CDFAM Computational Design Symposium

Recorded at CDFAM Computational Design Symposium, NYC 2024

Presentation Abstract

Computer-Aided Manufacturing (CAM) has revolutionized the manufacturing industry over the past century by enabling the use of software tools to generate machine programs. However, a significant limitation remains: these tools still require substantial input from highly skilled human operators. As production technologies have advanced — from multi-degree-of-freedom (multi-DOF) robots to 3D printers and complex milling machines — the complexity of programming these machines has also increased. This growing complexity has made CAM a bottleneck in the adoption of advanced production techniques, particularly as batch sizes shrink and CAM-associated labor costs per part rise.

At two companies I am involved with: ArcNC, where we focus on CAM for robotic welding, and Oqcam, which specializes in dental CAM; we have explored various deep learning techniques to automate different aspects of the CAM process. In this talk, I will provide a high-level overview of our approaches, share key learnings from our journey, and discuss potential future directions for integrating modern deep learning approaches into CAM and design.

Speaker Bio.

Ben Schrauwen is an investor and entrepreneur, currently the Co-Founder of ArcNC, Oqcam, and Raidyn. He previously co-founded and served as CEO of Oqton, which was acquired by 3D Systems. Before that, he was a Senior Director in Autodesk’s manufacturing division. Ben also served as a Professor at Ghent University, where he founded a pioneering machine learning research group. He holds a PhD in Computer Engineering from Ghent University and was a visiting researcher at Harvard

CDFAM Computational Design Symposium series brings together leading experts in computational design from industry, academia and software development for two days of knowledge sharing and networking.

Visit CDFAM.COM to learn about upcoming events around the world.

Recorded at CDFAM Computational Design Symposium, NYC 2024

Presentation Abstract

This presentation is a review on the developments of complex ceramic structures at the SUPSI’s Hybrid Materials Laboratory. From the first attempts to use CAD to explain the thermo-mechanical behaviour of ceramic foams by finite element modelling (FEM), this practice is now a fundamental step fully integrated in the ceramic additive manufacturing (AM). Demanding end users’ requirements can be satisfied thanks to the combination of CD, simulation, and AM to solve multi-physics tasks. This presentation will show several examples of ceramic components working in high temperature, harsh conditions such as: re-entry thermal protection, porous burners, volumetric solar receivers, high temperature waste heat recovery systems, power to X components and periodic open cellular structures for catalysis.

Speaker Bio.

Graduated in naval and mechanical engineering at the University of Naples in 1989, in 1992 specialized in composite materials at the Center for Composite Materials at the University of Delaware in USA. After ten years in the industry he is now professor at SUPSI, responsible of the Hybrid Materials laboratory at SUPSI and faculty member at the Doctoral School of Industrial Engineering of the University of Padova (I) . His research fields are: process engineering of polymer and ceramic matrix composites, oxide and carbide ceramics, design and additive manufacturing of complex ceramics. He has been project manager in national (Innosuisse, SNF), European (FP5, FP6, FP7 and H2020 ) projects. Nowadays his group is focusing on net shape processing of complex ceramics (oxides, carbides and composites) by additive manufacturing. Prof. Ortona has published about 100 peer-reviewed papers and 6 patents. He is member of the evaluation body of the “Practice to Science” founding scheme at SNF and editor of The journal of American Ceramic Society, Materials and Hybrid Advances.

CDFAM Computational Design Symposium series brings together leading experts in computational design from industry, academia and software development for two days of knowledge sharing and networking.

Visit CDFAM.COM to learn about upcoming events around the world.

Recorded at CDFAM Computational Design Symposium, NYC 2024

Presentation Abstract

Kiera will discuss Ocado Technology’s additive-first approach to robotics hardware development. This design process, with additive at its centre, unlocks the benefits of agile software development for the world of hardware, allowing the team to create the world’s lightest and most efficient grocery fulfilment bot.

Agile practices allowed the team to experiment, learn, and iterate at speed with many of the product concepts being designed in just a few weeks. Achieving these results with traditional manufacturing approaches would have taken many times longer due to the design, tooling and procurement lead times associated with testing multiple concepts.

Speaker Bio

Kiera is a Software Engineer on the Industrial DevOps team at automation and robotics platform company Ocado Technology. She joined Ocado Technology in 2021 in the Supply Chain Simulation team in London, working on a site and network digital twin for Ocado’s automated warehouses. In 2023 she moved to Ocado’s Stockholm development centre to join the team developing the next generation of Ocado’s fulfilment robot, the 600 series. Her role in Industrial DevOps is to develop tools that can be used to apply the software concepts of DevOps to the world of hardware development. When she is not writing or reviewing code, she can be found planning her next TTRPG session

CDFAM Computational Design Symposium series brings together leading experts in computational design from industry, academia and software development for two days of knowledge sharing and networking.

