3D CAD Data Research Articles

Genetic Algorithm-Based Data-Driven Process Selection System for Additive Manufacturing in Industry 4.0.

Additive manufacturing (AM) has impacted the manufacturing of complex three-dimensional objects in multiple materials for a wide array of applications. However, additive manufacturing, as an upcoming field, lacks automated and specific design rules for different AM processes. Moreover, the selection of specific AM processes for different geometries requires expert knowledge, which is difficult to replicate. An automated and data-driven system is needed that can capture the AM expert knowledge base and apply it to 3D-printed parts to avoid manufacturability issues. This research aims to develop a data-driven system for AM process selection within the design for additive manufacturing (DFAM) framework for Industry 4.0. A Genetic and Evolutionary Feature Weighting technique was optimized using 3D CAD data as an input to identify the optimal AM technique based on several requirements and constraints. A two-stage model was developed wherein the stage 1 model displayed average accuracies of 70% and the stage 2 model showed higher average accuracies of up to 97.33% based on quantitative feature labeling and augmentation of the datasets. The steady-state genetic algorithm (SSGA) was determined to be the most effective algorithm after benchmarking against estimation of distribution algorithm (EDA) and particle swarm optimization (PSO) algorithms, respectively. The output of this system leads to the identification of optimal AM processes for manufacturing 3D objects. This paper presents an automated design for an additive manufacturing system that is accurate and can be extended to other 3D-printing processes.

A decision support system for the selection of FDM process parameters using MOORA

Additive Manufacturing (AM) is an automated process of fabricating three-dimensional (3D) physical objects from a 3D-CAD data by adding layers of materials one upon another through a print head or nozzle without using any tooling components or machining environments. Due to freedom in design, any complex shape can be produced using this process. Fused Deposition Modeling (FDM) is one such AM technology that is commonly used for its simplicity, environment friendliness and low requirement for process monitoring. However, this technology is limited only to small-scale production due to high cost and high build time. The present work focuses on the development of a framework for parametric optimization of the FDM process using multi-objective optimization based on ratio analysis (MOORA). A CAD model of the cam follower mechanism has been prepared in the Solidworks platform and used in this experiment for optimization of build time and cost which have been considered as response variables of the experiment. The experiment has been conducted following the full factorial design of experiment (DoE) method.

Investigation on topology-optimized compressor piston by metal additive manufacturing technique: Analytical and numeric computational modeling using finite element analysis in ANSYS

Abstract Air compressors are widely used in factories to power automation systems and store energy. Several studies have been conducted on the performance of reciprocating and screw compressors. Advancements in design and manufacturing techniques, such as generative design and topology optimization, are leading to improved performance and turbomachinery growth. This work presents a methodology to design and manufacture air compressor pistons using topology optimization and metal additive manufacturing. The existing piston is converted to 3D CAD data and topology optimization is conducted to reduce material in stress concentration regions. Thermal and mechanical loads are considered in boundary conditions. The results show reduced material and improved efficiency, which is validated using ANSYS fluent. The optimized 3D model of the piston is too complex for conventional subtractive manufacturing, so laser sintering 3D printing is proposed. Honeycomb pattern infill patterns are used in 3D printing. This investigation is a step toward researching similar methods in other reciprocating compressor components such as cylinder, cylinder head, piston pins, crankshaft, and connecting rods, which will ultimately lead to improved compressor efficiency.

Feasibility Study of Laser-Assisted Incremental Forming for Carbon Fiber Reinforced Thermo Plastic Based on 3D-CAD Data

A three-dimensional (3D) printer can be used to form various shapes in a single process. However, shell shape formation is difficult because of the low adhesion strength between the layers in 3D printing, and sufficient stiffness cannot be maintained. Therefore, the authors focused on laser-assisted incremental forming, which enables the formation of shell shapes from sheet materials, and used carbon fiber reinforced thermo plastic (CFRTP) for the samples. In the study, a laser-assist incremental forming system based on 3D computer-aided design (CAD) data was developed. The system comprises computer-aided manufacturing (CAM) system, which generates a tool path based on CAD data and evaluates the formability between the CAD data and 3D-scanned data, including alignment compensation. The feasibility of the developed system was demonstrated through a set of forming experiments.

