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๐ง Metal 3D Printing and Generative Design Applied to Vehicle Chassis Engineering
This advanced demonstration combines Generative Design algorithms with Directed Energy Deposition (DED) metal 3D printing technology to redefine how we design and manufacture structural automotive components.
Key advancements include:
By integrating AI-driven design with additive manufacturing, this approach not only improves mechanical performance but also revolutionizes the production process through material efficiency and design optimization.
#Metal3DPrinting #GenerativeDesign #DirectedEnergyDeposition #AdditiveManufacturing #VehicleEngineering #InnovationInMotion #AdvancedManufacturing
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This advanced demonstration combines Generative Design algorithms with Directed Energy Deposition (DED) metal 3D printing technology to redefine how we design and manufacture structural automotive components.
Key advancements include:
โข ๐ป Up to 10ร reduction in part count โ minimizing complexity and improving maintainability.
โข โฑ๏ธ 60% shorter lead times โ accelerating prototyping and production cycles.
โข ๐ชถ Lightweight and modular architecture โ enabling enhanced performance and energy efficiency.
By integrating AI-driven design with additive manufacturing, this approach not only improves mechanical performance but also revolutionizes the production process through material efficiency and design optimization.
#Metal3DPrinting #GenerativeDesign #DirectedEnergyDeposition #AdditiveManufacturing #VehicleEngineering #InnovationInMotion #AdvancedManufacturing
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๐ Autonomous AI Systems: Shaping the Future of Engineering & Intelligent Decision-Making
Imagine an AI system that doesn't just process data but learns, plans, experiments, and generates innovative solutions independently.
These next-generation autonomous systems function in iterative, adaptive cycles, enabling them to:
All with minimal to no human intervention drastically accelerating innovation across disciplines.
๐ Key Applications Include:
โข Intelligent Data Acquisition through Active Learning
โข Automated Hyperparameter Tuning via Bayesian Optimization
โข Closed-loop Experimental Design and Model-Driven Discovery
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Imagine an AI system that doesn't just process data but learns, plans, experiments, and generates innovative solutions independently.
These next-generation autonomous systems function in iterative, adaptive cycles, enabling them to:
๐ Plan and execute complex simulations and optimization workflows
๐ Evaluate results automatically and refine strategies based on outcomes
๐ก Generate novel solutions grounded in learned patterns and insights.
All with minimal to no human intervention drastically accelerating innovation across disciplines.
๐ Key Applications Include:
โข Intelligent Data Acquisition through Active Learning
โข Automated Hyperparameter Tuning via Bayesian Optimization
โข Closed-loop Experimental Design and Model-Driven Discovery
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๐ A Must-Read Resource for Tech & Engineering Enthusiasts (Ansys Advantage โ Issue 2, 2024)
Focus Topic: AI-Powered Simulation & Autonomous Systems in Engineering
This issue provides deep insights into the future of simulation technologies, autonomous AI systems, digital twins, and their real-world industrial applications.
Key Highlights:
๐น Autonomous AI for Smart Decision-Making
๐น AI-Driven Simulation & Optimization Workflows
๐น Digital Twin Development with AI/ML Integration
๐น Industrial Case Studies from Leading Companies (Tata Steel, Seagate, Automotive, Aerospace)
๐ฅ Access to the full PDF is available in this post.
For more high-value resources in technology, engineering, and AI โ stay connected with @AddiTech.
#AI #Engineering #Simulation #DigitalTwin #Optimization #AddiTech
Focus Topic: AI-Powered Simulation & Autonomous Systems in Engineering
This issue provides deep insights into the future of simulation technologies, autonomous AI systems, digital twins, and their real-world industrial applications.
Key Highlights:
๐น Autonomous AI for Smart Decision-Making
๐น AI-Driven Simulation & Optimization Workflows
๐น Digital Twin Development with AI/ML Integration
๐น Industrial Case Studies from Leading Companies (Tata Steel, Seagate, Automotive, Aerospace)
๐ฅ Access to the full PDF is available in this post.
For more high-value resources in technology, engineering, and AI โ stay connected with @AddiTech.
#AI #Engineering #Simulation #DigitalTwin #Optimization #AddiTech
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Generative Design โ๏ธ
Revolutionizing Engineering Through AI
Stay tuned for real-world applications, case studies, and simulation insights into the future of design and manufacturing. ๐โจ
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Revolutionizing Engineering Through AI
Generative Design is a cutting-edge, AI-driven approach that transforms the way we conceptualize and create engineering solutions. Instead of manually modeling a structure based on past experience or intuition, engineers define the design goals, constraints, material properties, manufacturing methods, and loading conditions and the software explores hundreds or even thousands of optimized design alternatives.
This iterative and exploratory process mimics nature's evolutionary approach, using algorithms to evaluate and evolve solutions based on performance metrics such as strength, weight, durability, and cost-efficiency.
Unlike traditional CAD modeling, where design originates from the engineerโs mind, generative design starts with data โ and ends with innovation.
