Additive Manufacturing Process Simulation and Generative Design-Production of Functional Parts
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Additive manufacturing (AM) or 3D printing is maturing rapidly as a viable solution of make optimized parts for “real engineering” applications. The freedom of design that is achievable using AM process is un parallel in terms of reducing structural weight, reducing material cost, generating complex shapes and connections and introducing directional properties in a component. However, understanding of AM process and utilizing process parameters to optimize a design comes with many challenges. Currently, one of the emphasize is to use physics based realistic simulation to replicate the AM process numerically and relate process parameters to the concept of functional generative design that relates design with manufacturing process. Current work, through a typical build example, discusses an integrated numerical solution on a digital platform that involves the following. Generative Design involving topology optimization that creates parts in context of the manufacturing process and automatically generate variants of conceptual and detailed organic shapes that helps make informed business decisions based on physics-based analytic tools. Process planning that defines and customizes manufacturing environment including nesting parts automatically on the build tray, designing and generating optimal support structures, and creating machine specific slicing and scan path which is ready for print. Process simulation that automatically includes machine inputs for energy, material and supports into the simulation at layer, part and build levels for any additive manufacturing process and accurately predicts part distortions, residual stresses and as-built material behavior. Finally, the platform involves post processing to perform shape optimization where simulation is used to guide support-structure strategy for enhanced build yield, compensate distortion effects without the need to redesign the product tooling, produce high-quality morphed surface geometry with unchanged topology, and perform final in-service performance validations of manufactured part.
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Additive Manufacturing Process Simulation and Generative Design-Production of Functional Parts
- 1. Additive Manufacturing Process Simulation and Generative Design – Production of Functional Parts Arindam Chakraborty, PhD, PE Virtual Integrated Analytics Solutions (VIAS) achakraborty@viascorp.com www.viascorp.com June 06, 2018
- 3. © 2018 Virtual Integrated Analytics Solutions Inc. Company Overview 3 • Multiple Industry Experience • Aerospace & Defense • Automotive • Energy, Process & Utilities • Machinery & Equipment • Nuclear • Marine & Offshore • Medical Devices • High-tech • Presence in Houston, Chicago, Cincinnati, LA, Portland • Provides Engineering Consultancy, Automation and Customization, Training • Team consists of PhD’s and MSc/MTech’s in Design, Manufacturing, Solid Mechanics, Fatigue & Fracture, Composites, Thermal & Fluid, Materials & Corrosion, Numerical Analysis, Optimization & Reliability, Data Analytics, System and Hardware Architecture • Dassault Systèmes PLM Platinum Partner (CATIA, SIMULIA, DELMIA, ENOVIA, 3DEXPERIENCE) • Provide AM Simulation and 3D Printing Services Engineering Consultancy Training Automation & Customization Software
- 4. © 2018 Virtual Integrated Analytics Solutions Inc. VIAS Capabilities 4 Advanced FEA Fatigue-Fracture / Damage Mechanics Reliability and Optimization CFD and Multi-physics Simulation Fitness-for-Service and Root Cause Analysis Data Analytics CAD and PLM Services
- 5. AM – OVERVIEW AND CURRENT STATUS
- 6. © 2018 Virtual Integrated Analytics Solutions Inc. Additive Manufacturing A process of joining materials to make objects from 3D model data, usually layer upon layer, as opposed to subtractive manufacturing fabrication methodologies [ISO 17296-1 and ASTM 2792-12] Design Freedom Product Innovation Bio-inspired Generative Design • Early AM processes established in the mid 1980’s as a solution for faster product prototype development • Plastic processing techniques were initially commercialized for the development of “short life products” • Metal AM processes were developed and introduced into the market in the 1990’s