Classification of Hull Blocks of Ships Using CNN with Multi-View Image Set from 3D CAD Data

In order to proceed with shipbuilding scheduling involving hundreds of hull blocks of ships, it is important to mark the locations of the hull blocks with the correct block identification number. Incorrect information about the locations and the identification numbers of hull blocks causes disruption in the shipbuilding scheduling process of the shipyard. Therefore, it is necessary to have a system for tracking the locations and identification numbers of hull blocks in order to avoid time loss due to incorrectly identified blocks. This paper proposes a method to mark the identification numbers, which are necessary for the tracking system of hull blocks. In order to do this, 3 CNN (convolutional neural network) models, VGG-19, Resnet-152V2, and Densenet-201, are used to classify the hull blocks. A set of multi-view images acquired from 3D CAD data are used as training data to obtain a trained CNN model, and images from 3D printer-printed hull block models are used for the test of the trained CNN model. The datasets used for training and prediction are Non-Thr and Thr datasets, that each included both binarized and non-binarized datasets. As a result of end-to-end classification experiments with Non-Thr datasets, the highest prediction accuracy was 0.68 with Densenet-201. A total of 4050 experimental conditions were constructed by combining the threadhold of the Thr training and testing dataset. As a result of experiments with Thr datasets, the highest prediction accuracy of 0.96 was acquired with Resnet-152V2, which was trained with a threshold of 72 and predicted with a threshold of 50. In conclusion, the classification of ship hull blocks using a CNN model with binarized datasets of 3D CAD data is more effective than that using a CNN model with non-binarized datasets.

Micro-Defect Inspection on Curved Surface Using a 6-DOF Robot Arm with One-Shot BRDF Imaging

The need for automated visual inspection in Japan is increasing due to labor shortages caused by the declining birthrate and aging population. We have developed an imaging system called One-shot BRDF (Bidirectional Reflectance Distribution Function), which can easily detect even micro-defects that are conventionally difficult to capture using parallel-beam illumination and an image sensor. By color-coding the direction of light, micro-defects can be instantly captured as a clear image. This paper proposes a novel micro-defect inspection system capable of automatically inspecting the surface of materials with complex shapes by mounting One-shot BRDF optics on the tip of a 6-degree-of-freedom (DOF) robot arm and scanning the material's surface. The 6-DOF robot arm can track the scanning trajectory and keep the optics squarely against the curved surface at a constant distance. We developed a simple algorithm to automatically determine the trajectory from the material's 3D CAD data so that the entire surface to be scanned can be inspected quickly and within the 6-DOF robot arm's range of movement. For high-speed and high-precision inspection, we built a nonlinear dynamic model of the 6-DOF robot arm and model-based control to track the trajectory while suppressing vibration. In scanning experiments using mirror-finished aluminum with a curved surface, the position and orientation control errors were sufficiently small in high-speed operation at the limit of the robot arm's performance. Several minute scratches on the mirror-finished aluminum could be detected and their locations were mapped as 3D CAD data.

Motion Analysis of Butterfly-Style Flapping Robot Using CFD Based on 3D-CAD Model and Experimental Flight Data

In this paper, a computational fluid dynamics (CFD) analysis system based on a 3D-CAD model of a butterfly-style flapping robot using its experimental flight data is proposed. The butterfly-style flapping robot can control its attitude by changing its flapping and lead-lag angles; however, measuring the lift, thrust, and body pitch moment directly during flight is difficult. In the case of the flight motion analysis of insects, the state of flight has been photographed, and numerical analysis has been performed to obtain the flow field around the wings. However, when performing the motion analysis of hardware, it is difficult to reflect the shape of the body accurately using this method. In this study, a CFD analysis system considered the shape of the developed butterfly-style flapping robot as 3D-CAD data and analyzed the flow field around the wings using the experimental flight data of the hardware. The results of motion analysis showed that the attitude during flight differs due to the difference in lifts and body pitch moments in the flight experiment data of the hardware with different neutral angles of the flapping wings.

