Browse Topic: Advanced manufacturing
Fused deposition modeling (FDM) is a rapidly growing additive manufacturing method employed for printing fiber-reinforced polymer composites. Nonetheless, the performance of printed parts is often constrained by inherent defects. This study investigates how the varying annealing parameter affects the tribological properties of FDM-produced polypropylene carbon fiber composites. The composite pin specimens were created in a standard size of 35 mm height and 12 mm diameter, based on the specifications of the tribometer pin holder. The impact of high-temperature annealing process parameters are explored, specifically annealing temperature and duration, while maintaining a fixed cooling rate. Two set of printed samples were taken for post-annealing at temperature of 85°C for 60 and 90 min, respectively. The tribological properties were evaluated using a dry pin-on-disc setup and examined both pre- (as-built) and post-annealing at temperature of 85°C for 60 and 90 min printed samples
Additive Manufacturing (AM), specifically Fused Deposition Modeling (FDM), has become a highly promising method for creating intricate shapes using different materials. Polyethylene Terephthalate Glycol (PETG) is a highly utilized thermoplastic that is recognized for its exceptional strength, resistance to chemicals, and effortless processing. This study aims to optimize the process parameters of the FDM technique for PETG material using Taguchi Grey Relational Analysis (GRA). An empirical study was carried out to examine the impact of various FDM process parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on important outcome variables like dimensional accuracy, surface quality, and mechanical properties. The Taguchi method was used to systematically design a series of experiments, while GRA was used to optimize the process parameters and performance characteristics. The results unveiled the most effective parameter combinations for attaining
Additive Manufacturing (AM), specifically Fusion Deposition Modeling (FDM), has transformed the manufacturing industry by allowing the creation of complex structures using a wide range of materials. The objective of this study is to enhance the FDM process for Thermoplastic Polyurethane (TPU) material by utilizing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) optimization method. The study examines the influence of FDM parameters, such as layer height, nozzle temperature, and infill density, on important characteristics of the printing process, such as tensile strength, flexibility, and surface finish. The collection of experimental data is achieved by conducting systematic FDM printing trials that cover a variety of parameter combinations. The TOPSIS optimization method is utilized to determine the optimal parameter settings by evaluating each parameter combination against the ideal and anti-ideal solutions. This method determines the optimal parameter
Additive Manufacturing (AM), specifically Fused Deposition Modeling (FDM), has become a revolutionary technology for creating intricate shapes using different materials. Polylactic Acid (PLA) is a biodegradable thermoplastic that is commonly used in additive manufacturing (AM) because of its environmentally friendly properties, affordability, and ease of use. The objective of this study is to optimize the FDM parameters for PLA material and create predictive models using the Adaptive Neuro-Fuzzy Inference System (ANFIS) to forecast printing performance. An investigation was carried out through experimental trials to examine the impact of important FDM parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on critical outcomes such as dimensional accuracy, surface finish, and mechanical properties. The utilization of design of experiments (DOE) methodology enabled a methodical exploration of parameters. A predictive model using ANFIS was created to
Additive Manufacturing (AM), specifically Fused Deposition Modeling (FDM), has transformed the manufacturing industry by allowing the creation of intricate shapes using different materials. Polylactic Acid (PLA) is a biodegradable thermoplastic that is commonly used in additive manufacturing (AM) because of its environmentally friendly nature, affordability, and ease of processing. This study aims to optimize the parameters of Fused Deposition Modeling (FDM) for PLA material using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach. The researchers performed experimental trials to examine the impact of important FDM parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on critical outcomes, including dimensional accuracy, surface finish, and mechanical properties. The methodology of design of experiments (DOE) enabled a systematic exploration of parameters. The TOPSIS approach, a technique for making decisions
Researchers have developed a printing process that prints strong nonmetallic materials in record time — five times faster than traditional 3D printing. The process, called SWOMP, which stands for Selective dual-wavelength Olefin metathesis 3D printing, uses dual-wavelength light, unlike the traditional printing process