- 7. AM vs Subtractive Manufacturing 7© 2018 Virtual Integrated Analytics Solutions Inc. AM also gives us the power to manufacture more customized and complex shapes in comparison to subtractive manufacturing
- 8. AM – REAL WORLD CHALLENGES AND INNOVATION
- 9. © 2018 Virtual Integrated Analytics Solutions Inc. From Powder to Working Parts – Ideal World Field Ready-to-use part DesignRaw metal powder
- 10. © 2018 Virtual Integrated Analytics Solutions Inc. Additive Manufacturing for the REAL World Part Geometry Material Behavior Part Quality In-Service Loads Load scatter and Variability Crack Initiation and Growth Fatigue and Durability Topology Optimization Functional Lattices Geometry Reconstruction Generative Design As-built material properties Mean stress effects Structural Flaws Residual stress Part Distortion Build planning Support structure placement Tool Path Generation Repeatability & Scatter
- 11. © 2018 Virtual Integrated Analytics Solutions Inc. Powder to Working Parts - Challenges Field Surface finish Material defects Residual stress state Design Design for AM Process planning strategies Part quality & yield WEEKS : MONTHS
- 12. © 2018 Virtual Integrated Analytics Solutions Inc. Powder to Working Parts – Shorter Time? Field Surface finish Material defects Residual stress state Design Design for AM Process planning strategies Part quality & yield DAYS : WEEKS
- 13. © 2018 Virtual Integrated Analytics Solutions Inc. Addressing AM challenges: Going Digital “Semi-collaboration” Manage, migrate, repurpose files Domain-specific Tools Tribal knowledge dominant from electronic… …to digitally connected Establish digital connectivity Eliminate silos with a digital platform Unite all functions Sales, marketing, merchandising, design, engineering, manufacturing, retail, service and supply chain
- 14. © 2018 Virtual Integrated Analytics Solutions Inc. Going digital with 3D EXPERIENCE Data Driven Virtual+Real Model Based Connected
- 15. © 2018 Virtual Integrated Analytics Solutions Inc. Physics-based Process Simulation Goals 15 Optimize the Process • For Cost • For Build Quality Calibrate Material and Build • Improve material response & design Simulate Stress and Distortion • Calculate Tolerance Capture Physics • Process Specifics • Relevant phenomena • Cracking: Parts fail to build during the process due to thermal stresses • Tolerances: Part are out of tolerances due to the size or the print process (distortions) • Cost: Trial and error runs and re-runs on the machine can be time-consuming and very costly
- 16. © 2018 Virtual Integrated Analytics Solutions Inc. AM Standardization and Validation Design Design Rules Material Photopolymer Resins Metal Powders Polymer Filaments Process Material Jetting Material Extrusion Power Bed Fusion Performance Mechanical Test Methods Post-Processing Methods Part Quality • NIST- Roadmap for AM: Metal and Polymer (May 2013) • ASTM International Committee F42 on Additive Manufacturing Technologies was organized by industry in 2009 • ISO/TC 261: Joint effort with ASTM since 2011 • America Makes & ANSI Additive Manufacturing Standardization Collaborative (AMSC), launched in March 2016 Purpose of Standardization and Validation: • Efficiency - Reduces potential for redundancies and incompatibilities • Consistency – Ensures the consistency and quality of AM parts • Organization – Prioritization and planning of standards development is easier, and relationships between standards are clear Current Efforts
- 18. © 2018 Virtual Integrated Analytics Solutions Inc. Function Driven Generative Design 18 Unifying Modeling, Simulation and Optimization in a single environment • Efficient Product Engineering, removing bottlenecks that usually make it cost- prohibitive to explore optimized parts. • Intuitive Workflow for Designers, with non- expert solutions • Automatic Generation of function-driven conceptual shapes and detailed organic shapes • Seamless Collaboration with Designers, Simulation and Manufacturing Engineers Generative design is a form finding process that can mimic nature's evolutionary approach to design. It can start with design goals and then explore innumerable possible permutations of a solution to find the best option.