Topology optimization of clutch drive plate for commercial vehicles

he drive plate is one of the main components of the clutch disc which transmits the torque from engine to transmission. For commercial vehicle applications, the drive plate works under immense torsional forces thanks to high engine torque values. Therefore, high durability is expected during the operational life of the clutch disc drive plate. On the other hand, the lightweight of the vehicle components has an important role in CO2 emission standards. To be able to assure this regulation, companies conduct studies for decreasing the vehicle mass. In this study, the drive plate's 3D CAD data is created based on the current design by using CATIA solid creation software. Finite Element Analysis (FEA) was carried out in a statical analysis tool and to be verified for real-life working conditions. The topology optimization was performed using CAE software (ANSYS) in order to reduce the weight of the drive plate without compromising on mechanical durability. The optimized design was proposed based on topology optimization outputs. The strength of the proposed design was investigated by using FEA analysis and results are compared to the acceptance criteria of the material. The optimized geometry is equally durable and lighter in weight compared to the existing model. Mass was decreased %18 without compromising mechanical durability.

Feature visualization within an automated design assessment leveraging explainable artificial intelligence methods

Not only automation of manufacturing processes but also automation of automation procedures itself become increasingly relevant to automation research. In this context, automated capability assessment, mainly leveraged by deep learning systems driven from 3D CAD data, have been presented. Current assessment systems may be able to assess CAD data with regards to abstract features, e.g. the ability to automatically separate components from bulk goods, or the presence of gripping surfaces. Nevertheless, they suffer from the factor of black box systems, where an assessment can be learned and generated easily, but without any geometrical indicator about the reasons of the system’s decision. By utilizing explainable AI (xAI) methods, we attempt to open up the black box. Explainable AI methods have been used in order to assess whether a neural network has successfully learned a given task or to analyze which features of an input might lead to an adversarial attack. These methods aim to derive additional insights into a neural network, by analyzing patterns from a given input and its impact to the network’s output. Within the NeuroCAD Project, xAI methods are used to identify geometrical features which are associated with a certain abstract feature. Within this work, a sensitivity analysis (SA), the layer-wise relevance propagation (LRP), the Gradient-weighted Class Activation Mapping (Grad-CAM) method as well as the Local Interpretable Model-Agnostic Explanations (LIME) have been implemented in the NeuroCAD environment, allowing not only to assess CAD models but also to identify features which have been relevant for the network’s decision. In the medium run, this might enable to identify regions of interest supporting product designers to optimize their models with regards to assembly processes.

Experimental and Numerical Investigation of Crack Propagation in Spherical Porous Cylindrical Specimen under Mixed Mode Loading

In this study, mixed mode-I/III fatigue crack propagation is examined experimentally and numerically by using spherical porous cylindrical specimen. The crack propagation path, profiles of crack front, the differences of stress intensity factors (SIF) and equivalent SIF were computed by Ansys, FCPAS and Solidworks softwares and compared with experimental data. Modeling, meshing and problem solving were performed using ANSYS, and the resulting SIF and equivalent SIF along the crack front were calculated using FCPAS. Two digital cameras were used to observing the crack growth path and fractured surfaces on specimen under mixed mode loading and the obtained images was converted into 3D CAD data by using Solidworks software. It was found that good agreements are achieved between the results of the experiment and simulation, considering both evolving the crack propagation paths and crack front.

Direct metal laser sintering of TI6Al4V alloy for patient-specific temporo mandibular joint prosthesis and implant

An Additive Manufacturing technique uses 3D CAD model and data to manufacture a product by placing layers of material consecutively. Additionally, referred to as “3D printing”, there are numerous techniques which distinctively does not use conventional material removal methods. Direct Metal Laser Sintering (DMLS) is one of such AM techniques that can manufacture metal components from a 3D CAD design. It utilizes a strong laser beam for melting micro powdered metallic particles layer up layer, to obtain the desired product. DMLS technique is attributing medical and engineering fraternity to fabricate tailor-made metal implants and prosthesis for oral and maxillofacial as well as prosthodontics applications. This research article has discussed the process of creating a unique and customized TMJ prosthesis for first time in India using 3D CAD modelling for design and DMLS technique for fabrication.

