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Additive Manufacturing

Additive Manufacturing Artificial Intelligence Analysis FEA|CFD & AI Integration

Nonparametric optimization techniques such as artificial intelligence (AI) can be used in conjunction with finite element analysis (FEA) to further optimize designs for AM. AI can help identify the most critical design parameters and their optimal values, while FEA can be used to simulate the performance of the design under various loading conditions. Together, these tools can help engineers create parts that are not only lighter and stronger, but also tailored to specific applications.

Furthermore, AM simulations with advanced package such as Ansys can be used to assess the quality of finished parts before they are manufactured, reducing the need for costly physical testing and prototyping. By simulating the entire manufacturing process, including the effects of material properties, process parameters, and part geometry, engineers can identify potential issues and optimize the process to improve part quality and reduce the risk of failure.

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Additive Manufacturing, Integrated FEA|CFD with Artificial Intelligence

Generative Design & Lattice Structures: Topology, Shape and Bead Optimization

Generative Design is an innovative approach to product design that leverages topology optimization, artificial intelligence, and advanced simulation to create multiple viable design alternatives automatically, based on simple design criteria specified by the user.

Generative Design allows engineers and designers to explore a much wider range of design options than traditional methods, leading to increased creativity and innovation in the product design process. By generating multiple design alternatives, it also helps to optimize designs for efficiency, reduce weight, and minimize material usage, resulting in cost savings and improved sustainability.

Moreover, we use Generative Design to reduce the time-to-market for new products, as it enables our designers to quickly generate and evaluate multiple design alternatives, reducing the need for time-consuming manual design iterations.

Generative Design + CFD: Topology-Optimized Fluid Dynamics

Combine genetic algorithms with RANS/LES simulations to auto-generate weight-optimized turbomachinery blades, heat sinks, and microfluidic devices.

Simulation Dynamics
Generative Design & Lattice Structures: Topology, Shape and Bead Optimization, Ansys, Simulia, Siemens, Integrated FEA|CFD with Artificial Intelligence
Advanced Engineering Solutions

Directed Energy & Laser Metal Deposition

By using advanced FEA software and high-performance computing (HPC) hardware, it is possible to simulate the thermal and mechanical behavior of the additive manufacturing process of Directed Energy Deposition (DED), Direct Metal Deposition (DMD) & Laser Metal Deposition (LMD) in great detail. This can help to identify potential issues and optimize the manufacturing process to reduce distortions and improve the quality of the final component.

Furthermore, FEA simulations can also be used to investigate phase transformations that occur during additive manufacturing. These transformations can have a significant impact on the microstructure and properties of the final component, and understanding them is important for optimizing the manufacturing process and achieving desired material properties.

Cognitive FEA: Machine Learning-Predictive Structural Integrity

Deploy graph neural networks (GNNs) to forecast nonlinear material deformation, crack propagation, and fatigue failure. Train AI on legacy FEA datasets for ISO-certified validation of aerospace composites, additive manufacturing defects, and seismic-resistant infrastructure.

Simulation Dynamics
Directed Energy & Laser Metal Deposition, Ansys, Simulia, Siemens, Integrated FEA|CFD with Artificial Intelligence
Advanced Engineering Solutions

Metal Binder Jetting

Metal Binder Jetting (MBJ) is an emerging additive manufacturing technology that offers several key advantages over traditional Powder Bed Fusion processes.

One of the main advantages of MBJ is its ability to print high volumes of parts with minimal spacing. This means that multiple parts can be printed simultaneously, reducing the time and cost of production. Additionally, MBJ does not require support structures, which simplifies the design process and reduces material usage.

Furthermore, MBJ has the potential to replace low-volume, high-cost metal injection molding for a wide range of applications. This is because MBJ is capable of producing complex metal parts with high accuracy and surface quality, making it suitable for use in industries such as aerospace, automotive, and medical applications.

Our cutting-edge Artificial Intelligence & Machine Learning integrated development solutions combine technical excellence with business insight to deliver exceptional digital experiences.

We leverage modern frameworks with CFD & FEA solvers and cloud infrastructure to build applications that scale seamlessly with your industrial needs.

Simulation Dynamics
Metal Binder Jetting, Ansys, Simulia, Siemens, Integrated FEA|CFD with Artificial Intelligence
Advanced Engineering Solutions

Plastics & Reinforced Polymers

Advanced additive manufacturing simulation platforms such as MSC Digimat, Ansys, and Abaqus are powerful tools that can be used to simulate the manufacturing process of various additive manufacturing techniques, including Fused Filament Fabrication (FFF), Fused Deposition Modeling (FDM), and Selective Laser Sintering (SLS).

One of the biggest challenges in additive manufacturing is achieving high part fidelity, which refers to the accuracy and precision of the final printed part. Simulation-based design allows engineers to predict and optimize the manufacturing process to minimize warpage and residual stresses, which are common issues in the production of polymer parts.

By using advanced simulation platforms, our engineers can analyze the thermal and mechanical behavior of the additive manufacturing process, allowing them to optimize process parameters and material selection to improve part fidelity and reduce defects and to reduce the time and cost of development.

Multiphysics AI: Simulate Fluids, Structures, & Electromagnetics

Model EV motor cooling, MEMS sensors, and satellite thermal-vibration coupling. Use pytorch/TensorFlow-integrated solvers to automate boundary conditions and predict multiphysics failures in mission-critical systems.

Simulation Dynamics
Plastics & Reinforced Polymers, Ansys, Simulia, Siemens, Integrated FEA|CFD with Artificial Intelligence
Advanced Engineering Solutions

Powder Bed Fusion

Powder Bed Fusion (PBF) is an additive manufacturing technique that uses a heat source, typically a laser or electron beam, to fuse powder particles layer-by-layer, forming a solid part. PBF enables the production of geometrically complex parts that would be difficult or impossible to produce with traditional manufacturing techniques.

One of the main advantages of PBF is its flexibility in terms of materials and technology. PBF can be used with a wide range of materials, including metals, polymers, and ceramics, and can be applied using several different techniques, including Selective Laser Melting (SLM), Electron Beam Melting (EBM), and Direct Energy Deposition (DED).

Furthermore, PBF offers a high degree of design freedom, as complex geometries can be produced without the need for complex tooling or machining processes. This allows manufacturers to create highly customized and intricate parts that would be difficult or impossible to produce with traditional manufacturing techniques.

AI-Driven Simulations for Smarter Engineering.

Leverage Artificial Intelligence to optimize CFD, FEA, and multiphysics simulations. Automate workflows, reduce errors, and accelerate innovation. Transform your engineering processes with AI-powered insights.

Simulation Dynamics
Powder Bed Fusion, Ansys, Simulia, Siemens, Integrated FEA|CFD with Artificial Intelligence
Advanced Engineering Solutions