- 19. © 2018 Virtual Integrated Analytics Solutions Inc. AM – New Design Paradigm Loading ConditionsDesign Space Targets & Constraints Explore Generate Validate Select the best concept Use KPI’s to decide Milling Casting Additive Manufacturing Capture Functional Specifications1 Generate & Validate Conceptual Shapes2 Concept trade-off3 Generative Shape Modeling & Validation4 Functional Generative Designer “Optimal lightweight design within specification”
- 20. © 2018 Virtual Integrated Analytics Solutions Inc. Solution Coverage – Behind the Scene 26 Topology Optimization Increasingnon-linearity No relative motion (linear) Small relative motion, no friction Large material deformation Large relative motion, friction Braking TurningUndeformed Constraints Constraints for mass, symmetry, stress, displacement, forces for conventional and additive manufacturing New: Geometry based overhang constraints for AM With (45°) overhang, self-supporting Printdirection Part requires supports for print Geometry and Validation Smooth Surface Direct Modeling Parametric Modeling 𝝈 𝒗𝒎 ≤ 𝟕𝟎𝟎
- 22. © 2018 Virtual Integrated Analytics Solutions Inc. Additive Manufacturing| Process Planning 28 Process Re-use1 Process Preparation2 Slicing & Scan Path Generation3 Generate the Outputs4 Additive Manufacturing Programmer “Defining the Manufacturing Build”
- 23. VIRTUAL PRINTING - SIMULATION
- 24. © 2018 Virtual Integrated Analytics Solutions Inc. Additive Manufacturing – Printing Simulation 32 Guided Simulation Assistant for Powder Bed Fusion Processes 1 Configurable, General- Purpose Process Simulation Framework 2 Simulation for Post- Processing and In- Service Performance Validation 3 Additive Manufacturing Researcher “Simulate the Manufacturing Build”
- 25. © 2018 Virtual Integrated Analytics Solutions Inc. Simulation Framework - Mesh AM Tool Intersection 33 Inputs can be machine- level details or lumped representations A geometric shape can be assigned to the tool, e.g rectangle for polymer material addition Data can include power, mass rates, recoater times, build changes, any others. Geometry intersections of this virtual tool performed with any arbitrary mesh Process data aggregated into a series of space and time events Tool path input used to simulate location of a tool, e.g. laser source or recoater
- 26. © 2018 Virtual Integrated Analytics Solutions Inc. Simulation Framework - Material and Energy 34 Built-in and programmable distributed heat flux physics Elements activated in progressive fashion Automatic free surface inclusions for convection and radiation Full or partial element volumes to achieve physical layer level accuracy Precise handling of heating events Higher fidelity with mesh and time refinement
- 27. © 2018 Virtual Integrated Analytics Solutions Inc. In-Process Simulation Coverage 35 Recoater Interference In-Build Crack Propagation Plot build distortions on the recoater plane to visualize where recoater interference may occur Employ interference detection sensors in the simulation to monitor distortion results, and terminate simulation if recoater failure tolerance is reached Thermal - Stress Analysis Complete thermo-mechanical solution for part-build, interaction between parts and build tray, and build environment. Thermal gradients, distortion, and stress results throughout the build provide feedback for better print performance Predict print build failure using mesh- independent and solution-dependent crack initiation and propagation with XFEM technology
- 28. © 2018 Virtual Integrated Analytics Solutions Inc. Trade-Off Studies - Performance versus Accuracy 36 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Design Production Analysis SUBHAM WILL SEND VIDEO FROM TIPHAINE 16.9 23.5 34.8 18.0 12.9 15.2 4.5 3.0 4.2 1 1 1 Design Production Research Physical Print Performance for Purpose Accuracy for Purpose Height 165 mm 3300 layers 240k elements SS316 Height 57 mm 1130 layers 460k elements Inconel 718 Height 266 mm 8060 layers 700k elements Aluminum 33 min