Visit CDFAM.COM to learn about upcoming events around the world.

Recorded at CDFAM Computational Design Symposium, NYC 2024

Presentation Abstract

Despite the enormous potential of leveraging the rich information embedded in biological form, and the rising interest in bio-inspired design, there is no generalized, accessible computational design tool that enables it. In this presentation I will identify what I believe are the reasons for this gap and propose a framework to address it in the context of nine distinct types of architected materials, introduced here as “Bio-Motifs”. This framework consists of three pillars: (i) knowledge graphs, (ii) mathematical models, and (iii) data and information. I will elucidate aspects of this framework with examples from ongoing work spanning diverse organisms and structural elements such as sea sponge networks, honeybee hair, honeycomb, scales and branching structures. I will also demonstrate how we use computational design, simulation and additive manufacturing to both understand the functional basis for biological form, and leverage that understanding to engineer novel application solutions.

Speaker Bio

Christian Waldvogel is the founder of spherene, a Zurich-based company developing autonomous design software. He holds a Master’s degree in architecture from ETHZ, made his first 3D print in 1999, and spent most part of the 21st century as a conceptual artist. His work, which aims to reflect humanity as a species, on a planet and in the universe, was published and exhibited worldwide, and has directly led to the discovery of the spherene geometry in 2012

CDFAM Computational Design Symposium series brings together leading experts in computational design from industry, academia and software development for two days of knowledge sharing and networking.

Visit CDFAM.COM to learn about upcoming events around the world.

Recorded at CDFAM Computational Design Symposium, NYC 2024

Presentation Abstract

In today’s competitive landscape, organizations are increasingly commercializing meaningful additive manufacturing (AM) applications while striving to optimize costs and improve their bottom line. We will address the pressing need to eliminate repetitive activities by simplifying AM workflows through DfAM partnerships and developing design automation processes.   

Gain insights into how to automate design workflows for mass customization, streamline repetitive data and build preparation tasks, and debug build processing workflows using visualization tools powered by Magics SDKs.   

We will discuss how the industry must embrace collaboration and openness to enable innovation at scale with AM. By the end of this talk, you will have a clearer understanding of how to enhance your AM capabilities through partnership integrations, automation, and innovative solutions.

CDFAM Computational Design Symposium series brings together leading experts in computational design from industry, academia and software development for two days of knowledge sharing and networking.

Visit CDFAM.COM to learn about upcoming events around the world.

Recorded at CDFAM Computational Design Symposium, NYC 2024

Presentation Abstract

Additive manufacturing (AM) technology has afforded greater degree of geometrical design freedoms not otherwise available through traditional manufacturing. Multi-material laser powder bed fusion (MM-LPBF) combines the great geometric and surface roughness resolution associated with LPBF with selective powder deposition (SPD), allowing for the special tailoring of material based on functional design requirements. For instance, advanced heat exchanger design can now include copper fins for efficient heat dissipation combined with nickel alloys for structural strength, and stainless steel for corrosion resistance. The ability to selectively engineer the design and material assignment of multiple metals in true 3D voxel approach into a single component can produce extreme design advantages for both part consolidation and unnecessary material reduction. In most engineering applications (e.g. aerospace, automotive, space) weight is considered a critical design factor. Part and assembly consolidation, as well as light weighting associated with new AM technology, can now be extended beyond traditional single material design and on many length scales. To facilitate this aspiration, we have developed a framework utilizing topology optimization capable of simultaneous multi-material design, inspired by the newfound design freedoms enabled by MM-LPBF. Our motivation exists to investigate and develop new design methods which incorporate manufacturing process considerations (e.g. build orientation, minimum feature size) to produce multi-material metallic designs which meet clear objective functions, such as maximizing stiffness or thermally fluidic heat dissipation.

Speaker Bio

Dr. Guha Manogharan is the Emmert H. Bashore Faculty Development Associate Professor of Mechanical Engineering at The Pennsylvania State University – University Park. He is the Co-Director of CIMP-3D (Center for Innovative Materials Processing through Direct Digital Deposition (CIMP-3D) and also heads the Systems for Hybrid – Additive Processing Engineering – The SHAPE Lab which focuses on additive and hybrid manufacturing with an emphasis on biomedical, defense and aerospace applications. Dr. Manogharan received his Ph.D. (2014) and M.S. (2009) from North Carolina State University. He has received the 2022 ASME Early Career Leadership (ECLIPSE) award, and several young investigator awards (2021 ASTM, 2020 NSF CAREER, 2018 FAME Jr., 2017 SME Outstanding Young Manufacturing Engineer Award and 2016 IISE Outstanding Young Investigator by Manufacturing and Design Division). His current work is supported by NSF, DoE, ONR, AFRL, IACMI, and Manufacturing PA. 

