Browse Topic: Rapid prototyping

Items (523)
Over the decades, robotics deployments have been driven by the rapid in-parallel research advances in sensing, actuation, simulation, algorithmic control, communication, and high-performance computing among others. Collectively, their integration within a cyber-physical-systems framework has supercharged the increasingly complex realization of the real-time ‘sense-think-act’ robotics paradigm. Successful functioning of modern-day robots relies on seamless integration of increasingly complex systems (coming together at the component-, subsystem-, system- and system-of-system levels) as well as their systematic treatment throughout the life-cycle (from cradle to grave). As a consequence, ‘dependency management’ between the physical/algorithmic inter-dependencies of the multiple system elements is crucial for enabling synergistic (or managing adversarial) outcomes. Furthermore, the steep learning curve for customizing the technology for platform specific deployment discourages domain
Varpe, Harshal BabsahebColeman, JohnSalvi, AmeyaSmereka, JonathonBrudnak, MarkGorsich, DavidKrovi, Venkat N
Fused Deposition Modeling (FDM) is a widely recognized additive manufacturing method that is highly regarded for its ability to create complex structures using thermoplastic materials. Thermoplastic Polyurethane (TPU) is a highly versatile material known for its flexibility and durability. TPU has several applications, including automobile instrument panels, caster wheels, power tools, sports goods, medical equipment, drive belts, footwear, inflatable rafts, fire hoses, buffer weight tips, and a wide range of extruded film, sheet, and profile applications.. The primary objective of this study is to enhance the FDM parameters for TPU material and construct regression models that can accurately forecast printing performance. The study involved conducting experimental trials to examine the impact of key FDM parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on critical responses, including dimensional accuracy, surface quality, and mechanical
Pasupuleti, ThejasreeNatarajan, ManikandanSagaya Raj, GnanaSilambarasan, RKiruthika, Jothi
Fused Deposition Modeling (FDM) is a highly adaptable additive manufacturing method that is extensively employed for creating intricate structures using a range of materials. Thermoplastic Polyurethane (TPU) is a highly versatile material known for its flexibility and durability, making it well-suited for use in industries such as footwear, automotive, and consumer goods. Hoses, gaskets, seals, external trim, and interior components are just a few of the many uses for thermoplastic polyurethanes (TPU) in the automobile industry. The objective of this study is to enhance the performance of Fused Deposition Modeling (FDM) by optimizing the parameters specifically for Thermoplastic Polyurethane (TPU) material. This will be achieved by employing a Taguchi-based Grey Relational Analysis (GRA) method. The researchers conducted experimental trials to examine the impact of key FDM parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on critical responses
Pasupuleti, ThejasreeNatarajan, ManikandanRamesh Naik, MudeSilambarasan, RD, Palanisamy
Additive Manufacturing (AM), particularly Fused Deposition Modeling (FDM), has emerged as a revolutionary method for fabricating complex geometries using a variety of materials. Polyethylene terephthalate glycol (PETG) is a thermoplastic material that is biodegradable and environmentally friendly, making it a preferred choice in additive manufacturing (AM) due to its affordability and ease of use. This study aims to optimize the FDM settings for PETG material and investigate the impact of key process parameters on printing performance. An experimental study was conducted to evaluate the influence of crucial factors in FDM, including layer thickness, infill density, printing speed, and nozzle temperature, on significant outcomes such as dimensional accuracy, surface quality, and mechanical properties. The use of the Grey Relational Analysis (GRA) approach enabled a systematic assessment of multi-performance characteristics, facilitating the optimization of the FDM process. The findings
Pasupuleti, ThejasreeNatarajan, ManikandanKumar, VKiruthika, JothiKatta, Lakshmi NarasimhamuSilambarasan, R
Fused Deposition Modeling (FDM), a form of Additive Manufacturing (AM), has emerged as a groundbreaking technology for the production of complex shapes from a variety of materials. Acrylonitrile Butadiene Styrene (ABS) is an opaque thermoplastic that is frequently employed in additive manufacturing (AM) due to its affordability and user-friendliness. The purpose of this investigation is to enhance the FDM parameters for ABS material and develop predictive models that anticipate printing performance by employing the Adaptive Neuro-Fuzzy Inference System (ANFIS). Through experimental trials, an investigation was conducted to evaluate the influence of critical FDM parameters, including layer thickness, infill density, printing speed, and nozzle temperature, on critical outcomes, including mechanical properties, surface polish, and dimensional accuracy. The utilization of design of experiments (DOE) methodology facilitated a systematic examination of parameters. A predictive model was