Stay tuned for real-world applications, case studies, and simulation insights into the future of design and manufacturing. ๐โจ
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๐ ๐๐ฑ๐ฑ๐ถ๐ง๐ฒ๐ฐ๐ต ๐ฆ๐๐ฟ๐ฎ๐๐ฒ๐ด๐ถ๐ฐ ๐ฅ๐ผ๐ฎ๐ฑ๐บ๐ฎ๐ฝ ๐ฎ๐ฌ๐ฎ๐ฑโ๐ฎ๐ฌ๐ฏ๐ฎ
Our prospective view will be at integration of intelligent process control, human-machine collaboration, and cyber-physical resilience in metal additive manufacturing (AM).
๐ค ๐ฅ๐ผ๐ฎ๐ฑ๐บ๐ฎ๐ฝ ๐๐ถ๐ด๐ต๐น๐ถ๐ด๐ต๐๐:
๐ค๐๐ผ๐ถ๐ป ๐จ๐:
Open collaboration with researchers, innovators, and companies in:
โข Metal AM
โข Advanced control systems
โข AR/MR
โข Sustainable manufacturing
โข Cybersecurity in industry
Letโs shape the future of AM together
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Our prospective view will be at integration of intelligent process control, human-machine collaboration, and cyber-physical resilience in metal additive manufacturing (AM).
๐ค ๐ฅ๐ผ๐ฎ๐ฑ๐บ๐ฎ๐ฝ ๐๐ถ๐ด๐ต๐น๐ถ๐ด๐ต๐๐:
๐ฎ๐ฌ๐ฎ๐ฑโ๐ฎ๐ฌ๐ฎ๐ณ: ๐๐ฏ๐ต๐ฆ๐ญ๐ญ๐ช๐จ๐ฆ๐ฏ๐ต ๐๐ณ๐ฐ๐ค๐ฆ๐ด๐ด ๐๐ฐ๐ฏ๐ต๐ณ๐ฐ๐ญ
Real-time manufacturing optimization using AI, adaptive systems, and optical sensors.
๐ฎ๐ฌ๐ฎ๐ณโ๐ฎ๐ฌ๐ฎ๐ด: ๐๐ถ๐ด๐ต๐ข๐ช๐ฏ๐ข๐ฃ๐ช๐ญ๐ช๐ต๐บ & ๐๐ถ๐ฎ๐ข๐ฏ ๐๐ฆ๐ญ๐ญ-๐ฃ๐ฆ๐ช๐ฏ๐จ
Focus on eco-friendly processes, bio-compatible materials, and socially responsible production.
๐ฎ๐ฌ๐ฎ๐ดโ๐ฎ๐ฌ๐ฏ๐ฌ: ๐๐ฅ๐ท๐ข๐ฏ๐ค๐ฆ๐ฅ ๐๐ถ๐ฎ๐ข๐ฏ-๐๐ข๐ค๐ฉ๐ช๐ฏ๐ฆ ๐๐ฏ๐ต๐ฆ๐ณ๐ง๐ข๐ค๐ฆ๐ด (๐๐๐๐)
Integration of AR/MR for immersive monitoring and co-creation in AM.
2030โ2032: ๐๐บ๐ฃ๐ฆ๐ณ-๐๐ฉ๐บ๐ด๐ช๐ค๐ข๐ญ ๐๐ฆ๐ค๐ถ๐ณ๐ช๐ต๐บ & ๐๐ฆ๐ด๐ช๐ญ๐ช๐ฆ๐ฏ๐ค๐ฆ
Robust and secure AM environments via AI-driven anomaly detection and system integration.
๐ค๐๐ผ๐ถ๐ป ๐จ๐:
Open collaboration with researchers, innovators, and companies in:
โข Metal AM
โข Advanced control systems
โข AR/MR
โข Sustainable manufacturing
โข Cybersecurity in industry
Letโs shape the future of AM together
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โก๏ธ ๐๐ฒ๐๐ถ๐ด๐ป๐ถ๐ป๐ด ๐๐๐ฟ๐ฒ๐๐-๐ฟ๐ฒ๐๐ถ๐๐๐ฎ๐ป๐ ๐ฏ๐ฟ๐ฎ๐ฐ๐ธ๐ฒ๐๐ ๐๐ต๐ฎ๐ ๐ฎ๐ฟ๐ฒ ๐ฏ๐ผ๐๐ต ๐น๐ถ๐ด๐ต๐๐๐ฒ๐ถ๐ด๐ต๐ ๐ฎ๐ป๐ฑ ๐ฟ๐ผ๐ฏ๐๐๐ ๐ฝ๐ฟ๐ฒ๐๐ฒ๐ป๐๐ ๐ฎ ๐๐ถ๐ด๐ป๐ถ๐ณ๐ถ๐ฐ๐ฎ๐ป๐ ๐ฐ๐ต๐ฎ๐น๐น๐ฒ๐ป๐ด๐ฒ
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#GenerativeDesign #Engineering #AI #SimAI
๐๐ณ๐ฆ๐ฅ๐ช๐ต๐ด: ๐๐-๐๐ณ๐ช๐ท๐ฆ๐ฏ ๐๐ช๐ฎ๐ถ๐ญ๐ข๐ต๐ช๐ฐ๐ฏ ๐๐ฏ๐จ๐ช๐ฏ๐ฆ๐ฆ๐ณ๐ด ๐ข๐ต ๐๐ฏ๐ด๐บ๐ด
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In this example, we explore new design ideas faster by leveraging existing models. โก๏ธ
In recent projects, we ran up to 250 training samples of various bracket designs to develop a comprehensive AI model. Using SimAI, we can predict physical behaviors such as Von Mises stress in seconds.