Investigating the Impacts of Heterogeneous Infills on Structural Strength of 3D Printed Parts

Additive Manufacturing is a manufacturing process based on layers for making three dimensional scaled physical parts directly from 3D CAD data. Fused Deposition Modeling (FDM) is widely used technology that provides functional prototypes in various thermoplastics. In additive manufacturing, filling patterns are of two types; External and Internal filling patterns. Multiple patterns are developed for both filling categories. In this work, a heterogeneous infill strategy is used by choosing developed patterns in order to improve strength to weight ratio, material usage and build time for parts. A rectilinear pattern combination with triangular and rectangular pattern has been chosen for 3D printing. The tensile testing is performed on the printed specimens to calculate the strength to weight ratio. By comparing the obtained results, a strategy based on maximum strength to weight ratio, minimum material usage and reduced build time is recommended for FDM technology.

3D CAD data extraction and conversion for application of augmented/virtual reality to the construction of ships and offshore structures

ABSTRACTDue to the global economic downturn and low oil prices, orders for offshore plants and vessels have declined. Moreover, the range of regulations has increased and customer requirements have diversified. As a result, a new paradigm for the manufacturing environment is needed to improve competitiveness. As IT technology develops, we are making efforts to improve product design and production efficiency by combining various technologies such as digital twin, virtual reality and augmented reality. To use these technologies, 3D models of products are important. A product model exists in a 3D CAD system, which is required to utilize the model. The focus of previous research was on shape transformation using neutral formats such as igs and step files. However, this was also incomplete, and would be better visualized in virtual/augmented reality. In this study, we aimed to develop a framework to extract and visualize 3D models that could be used in augmented/virtual reality in real time and we conducted a test to verify the framework’s validity and efficiency. As a result of the test, it is expected that this framework will be a valuable variety field in the lifecycles of a ship, an offshore structure, and an industrial plant.

Plastic droplet welding: bond strength between plastic freeforming structures and continuous fiber-reinforced thermoplastic composites

Plastic freeforming (PF) is an additive-manufacturing process for producing three-dimensional plastic parts based on 3D CAD data by applying plastic droplets in layers. This process is used to produce customer-specific and complex geometries (prototypes and small series) on organic sheets. A comparable serial process is the injection of a second component onto organic sheets by injection molding. A sufficient bond between the PF structure and the organic sheets is of particular importance for each application. If this is not guaranteed, the composite system cannot withstand the mechanical load and fails. The force exerted on the system can no longer be transmitted between the PF structure and the organic sheet. The organic sheet is made of glass fiber-reinforced polypropylene (PP). The connection between the organic sheet and the PF structure is achieved by welding the molten polymer droplets and the surface of the organic sheet. The PF structures are made of PP to ensure sufficient compatibility with regard to the weldability of the components. The processing of PP in the PF process is a challenge because PP is a semi-crystalline material. The shrinkage of semi-crystalline materials is significantly higher compared to amorphous materials. Due to the layered structure of the components, the shrinkage of the individual layers results in undesired warpage. The adhesive strength between the organic sheet and the PF structure is investigated by determining the bending strength in the 3-point bending test. The investigations include an optimization of the process parameters to maximize the adhesive strength. The experimental investigations show that an increase of the nozzle and build chamber temperature leads to a higher adhesive strength. In further investigations, the temperature of the nozzle shows no significant influence on the surface temperature despite the expected heat radiation. The surface temperature is almost only dependent on the temperature of the build chamber.