Natarajan, ManikandanPasupuleti, ThejasreeKumar, VKiruthika, JothiKatta, Lakshmi NarasimhamuSilambarasan, R
In recent years, Additive Manufacturing (AM), more especially Fused Deposition Modeling (FDM), has emerged as a very promising technique for the production of complicated forms while using a variety of materials. Polyethylene Terephthalate Glycol, sometimes known as PETG, is a thermoplastic material that is widely used and is renowned for its remarkable strength, resilience to chemicals, and ease of processing. Through the use of Taguchi Grey Relational Analysis (GRA), the purpose of this investigation is to improve the process parameters of the FDM technology for PETG material. In order to investigate the influence that several FDM process parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, have on significant outcome variables, such as dimensional accuracy, surface quality, and mechanical qualities, an empirical research was conducted. For the purpose of constructing the regression prediction model, the obtained dataset is used to make
Natarajan, ManikandanPasupuleti, ThejasreeShanmugam, LoganayaganKatta, Lakshmi NarasimhamuSilambarasan, RKiruthika, Jothi
Soft-bending actuators are gaining considerable attention in robotics for handling delicate objects and adapting to complex shapes, making them ideal for biomimetic robots. Soft pneumatic actuators (SPAs) are preferred in soft robotics because to their safety and compliance characteristics. Using negative pressure for actuation, it enhances stability by reducing the risk of sudden or unintended movements, crucial for delicate handling and consistent performance. Negative pressure actuation is more energy-efficient, safe and are less prone to leakage, increasing reliability and durability. This paper involves development of a new soft pneumatic actuator design by comparing various designs and to determine its performance parameters. This paper depicts on designing, and fabricating flexible soft pneumatic actuators working under negative pressure for soft robotic applications. The material used for fabrication was liquid silicone rubber and uniaxial tensile tests were conducted to
Warriar J S, SreejithSadique, AnwarGeorge, Boby
Additive Manufacturing (AM), particularly Fused Deposition Modeling (FDM), has revolutionized the manufacturing sector by enabling the production of complex geometries using various materials. Polylactic Acid (PLA) is a biodegradable thermoplastic often used in additive manufacturing (AM) because to its eco-friendliness, cost-effectiveness, and processing simplicity. This research seeks to enhance the parameters of Fused Deposition Modeling (FDM) for PLA material with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methodology. The researchers conducted experimental trials to investigate the influence of key FDM parameters, including layer thickness, infill density, printing speed, and nozzle temperature, on essential outcomes such as dimensional accuracy, surface quality, and mechanical qualities. The design of experiments (DOE) technique facilitated a systematic investigation of parameters. The TOPSIS method, a decision-making tool based on several
Natarajan, ManikandanPasupuleti, ThejasreeC, NavyaKiruthika, JothiSilambarasan, R
PEM electrolysis system has characteristic of excellent performance such as fast response, high electrolysis efficiency, compact design and wide adjustable power range. It provides a sustainable solution for the production of hydrogen, and is well suited to couple with renewable energy sources. In the development process of PEM electrolysis controller, this article originally applied the V-mode development process, including simulation modeling, RCP testing, and HIL testing, which can provide guidance in the practical application of electrolytic hydrogen production. In this paper, we present modeling and simulation study of PEM water electrolysis system. Model of electrolytic cell, hydrogen production subsystem and thermal management subsystem are constructed in Matlab/Simulink. Controller model was designed based on PI control strategy. A rapid prototyping controller with MPC5744 chip was used to develop the control system of electrolytic hydrogen production system. Hardware in the
Hua, YuweiJin, ZhenhuaTian, YingTao, Yuepeng
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
Nallasivam, J.D.Sundararaj, S.Kandavalli, Sumanth RatnaPradab, R.