Researchers at the Johns Hopkins Applied Physics Laboratory have developed a machine learning method that could have a huge impact on understanding how material is formed during the additive manufacturing process. John Hopkins Applied Physics Laboratory, Laurel, MD Researchers at the Johns Hopkins Applied Physics Laboratory (APL) in Laurel, Maryland, have demonstrated a novel approach for applying machine learning to predict microstructures produced by a widely used additive manufacturing technique. Their approach promises to dramatically reduce the time and cost of developing materials with tailored physical properties and will soon be implemented on a NASA-funded effort focused on creation of a digital twin. “We anticipate that this new approach will be extremely impactful in helping design and understand material formation during additive manufacturing processes, and this fits into our overarching strategy focused on accelerating materials development for national security,” said
As “point of need” additive manufacturing emerges as a priority for the Department of Defense (DoD), Australian 3D printing provider SPEE3D is one of several companies demonstrating that its machines can rapidly produce castings, brackets, valves, mountings and other common replacement parts and devices that warfighters often need in an on-demand schedule when deployed near or directly within combat zones. DoD officials describe point of need manufacturing as a concept of operations where infantry and squadron have the equipment, machines, tools and processes to rapidly 3D print parts and devices that are being used in combat. Based in Melbourne, Australia, SPEE3D provides cold spray additive manufacturing (CSAM) machines that use a combination of robotics and high-speed kinetic energy to assemble and quickly bind metal together into 3D-printed parts without the need for specific environmental conditions or post-assembly cooling or temperature requirements. Over the last two years, the
Honda has long been at the cutting edge of mobility and tech, with everything from the Asimo robot of 20 years ago to plans for reusable rockets to launch lightweight satellites into orbit. During a Tech Day event in early October in Tochigi, Japan, the Japanese automaker announced further details of its upcoming Honda 0 architecture (Honda calls it “Honda Zero” but writes it with the number), its first in-house electric platform designed from the ground up. Honda also discussed some of the advanced manufacturing techniques it's pioneering to reach its core design and technology tenants
ABSTRACT This paper focuses on the application of a novel Additive Molding™ process in the design optimization of a combat vehicle driver’s seat structure. Additive Molding™ is a novel manufacturing process that combines three-dimensional design flexibility of additive manufacturing with a high-volume production rate compression molding process. By combining the lightweighting benefits of topology optimization with the high strength and stiffness of tailored continuous carbon fiber reinforcements, the result is an optimized structure that is lighter than both topology-optimized metal additive manufacturing and traditional composites manufacturing. In this work, a combat vehicle driver’s seatback structure was optimized to evaluate the weight savings when converting the design from a baseline aluminum seat structure to a carbon fiber / polycarbonate structure. The design was optimized to account for mobility loads and a 95-percentile male soldier, and the result was a reduction in
ABSTRACT A 3D printed battery bracket is strengthened via post-print thermal annealing, demonstrating a transitionable approach for additive manufacturing of robust, high performance thermoplastic components. Citation: E. D. Wetzel, R. Dunn, L. J. Holmes, K. Hart, J. Park, and M. Ludkey, “Thermally Annealed, High Strength 3D Printed Thermoplastic Battery Bracket for M998,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 16-18, 2022
ABSTRACT The United States Army is leveraging Advanced Manufacturing (AdvM) methods to solve both operational and tactical readiness gaps. AdvM includes not only Additive Manufacturing (AM), but also traditional manufacturing capabilities in the field and at Army production facilities. The Tank-Armaments and automotive Command (TACOM) and the Ground Vehicles Systems Center (GVSC) Materials-AdvM Branch have developed a strategy of five critical path key words oriented on three Lines of Effort (LOE) that enables a disciplined process to deliver final use qualified parts manufactured by the Organic Industrial Base (OIB) as an alternate source of supply that will improve readiness of TACOM’s combat and tactical wheeled fleets. Additionally, an alternate critical path has been developed to provide limited use parts for Battle Damage and Repair (BDAR). Citation: P. Burton, N. Kott, A. Kruz, A. Batjer, “Path to 450 Parts Qualified for Advanced Manufacturing”, In Proceedings of the Ground
ABSTRACT Gas metal arc pulse directed energy deposition (GMA-P DED) offers large-scale additive manufacturing (AM) capabilities and lower cost systems compared to laser or electron beam DED. These advantages position GMA-DED as a promising manufacturing process for widespread industrial adoption. To enable this “digital” manufacturing of a component from a computer-aided design (CAD) file, a computer-aided manufacturing (CAM) solver is necessary to generate build plans and utilize welding parameter sets based on feature and application requirements. Scalable and robot-agnostic computer-aided robotics (CAR) software is therefore essential to provide automated toolpath generation. This work establishes the use of Autodesk PowerMill Ultimate software as a CAM/CAR solution for arc-based DED processes across robot manufacturers. Preferred aluminum GMA-P DED welding parameters were developed for single-pass wide “walls” and multi-pass wide “blocks” that can be configured to build a wide
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