- 29. © 2018 Virtual Integrated Analytics Solutions Inc. Post-Process| Part Yield and Quality 37 ANIMATION OF SLOW BRIDGE CUTTING FROM RACHEL Wire EDM Heat Treatment Stresses after the build process and cooling Stresses after heat treatment SUBHAM WILL SEND VIDEO FROM TIPHAINE Machining Simulate the process of removing the part from the build plate (or removing support structures) using progressive element removal Final machining of AM parts to remove excess stock along with fixture design and CNC programming
- 30. © 2018 Virtual Integrated Analytics Solutions Inc. In-Service Capabilities - Life-time estimations 38 Durability Bolt axial loads applied on the hinge The effect of residual stresses can be significant for fatigue life Part FailureService Loading Incorporate residual stresses effects and manufacturing history for investigating in- service part performance Include manufacturing residual stresses in damage, delamination, and crack propagation simulations End of Build Final Stress State Reliability estimate fatigue reserve factor
- 32. © 2018 Virtual Integrated Analytics Solutions Inc. Materials Coverage - From Atoms to Parts 40 Material Microscale (before print) ❖ Grain morphology via Phase Field Simulations ❖ Material properties via FE homogenization ❖ Thermal mechanical properties ❖ Metal, alloy, polymer, composite, ceramic Material Evolution (during print) ❖ Realistic temperature-dependent models ❖ Raw material - melt pool - solid ❖ Metallurgical transformations ❖ Grain Nucleation and Growth ❖ Computationally efficient Material Performance (after print) ❖ Constitutive laws: elastoplastic, visco, damage .. ❖ Customizable constitutive model interface ❖ Multi-scale material downscaling & upscaling ❖ In-situ material calibration ❖ In-service fatigue life prediction Material Evolution Material Performance Material Microscale
- 33. © 2018 Virtual Integrated Analytics Solutions Inc. Simulation Validations - Distortion 42 Coupon Test Level Deformations Build Part Level Deformations Match distortions for different scan patterns using anisotropic expansion coefficients of Inconel 625 Blindly match distortions using only material properties from literature for Ti-6Al-4V Full-sized excavator arm made of AISI 1018 steel Thin walled structure distortion predictions in AISI 1018 steel Simunovic et. al. (2018). NAFEMS World Congress. Oancea, London (TWI), NAFEMS World Congress, 2018 [m] Experiment: Wu et al. 2014 Match distortion contour for complex geometry of Steel 316L
- 34. © 2018 Virtual Integrated Analytics Solutions Inc. Simulation Validations - Stress and Microstructures 43 Residual Stresses Experiment: Wu et al, 2014.; Hodge et al, 2016.. Residual stress components validated for Steel 316L Simulation Results Melt Pool & Microstructure Melt pool size & overlap for Inconel 718 Porosity from unfused regions in Ti-6Al-4V Phase content in Ti-6Al-4V Oancea, London (TWI), NAFEMS World Congress, 2018 Experiment: Lee et al. 2016.
- 35. © 2018 Virtual Integrated Analytics Solutions Inc. Physics-based Process Simulation Goals 45 Process Parameter Analytics Path 1 Path 2 Path 3 Path 4 Use simulation to optimize process parameters and tool paths to improve part quality, minimize distortions and stresses, and design spatially varying material properties Process Parameter Mapping Create process maps and guidelines using virtual simulations instead of real prints Mapping scan pattern, laser speed and laser power with microstructure and material property LaserPower Laser speed ScanPattern Porosity Phase Content Grain Size & Morphology Melt Pool Dimension Yield Strength
- 36. SUMMARY
- 37. © 2018 Virtual Integrated Analytics Solutions Inc. Manufacturing Simulation Overview 47 Function- driven design TASK Catia TECHNOLOGY Manufacturing process planning TASK Delmia TECHNOLOGY Manufacturing process simulation TASK Simulia TECHNOLOGY Manufacturing process compensation TASK Catia TECHNOLOGY
- 38. © 2018 Virtual Integrated Analytics Solutions Inc. Solution Access and Usage Options 48 Flexible Cloud-Based Burst Licensing On-Premise On-CloudHigh Performance Computing
- 39. © 2018 Virtual Integrated Analytics Solutions Inc. Additive Manufacturing: Challenges Field Surface finish Material defects Residual stress state Design Design for AM Process planning strategies Part quality & yield DAYS : WEEKS
- 40. Q&A THANK YOU!