3-Dimensional (3D) printing is an additive manufacturing technology that deposits materials in layers to build a three-dimensional component. Fused Deposition Modelling (FDM) is the most widely used 3D printing technique to produce the thermoplastic components. In FDM, the printing process parameters have a major role in controlling the performance of fabricated components. In this study, carbon fibre reinforced polymer composites were fabricated using FDM technique based on Taguchi's Design of experimental approach. The matrix and reinforcement materials were poly-lactic acid (PLA) and short carbon fibre, respectively. The goal of this study is to optimize the FDM process parameters in order to obtain the carbon fibre reinforced PLA composites with enhanced hardness and compressive strength values. Shore-D hardness and compression tests were carried out as per American Society for Testing and Materials (ASTM) D2240 and ASTM D695 standards respectively, to measure the output responses
Sugumar, SureshDhamodaran, GopinathSeetharaman, PradeepkumarSivakumar, Rajkamal
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
Natarajan, ManikandanPasupuleti, ThejasreeKiruthika, JothiKatta, Lakshmi NarasimhamuSilambarasan, R.
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
Pasupuleti, ThejasreeNatarajan, ManikandanKiruthika, JothiRamesh Naik, MudeSilambarasan, R
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
Natarajan, ManikandanPasupuleti, ThejasreeKiruthika, JothiD, PalanisamySilambarasan, R
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
Pasupuleti, ThejasreeNatarajan, ManikandanKiruthika, JothiRamesh Naik, MudeSilambarasan, R
Additive Manufacturing (AM) techniques, particularly Fusion Deposition Modeling (FDM), have received considerable interest due to their capacity to create complex structures using a diverse array of materials. The objective of this study is to improve the process control and efficiency of Fused Deposition Modeling (FDM) for Thermoplastic Polyurethane (TPU) material by creating a predictive model using an Adaptive Neuro-Fuzzy Inference System (ANFIS). The study investigates the impact of FDM process parameters, including layer height, nozzle temperature, and printing speed, on key printing attributes such as tensile strength, flexibility, and surface quality. Several experimental trials are performed to gather data on these parameters and their corresponding printing attributes. The ANFIS predictive model is built using the collected dataset to forecast printing characteristics by analyzing input process parameters. The ANFIS model utilizes the learning capabilities of neural networks
Pasupuleti, ThejasreeNatarajan, ManikandanD, PalanisamyA, GnanarathinamUmapathi, DKiruthika, Jothi
In this study, we investigate the optimization of additive manufacturing (AM) parameters using a bi-objective optimization approach through the non-dominated sorting genetic algorithm II (NSGA-II). The objectives are to minimize build time and maximize mechanical strength. Experimental evaluations are conducted on various process parameters, including layer thickness, build orientation, and infill density, with a focus on their impact on build time and mechanical properties. Optimal parameter combinations, such as the lowest layer thickness, vertical build orientation, and relatively low fill density, are identified for maximizing tensile strength while minimizing build time. The consistency between experimental results and those obtained through NSGA-II validation validates the reliability of the optimization approach. Overall, this study contributes to the advancement of AM by providing insights into efficient parameter optimization strategies for enhancing both efficiency and
EL Azzouzi, AdilZaghar, HamidZiat, AbderazzakLarbi, Lasri
Smaller than a coin, this optical device could enable rapid prototyping on the go. Massachusetts Institute of Technology, Cambridge, MA Imagine a portable 3D printer you could hold in the palm of your hand. The tiny device could enable a user to rapidly create customized, low-cost objects on the go, like a fastener to repair a wobbly bicycle wheel or a component for a critical medical operation. Researchers from MIT and the University of Texas at Austin took a major step toward making this idea a reality by demonstrating the first chip-based 3D printer. Their proof-of-concept device consists of a single, millimeter-scale photonic chip that emits reconfigurable beams of light into a well of resin that cures into a solid shape when light strikes it.
