.
2:30 PM
Multi-bead and Multilayer Printing Geometric Defect Identification Using Single Bead Trained Models: Nowrin Akter Surovi1; Gim Song Soh1; 1SUTD
In Wire Arc Additive Manufacturing (WAAM), a geometric defect is a defect that creates voids in the final printed part due to incomplete fusion between two non-uniform overlapping bead segments. Such a defect poses the onset of a severe problem during multi-bead prints. In our earlier work, a methodology has been developed to construct machine learning (ML)-based models to identify geometrically defective bead segments using acoustic signals. In this paper, we investigate the performance of these single-bead segments trained defect detection model scalability for identifying voids during multi-bead prints. A comparative study of the performance of a variety of ML models is explored based on Inconel 718 material block printing. The results show that the single bead segments-based defect identification model can identify defective and non-defective segments in multi-bead printing effectively.
2:50 PM
The WAAM Number: A Dimensionless Number for Predicting Wire Arc Additive Manufacturing Bead Geometry: Bemnet Molla1; Christopher Williams1; 1Virginia Polytechnic Institute and State University
Wire Arc Additive Manufacturing (WAAM) has many process parameters with complex interactions in the formed melt pool that affect its ability to obtain consistent depositions. This work introduces a novel dimensionless number, the WAAM Number, that characterizes bead geometry by encapsulating multiple process parameters, including ac voltage, arc current, mass flow rate, travel speed, and intrinsic material properties into a single independent variable. This WAAM number presents a generalizable representation for predicting bead geometry, width, and height, and can be applied across multiple materials, welding modes, and WAAM systems. The utility of the WAAM number for characterizing and predicting bead geometry is validated through analysis of single-track depositions of Al5Mg and mild steel using two short circuit welding modes on two separate WAAM machines.
3:10 PM Break
3:40 PM
Dynamic Start Point Modification in Closed Contour Toolpaths for A Multi-robot Wire-fed Ded System: Christopher Masuo1; Andrzej Nycz1; Peter Wang1; Joshua Vaughan1; Alex Walters1; William Carter1; Luke Meyer1; Riley Wallace1; Jonathan Paul2; Jason Flamm2; 1Oak Ridge National Laboratory; 2Lincoln Electric
A multi-robot wire-fed directed energy deposition (DED) system can exceed the production rate seen in a standard single wire-fed DED robot. Multiple robots can deposit material simultaneously and collaborate with each other to effectively produce a large-scaled additive part. This, however, introduces the challenge of proper toolpath assignment for each robot to ensure that the robots would not interfere with each other. Pre-processed toolpaths, dynamic toolpath assignment, and region-of-interest (ROI) can eliminate this challenge. However, this can still result in long idle times for most robots solely based on their toolpath start points. In this work, a dynamic start point modification algorithm was developed to improve the utilization of the robots. A case-study was conducted to compare production efficiencies with and without using this algorithm.
4:00 PM
Optimal Planning and Control for Microhardness Demonstrated in Thin-walled Steel Parts Made via Wire Arc Additive Manufacturing: Mikhail Khrenov1; P. Chris Pistorius1; Sneha Narra1; 1Carnegie Mellon University
High power inputs and changing geometries induce highly transient and dynamic thermal histories over parts produced by Wire Arc Additive Manufacturing (WAAM). This, in turn, results in uncontrolled in-situ heat treatments and varying properties, such as differences in hardness, across the final part. This work proposes and demonstrates the application of optimal planning techniques, utilized to great effect in fields such as aerospace engineering and robotics, to control these outcomes. The dynamics of temperature and hardness evolution are modeled using physics-based techniques informed by in-situ data. These are used to solve a joint trajectory optimization problem for desired outcomes. State estimation and feedback control is employed to track the resultant solutions during fabrication. Control of hardness by the combined system is experimentally verified. This work has the potential to advance the use of WAAM for mission-critical parts, while also laying the foundation for similar developments in large-scale additive manufacturing broadly.
4:20 PM
Exploring the Effects of Oscillatory Deposition Paths on Wire Arc Additive Manufacturing (WAAM) of Al5Mg: Bemnet Molla1; Christopher Williams1; 1Virginia Polytechnic Institute and State University
Wire Arc Additive Manufacturing (WAAM) is a relatively low-cost, high throughput additive manufacturing technology that uses arc welding to deposit metal beads in a layer-wise fashion to produce large-scale, complex parts. WAAM toolpathing strategies commonly feature overlapping linear deposition paths, which result in a high number of thermal cycles and internal porosity defects that can reduce final part performance. Traditional arc welding for joining utilizes oscillatory paths to increase productivity and improve mechanical performance of the weld. The use of oscillatory paths in WAAM is underreported in literature; no prior work has explored how oscillatory path geometries effect part quality. This work analyzes the effects of a variety of single-track and multi-layer oscillatory path geometries on the bead geometry, energy input, mechanical performance, and grain structure of Al5Mg produced by WAAM.
5:00 PM
Resource Efficiency of the Robot-based Hybrid Additive Manufacturing Chain: Cornelia Tepper1; Jonathan Utsch1; Jonas Zarges1; Matthias Weigold1; 1PTW TU Darmstadt
Combining additive and subtractive metal processes to a hybrid additive manufacturing chain not only enables the production of parts with application-oriented design but also leads to increased resource efficiency especially when combined in an industrial robotic cell. Compared to parts manufactured through subtractive processes from full material the hybrid additive manufacturing chain is considered to be resource efficient due to reduced material consumption. However, the energy consumption of the hybrid additive processes is considered higher because of the use of laser for the additive process. It is assumed that the decreased material consumption outweighs the higher energy consumption regarding the resource efficiency but until now it is not investigated. Therefore, in this paper the resource consumption of the robot-based hybrid additive manufacturing chain including the wire based direct energy deposition process and the milling process is analysed through measurements during experiments and compared to subtractive processes using the carbon footprint.
4:40 PM
GKN Aerospace Deposition of a Laser Wire DED 2.5m Titanium Aerostructure Demonstrator: Leon Hill1; Jeremy Tylenda1; 1GKN Aerospace
GKN Aerospace in collaboration with Northrop Grumman deposited a large scale titanium aerostructure representative of a primary air vehicle structure. The titanium laser wire directed energy deposition (DED) preform measures approximately 8 feet (2.5 meters) and is the largest additively manufactured aerostructure produced by GKN Aerospace to date. The demonstration article utilized novel toolpathing techniques to manage thermal history and distortion concurrently. In addition, the deposition was completed first-time-right using GKN’s proprietary adaptive closed loop control systems to maintain build quality throughout the deposition. This milestone demonstrates cutting-edge manufacturing technology to build large primary aerostructures for future air vehicles. This presentation will shares the whole story of adaptive closed loop control, toolpath, and thermal history management to deposit a preform of this monumental scale. Link to public press release:https://www.gknaerospace.com/en/newsroom/news-releases/2022/gkn-aerospace---northrop-grumman-collaboration-achieves-additive-manufacturing-milestone/