Assembly motion automatic planning technology using geometric constraint conditions (Calculation of start, end and via point for parts assembly task using 3D CAD data)

Assembly motion automatic planning technology using geometric constraint conditions (Calculation of start, end and via point for parts assembly task using 3D CAD data)

Study on Method of Fabricating the Upper Limb Orthosis (Splint) from 3D CAD Data

Study on Method of Fabricating the Upper Limb Orthosis (Splint) from 3D CAD Data

Appraisal of Mechanical and Tribological Properties on PA6-TiO2 Composites through Fused Deposition Modelling

The primary objective of this examination is to build an arrangement of new polyamide blends with inventive properties like biodegradability. The composite blends of polyamide 6 (PA6) blended with 10, 20 and 30 wt.% titanium-di-oxide (TiO2) were taken for this proposed work and converted in a form of wire in a filament extruder machine and taken to build the parts by using Fused deposition modelling (FDM) machine. Fused deposition modelling (FDM) is an additive manufacturing technology commonly used for modelling, prototyping, and production applications. This process constructs three-dimensional objects directly from 3D CAD data. A temperature-controlled head extrudes thermoplastic material layer by layer. The quality and strength of part that is built depends on many variables in FDM process. In this study important process parameters of extrusion were fixed. Test specimens were prepared by melting, compounding and smoothly printed by means of a commercial FDM three-dimensional (3D) printer. The printed samples were taken for mechanical and tribological test. The tested sample’s outcome from UTM indicates that incorporation of filler stacking with equally distributed particles and higher weight (30) percentage of TiO2 has influenced in higher mechanical properties of virgin PA6 and lower weight (10 and 20) percentage of TiO2 gives moderate mechanical properties of the same. These tribological tests were carried out on the pin on disk tribometer under varying load conditions such as 5, 10, 15 and 20 N at sliding speed of 1.256 m/s for the run time of 5 and 10 minutes. The results showed that the minimum wear rate of PA6-30%TiO2 samples at maximum applied load of 20N and run time of 10 minutes conditions. The results obtained are exceptionally promising which concludes the methodology exhibited in this paper has applications for design and manufacture of automotive parts utilizing FDM technology.

Practical implementation of cutting force model for step drill using 3D CAD data

As an extension of the cutting force model, which was developed by analyzing the forces on rake and relief face, a practical method of cutting force model is suggested. By a calibration test, cutting coefficients are determined, including the information on tool geometry, work material and cutting conditions such as cutting speed and feed rate. As inputs for the force model, normal rake angle and normal relief angle were obtained by a new method from the measured angles using a 3D CAD machine. This practical force model can be applied for machining CFRP successfully, which was proved from the experiments.

ABC's of Measurement Point Cloud Validation against 3D-CAD Data

ABC's of Measurement Point Cloud Validation against 3D-CAD Data

Utilizing a low-cost desktop 3D printer to develop a \u201cone-stop 3D printing lab\u201d for oral and maxillofacial surgery and dentistry fields

BackgroundIn the oral and maxillofacial surgery and dentistry fields, the use of three-dimensional (3D) patient-specific organ models is increasing, which has increased the cost of obtaining them. We developed an environment in our facility in which we can design, fabricate, and use 3D models called the “One-stop 3D printing lab”. The lab made it possible to quickly and inexpensively produce the 3D models that are indispensable for oral and maxillofacial surgery. We report our 3D model fabrication environment after determining the dimensional accuracy of the models with different laminating pitches (; layer thickness) after fabricating over 300 3D models. Considerations were made for further reducing modeling cost and model print time. MDCT imaging was performed using a dry human mandible, and 3D CAD data were generated from the DICOM image data. 3D models were fabricated with a fused deposition modeling (FDM) 3D printer MF-2000 (MUTOH) with a laminating pitch of 0.2 mm, 0.3 mm, 0.4 mm, or 0.5 mm. Each 3D model was then subjected to reverse scanning to evaluate the modeling conditions and deformation during modeling. For the 3D image processing system, Volume Extractor 3.0 (i-Plants Systems) and POLYGONALmeister V2 (UEL) were used. For the comparative evaluation of CAD data, spGauge 2014.1 (Armonicos) was used.ResultsAs the laminating pitch increased, the weight of the 3D model, model print time, and material cost decreased, and no significant reduction in geometric accuracy was observed.ConclusionsThe amount of modeling material used and preparation cost were reduced by increasing the laminating pitch. The “One-stop 3D printing lab” made it possible to produce 3D models daily. The use of 3D models in the oral and maxillofacial surgery and dentistry fields will likely increase, and we expect that low-cost FDM 3D printers that can produce low-cost 3D models will play a significant role.