This research systematically explores the significant impact of geometrical dimensions within fused deposition modeling (FDM), with a focus on the influence of raster angle and interior fill percentage. Through meticulous experimentation and the application of response surface modeling (RSM), the influence on critical parameters such as weight, length, width at ends, width at neck, thickness, maximum load, and elongation at tensile strength is thoroughly analyzed. The study, supported by ANOVA, highlights the notable effects of raster angle and interior fill percentage, particularly on width at ends, width at neck, and thickness. During the optimization phase, specific parameters—precisely, a raster angle of 31.68 and an interior fill percentage of 27.15—are identified, resulting in an exceptional desirability score of 0.504. These insights, substantiated by robust statistical data, fill a critical gap in the understanding of 3D-printed parts, offering practical recommendations for
Moradi, MahmoudRezayat, MohammadMeiabadi, SalehRasoul, Fakhir A.Shamsborhan, MahmoudCasalino, GiuseppeKaramimoghadam, Mojtaba
This study aims to explore the wear characteristics of fused deposition modeling (FDM) printed automotive parts and techniques to improve wear performance. The surface roughness of the parts printed from this widely used additive manufacturing technology requires more attention to reduce surface roughness further and subsequently the mechanical strength of the printed geometries. The main aspect of this study is to examine the effect of process parameters and annealing on the surface roughness and the wear rate of FDM printed acrylonitrile butadiene styrene (ABS) parts to diminish the issue mentioned above. American Society for Testing and Materials (ASTM) G99 specified test specimens were fabricated for the investigations. The parameters considered in this study were nozzle temperature, infill density, printing velocity, and top/bottom pattern. The hybrid tool, i.e., GA–ANN (genetic algorithm–artificial neural network) has been opted to train, predict, and optimize the surface
Narang, RajanKaushik, AshishDhingra, Ashwani KumarChhabra, Deepak
In this paper, experimental studies were conducted to examine the mechanical behavior of a polymer composite material called polyamide with glass fiber (PA6-GF), which was fabricated using the three-dimensional (3D) fusion deposition modeling (FDM) technique. FDM is one of the most well-liked low-cost 3D printing techniques for facilitating the adhesion and hot melting of thermoplastic materials. PA6 exhibits an exceptionally significant overall performance in the families of engineering thermoplastic polymer materials. By using twin-screw extrusion, a PA6-GF mixed particles made of PA6 and 20% glass fiber was produced as filament. Based on literature review, the samples have been fabricated for tensile, hardness, and flexural with different layer thickness of 0.08 mm, 0.16 mm, and 0.24 mm, respectively. The composite PA6-GF behavior is characterized through an experimental test employing a variety of test samples made in the x and z axes. The mechanical and physical characteristics of
Sivanesh, A. R.Soundararajan, R.Natrayan, M.Nallasivam, J. D.Santhosh, R.
Fiber reinforced additive manufacturing (FRAM) is a fused deposition modelling (FDM) additive manufacturing (AM) process which produces composite print layers - polymer matrix and reinforcing fiber. This work proposes a novel method which utilizes FRAM design freedom and simultaneously optimizes 3D print orientation and component topology to improve the response of a mass minimization problem statement. The method is robust and is designed to solve industry-applicable problem statements (mass minimization) with complex geometry and loading. Design sensitivities of 3D print orientation design variables, (θ1, θ2, θ3), are calculated using finite differencing and gradient descent is used to converge to an optimized print orientation. Changing 3D print orientation alters anisotropic material properties to improve the structural response of the component in the prescribed load-cases. The numerical method optimizes the anisotropic material properties of the component and concurrently
Ray, NoahKim, Il Yong
This article explores the impact of As-built versus annealed Fused Deposition Modeling (FDM) on the mechanical properties of test samples fabricated from two distinct materials: Polyamide 6 (PA6) and PA6 with carbon fiber filament. Employing the FDM technique, these samples were meticulously produced, with significant process parameters maintained at optimal values. Two sets of printed specimens were prepared for examination, one composed of PA6 and the other of PA6 with carbon fiber (CF) reinforcement. The first set was subjected to mechanical testing in its As-built condition, while the second set underwent an annealing process utilizing a muffle furnace. The annealing reduces internal stresses, enhances interlayer adhesion, and promotes crystallinity. For both the sent samples exposed to comprehensive assessments to evaluate various mechanical performance attributes, including hardness, impact strength, tensile strength and flexural strength. The results of this study elucidate that
Raja, R.Arun Kumar, K.Jannet, SabithaNarasimharaj, V.