And here's the exciting part: Each prediction from the AI comes with a confidence level, shown to increase with the number of training samples.
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#GenerativeDesign #Engineering #AI #SimAI
๐๐ณ๐ฆ๐ฅ๐ช๐ต๐ด: ๐๐-๐๐ณ๐ช๐ท๐ฆ๐ฏ ๐๐ช๐ฎ๐ถ๐ญ๐ข๐ต๐ช๐ฐ๐ฏ ๐๐ฏ๐จ๐ช๐ฏ๐ฆ๐ฆ๐ณ๐ด ๐ข๐ต ๐๐ฏ๐ด๐บ๐ด
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๐จ ๐ง๐๐ ๐๐จ๐ง๐จ๐ฅ๐ ๐ข๐ ๐ ๐๐ง๐๐ ๐ฏ๐ ๐ฃ๐ฅ๐๐ก๐ง๐๐ก๐ ๐๐ฆ ๐๐๐ฅ๐! ๐ฉ๐ฅ
#๐ฆ๐ฝ๐ฟ๐ถ๐ป๐ด #๐ฎ๐ฌ๐ฎ๐ฑ ๐ ๐ฒ๐๐ฎ๐น ๐๐ ๐ ๐ฎ๐ด๐ฎ๐๐ถ๐ป๐ฒ
๐๐ผ๐๐ป๐น๐ผ๐ฎ๐ฑ ๐ป๐ผ๐. ๐ฅ๐ฒ๐ฎ๐ฑ ๐๐ต๐ฎ๐โ๐ ๐๐ต๐ฎ๐ฝ๐ถ๐ป๐ด ๐๐ต๐ฒ ๐ณ๐๐๐๐ฟ๐ฒ ๐ผ๐ณ ๐บ๐ฒ๐๐ฎ๐น ๐ฎ๐ฑ๐ฑ๐ถ๐๐ถ๐๐ฒ ๐บ๐ฎ๐ป๐๐ณ๐ฎ๐ฐ๐๐๐ฟ๐ถ๐ป๐ด.
๐ [Download Full PDF]
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#๐ฆ๐ฝ๐ฟ๐ถ๐ป๐ด #๐ฎ๐ฌ๐ฎ๐ฑ ๐ ๐ฒ๐๐ฎ๐น ๐๐ ๐ ๐ฎ๐ด๐ฎ๐๐ถ๐ป๐ฒ
๐๐ณ๐ฆ๐ข๐ฌ๐ต๐ฉ๐ณ๐ฐ๐ถ๐จ๐ฉ๐ด, ๐ช๐ฏ๐ด๐ช๐จ๐ฉ๐ต๐ด, ๐ข๐ฏ๐ฅ ๐ณ๐ฆ๐ข๐ญ-๐ธ๐ฐ๐ณ๐ญ๐ฅ ๐ช๐ฏ๐ฏ๐ฐ๐ท๐ข๐ต๐ช๐ฐ๐ฏ๐ด ๐ง๐ณ๐ฐ๐ฎ ๐จ๐ญ๐ฐ๐ฃ๐ข๐ญ ๐ญ๐ฆ๐ข๐ฅ๐ฆ๐ณ๐ด ๐ญ๐ช๐ฌ๐ฆ ๐๐๐๐, ๐๐, ๐ข๐ฏ๐ฅ ๐๐ฐ๐ญ๐ญ๐ด-๐๐ฐ๐บ๐ค๐ฆ.
๐๐ผ๐๐ป๐น๐ผ๐ฎ๐ฑ ๐ป๐ผ๐. ๐ฅ๐ฒ๐ฎ๐ฑ ๐๐ต๐ฎ๐โ๐ ๐๐ต๐ฎ๐ฝ๐ถ๐ป๐ด ๐๐ต๐ฒ ๐ณ๐๐๐๐ฟ๐ฒ ๐ผ๐ณ ๐บ๐ฒ๐๐ฎ๐น ๐ฎ๐ฑ๐ฑ๐ถ๐๐ถ๐๐ฒ ๐บ๐ฎ๐ป๐๐ณ๐ฎ๐ฐ๐๐๐ฟ๐ถ๐ป๐ด.
๐ [Download Full PDF]
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๐Microstructure-Structure based modelings and crystal plasticity in ABAQUS using UMAT
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