Additive manufacturing (AM) is a common way to make things faster in manufacturing era today. A mix of polypropylene (PP) and carbon fiber (CF) blended filament is strong and bonded well. Fused deposition modeling (FDM) is a common way to make things. For this research, made the test samples using a mix of PP and CF filament through FDM printer by varying infill speed of 40 meters per sec 50 meters per sec and 60 meters per sec in sequence. The tested these samples on a tribometer testing machine that slides them against a surface with different forces (from 5 to 20 N) and speeds (from 1 to 4 meters per sec). The findings of the study revealed a consistent linear increase in both wear rate and coefficient of friction across every sample analyzed. Nevertheless, noteworthy variations emerged when evaluating the samples subjected to the 40m/s infill speed test. Specifically, these particular samples exhibited notably lower wear rates and coefficients of friction compared to the remaining
Surendra, S.Sireesha, S.C.P., SivaSuresh, P.
Recent years have demonstrated the fragility of both military and nonmilitary supply chains. Through biotechnology and biomanufacturing, the Department of Defense (DoD) can use readily available feedstocks to onshore manufacturing of chemicals and materials critical to defense needs and to create advanced materials with enhanced capabilities. Development of DoD’s biotechnology and biomanufacturing capabilities will help secure the defense supply chain and contribute to a force that is sustainable, resilient, survivable, agile, and responsive. To accelerate the advancement of biotechnology and biomanufactured products, the Department launched the Tri-Service Biotechnology for a Resilient Supply Chain (T-BRSC) program in Fiscal Year 2022. T-BRSC is creating a pipeline for advanced development and transition of biomanufactured materials to support defense supply chain resilience. The effort brings together Joint Service partners to leverage significant advances made over the last decade
Wolfson, Benjamin R.Knott, Steve K.Maul, Steve J.Pietsch, Hollie A.Podolan, Kyle S.Thomas, Nick H.Hung, Chia-SueiGupta, Maneesh K.Kelley-Loughnane, NancyMalanoski, Anthony P.Glaven, Sarah M.Gibbons, Henry S.
A digital twin is a virtual model that accurately imitates a physical asset. This can be as complex as an entire vehicle, a subsystem, and down to a small functioning component. The digital twin has a level of fidelity that aligns to the goals of the project team. The usage of a digital twin inside a digital engineering (DE) ecosystem permits architecture and design decisions for optimized product behavior, performance, and interactions. This paper demonstrates a methodology to incorporate the digital twin concept from requirement analysis, low fidelity feature level simulation, rapid prototypes running inside a System Integration Lab, and high fidelity virtual prototypes executing in an entirely virtual environment.
Kanon, Robert J.Griffin, Kevin W.Fernando, RaveenShah, AmirKouba, RussFeury, Mark
The Software Production Factory (SPF) is a cyber physical construct of computers, hardware and software integrated together to serve as an ideation and rapid prototyping environment. SPF is a virtual dynamic environment to analyze requirements, architecture, and design, assess trade-offs, test Ground Vehicle development artifacts such as structural and behavioral features, and deploy system artifacts and operational qualifications. SPF is utilized during the product development as well as during system operations and support. The white paper describes the components of the SPF to build relevant Ground Vehicle Rapid Prototyping (GVRP) models in accordance with the model-centric digital engineering process guidelines. The factory and the processes together ensure that the artifacts are produced as specified. The processes are centered around building, maintaining, and tracing single source of information from source all the way to final atomic element of the built system.
Thukral, AjayGriffin, Kevin W.Kanon, Robert J.
This paper presents the energy savings of an automated driving control applied to an electric vehicle based on the on-track testing results. The control is a universal speed planner that analytically solves the eco-driving optimal control problem, within a receding horizon framework and coupled with trajectory tracking lower-level controls. The automated eco-driving control can take advantage of signal phase and timing (SPaT) provided by approaching traffic lights via vehicle-to-infrastructure (V2I) communications. At each time step, the controller calculates the accelerator and brake pedal position (APP/BPP) based on the current state of the vehicle and the current and future information about the surrounding environment (e.g., speed limits, traffic light phase). The target vehicle is a Chevrolet Bolt, an electric vehicle, which is outfitted with a drive-by-wire (DBW) system that allows external APP/BPP to command the speed of the vehicle, while the operator remains in charge of the
JEONG, JongryeolDudekula, Ahammad BashaKandaswamy, ElangovanKarbowski, DominikHan, JihunNaber, Jeffrey
Purdue University researchers have developed a patent-pending method to add particles to filament and disperse them evenly through a traditional fused deposition modeling, or FDM, 3D printer, which will aid industry in manufacturing functional parts.
Regarding the development of an aircraft assembly process, this paper will illustrate the intelligent decision and policies of the aircraft assembly process based on technician experience. A model of the knowledge management system of the aircraft assembly process is developed to avoid the complexity of the entire aircraft or aircraft product assembly process. Firstly, According to the characteristics of the knowledge management system of the aircraft assembly process, the aircraft assembly process has been discussed to realize the decision of the aircraft assembly process. Secondly, intelligent decision-making in the aircraft assembly process has been established based on the knowledge management system and aircraft assembly process library that is oriented to the assembly process requirements employing an assembly process reasoning method. Finally, the intelligent decision policies of the aircraft assembly process are based on tacit knowledge, which is applied to the decision-making
Miah, Md HelalZhang, Jianhua
Point cloud objects have gained popularity in three-dimensional (3D) printing recently due to advancements in reverse engineering technology. Fabricating an object with a fused deposition modeling (FDM) printer requires converting the object to layered contours, which involves a slicing process. The slicing process of a point cloud object usually requires reconstructing a 3D object from a point cloud, which requires users’ deep understanding of 3D modeling software and a laborious work process. To avoid these problems, the direct slicing of point cloud objects is gaining more popularity. This research work proposes an adaptive slicing approach from point cloud objects directly without surface reconstruction. The adaptive slicing maintains the global geometry error while requiring a smaller number of fabrication layers and printing time. A new error profile used in the adaptive slicing approach is introduced. It approximates the geometry error from the point cloud directly based on the
Moodleah, SamartKirimasthong, Khwunta
Additive manufacturing produces parts by adding material layer by layer with respect to time based on a computerized 3D solid model. The design model of Robotic arm was prepared using the solid works. The various components such as fingers, gripper, etc., were created and connected. After meticulous mathematical calculations, the design features of the robotic arm, including force analysis, are arrived at, and the arm is prepared to be operated using Bluetooth. Major challenges were faced during conversion of the designed model to prototype model. Furthermore, the components were created utilising fast rapid prototyping, which is more efficient than other traditional approaches. This technology has been effectively used in the production of light weight prototypes, tooling and the development low-cost bespoke designs. Finally, all the parts are assembled with Bluetooth control systems and validated with payload up to maximum of 10kgfor lowering and lifting.
Ramaswamy, NakandhrakumarElumalai, SangeethkumarGoswami, SwapnanilRaja, SelvakumarVelmurugan, RamanathanVenkata Goutham, VuttiRamakrishnan, M
Avoiding the pitfalls of 3D printing requires knowing the process limitations - and how to work around them. An expert at a leading AM specialist shares insights on getting it right. As additive manufacturing (AM) technology and its applications expand, engineers are recognizing that different industrial 3D printing processes have different constraints that can affect designed parts in production. Some constraints are universal across the different processes, and some are more specific to the type of process used. It is thus essential to understand the technology you are working with to maximize its potential as a production method. With this understanding it is possible to design around the general limitations of AM as well as the specific process constraints that could impact a product or part. While design for manufacture (DfM) is not a new concept, the rules for designing for additive manufacture (DfAM) require design engineers to take a different approach. This article is
Allen, Nick
Engineers have created a highly effective way to paint complex 3D-printed objects, such as lightweight frames for aircraft and biomedical stents, that could save manufacturers time and money and provide new opportunities to create “smart skins” for printed parts.
Senior level military members are constantly evaluating risk and finding ways to articulate and mitigate risks on the battlefield. When it comes to new technology adoption and consideration, these same leaders must take a similar approach to justify spending taxpayer dollars and implementing new processes to improve operational outcomes.
When weight reduction is the primary goal, 3D-printed aluminum alloys are a frequent choice for aerospace and high-performance motorsports applications. Aluminum is much lighter than nickel alloys and has been particularly popular for laser powder-bed fusion (LPBF) because it’s good for prototyping and easy to post-process.
Fiber-reinforced polymer composites propose exceptional directional mechanical properties, and combining their advantages with the potential of 3D printing has resulted in many novel research fronts. Industries have started using 3D printed components which are rapidly replacing conventional material components in most of the industries. Carbon fiber reinforced Polylactic Acid (PLA) often finds its application in reasonably high loading conditions working at lesser speed like lightweight gears, spanners, nuts, and bolts. Wear reduction is an important factor that plays an important role in prolonging the component's life. Hence, it is crucial to optimize 3D printing parameters to get desired strength according to the application. The aim of this paper is to conduct the wear rate test on the Fused Deposition Modelled (FDM) printed carbon fiber reinforced PLA parts, to identify the optimum printing parameters which are crucial for wear reduction. Two process parameters i.e. fill density
Raja, KumarNaiju, CDM, Senthil KumarDessalegn, Naol
The utilization of Additive Manufacturing (AM) technology in the current manufacturing sector is growing day - by - day. This is made possible by the constant development of new materials and techniques to overcome the difficulties that are encountered while fabricating a part. In AM, parts are fabricated by laying successive layers on one another till the complete part is build. This gives AM an edge over conventional manufacturing. Even intricate or hollow parts can be fabricated with the same ease as fabricating a solid part. The key objective of this project is to evaluate and compare mechanical properties of Polyethylene Terephthalate - Glycol modified (PETG) and Carbon fiber reinforced Polyethylene Terephthalate - Glycol modified (CF - PETG), which are fabricated using Fused Deposition Modelling (FDM) process of AM. The ASTM standards D638 and D790 were followed for fabricating tensile test and Flexural test specimens respectively. Subsequently, fractured specimens are analyzed
Raja, KumarNaiju, CDSenthil Kumar, MKrishnan, PadmanabhanDessalegn, Naol
Marotta Controls Montville, NJ 973-334-7800
Assessment of the boundaries for self-ignition of unburned charge in spark ignition engines (also related to knock) is required for development of the engine concepts and controls with respect to charge composition, spark advance and valve timing when designing the gas engines with wide range of the fuel compositions and converting compression ignition engines to gas engines. In this paper the combination of the single-zone model of the SI engine and chemical kinetics modeling is evaluated as a rapid prototyping tool for prediction of the self-ignition of the unburned charge in SI engine. The single-zone model simulates the cylinder pressure history based on Wiebe heat release function. The simulation of the self-ignition of the unburned charge is performed with coupled solution of the system of ordinary differential equations for temperature and species concentration with detailed chemical kinetic mechanism. Three fuels were considered: primary reference fuel, methane, hydrogen. The
Zaev, IvanSmirnov, Sergei
3D printing has the potential to revolutionize product design and manufacturing in a vast range of fields, from custom components for consumer products, to 3D-printed bone and medical implants. But the process also creates a large amount of expensive and unsustainable waste and takes a long time, making it difficult for 3D printing to be implemented on a wide scale.
ABSTRACT Considering the growth of unmanned vehicles in Defense and Government applications, a simple and efficient way to design, develop and deploy trusted and secure systems is imperative. Secmation’s SecMUAS brings a platform for the rapid design and development of secure modular unmanned systems to defense applications and beyond. SecMUAS “bakes in” cybersecurity features using a modular design framework for unmanned systems. SecMUAS enables affordable, high assurance, “future-proof” solutions to rapidly transition from design to operational use. Secmation’s SecMUAS hardware and software will provide developers a capability to address cybersecurity requirements and related certification approval processes, enabling the rapid transition of technology to the warfighter. Citation: H. Aldridge, F. Livingston, “Secure Rapid Prototyping for Unmanned Systems”, In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 10-12, 2021.
Aldridge, HalLivingston, Fred
Additive manufacturing, also known as 3D printing, allows the fast and cost-effective production of complex high-quality components in a range of materials. The rise of this technology has been fast, and it is rapidly altering the manufacturing landscape. In 2019, the global additive manufacturing market size was valued at $11.58 billion and is predicted to grow at a CAGR (compound annual growth rate) exceeding 14% from 2020 to 2027 (GVR). Additionally, research from Deloitte shows that additive manufacturing is empowering industry 4.0.
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