CDFAM Computational Design Symposium series brings together leading experts in computational design from industry, academia and software development for two days of knowledge sharing and networking.

Visit CDFAM.COM to learn about upcoming events around the world.

Recorded at CDFAM Computational Design Symposium, NYC 2024

Presentation Abstract

Boundary representation (B-rep) 3D models are the standard 3D representation used in the manufacturing industry. However, only recently has machine learning research begun to make progress on generative models capable of producing B-rep models. This talk will give a summary of the current state of the art for generating B-rep models. In particular it will cover, BrepGen, our recent work using diffusion models, that have proved extremely successful in the image domain, to the problem of B-rep generation.

Speaker Bio

Karl is a Senior Research Manager at Autodesk Research focused on data-driven design software for manufacturing. He holds a Ph.D. in Computational Design from Carnegie Mellon University and has presented his research internationally at conferences such as ICML, CVPR, ACM SIGGRAPH, ACM UIST, and ACM CHI. His work at Autodesk has won numerous awards including Fast Company Innovation By Design Honoree and Core77 Design Awards Research and Strategy Honoree.

CDFAM Computational Design Symposium series brings together leading experts in computational design from industry, academia and software development for two days of knowledge sharing and networking.

Visit CDFAM.COM to learn about upcoming events around the world.

Recorded at CDFAM Computational Design Symposium, NYC 2024

Presentation Abstract

This presentation explores how brands like CCM are partnering with software platforms like Toolkit3D, and using additive manufacturing tools from Carbon to offer customization to consumers with groundbreaking products like the AXIS XF Goalie Mask and the SUPER TACKS X Total Custom helmet. 

While designers at CCM used Carbon’s Design Engine Pro to create superior lattice pads that increase breathability in the AXIS XF Goalie Mask and the SUPER TACKS X Total Custom helmet, developers at Toolkit3D integrated the Scan-to-Fit Design Engine with Carbon Custom Production Software to build an automated workflow for custom parts, including computational design techniques and automated production preparation. 

In summary, CCM with Toolkit3D built an automated pipeline for products with Carbon’s dual-cure materials and advanced additive manufacturing processes that yield custom fit products automatically and at scale for all athletes– elite to amateur.

Speaker Bio

Puneet Jhaveri is a Senior Applications Engineer at Carbon 3D where he leverages his expertise and training in mechanical engineering and physiology to develop custom products. Originally on a medical track, Puneet’s interests shifted after being exposed to architecture and industrial design, sparking a passion for blending technical skills, aesthetics, and creative problem-solving. Puneet now focuses on pushing the boundaries of product design through innovative, cross-disciplinary approaches.

CDFAM Computational Design Symposium series brings together leading experts in computational design from industry, academia and software development for two days of knowledge sharing and networking.

Visit CDFAM.COM to learn about upcoming events around the world.

Recorded at CDFAM Computational Design Symposium, NYC 2024

Presentation Abstract

Engineering creativity and innovation are too often stifled by the tedious process of building simulation models. The process adds no value, can take weeks or months to complete, and far too often results in a model that has gotten out of sync with the design model.

Coreform’s new Flex product accelerates engineering design by reducing the meshing burden through easier and more powerful FEA. Coreform Flex leverages cutting-edge techniques from FEA and computational geometry to streamline the process of setting up FEA models. At the same time, Flex provides simulation results that are more accurate and robust than traditional low-order FEA across linear, nonlinear, static and dynamic simulation regimes. In most cases, users report that simulation models that usually take several weeks to build can now be built in less than a day.

In this presentation, Matthew Sederberg will give a concrete and accessible overview of the technical underpinnings of the Flex approach to FEA. He will also outline a few of the ways the Flex approach can accelerate engineering design and unleash the creativity of engineers.

Speaker Bio

Mr. Matt Sederberg is a pioneer in introducing new technologies to the CAD/CAE industry and has successfully started and sold a company in this space. Mr. Sederberg introduced T-Splines to the CAD market as its CEO in 2005, bootstrapping that company on SBIR funding to create plugins and integrated components used by over 2000 customers, sold through a channel with over 50 resellers. He created the premier brand in the industry, leading to a successful acquisition by market leader Autodesk in 2011, then led Autodesk’s \$40M automotive design product line. In 2016 Mr. Sederberg left Autodesk to join Coreform, where he now serves as Chief Strategy Officer.

CDFAM Computational Design Symposium series brings together leading experts in computational design from industry, academia and software development for two days of knowledge sharing and networking.

Visit CDFAM.COM to learn about upcoming events around the world.

Recorded at CDFAM Computational Design Symposium, NYC 2024

Presentation Abstract

In the context of traditional and advanced industrial settings, the adoption of Scientific Machine Learning (SciML) requires operating in digital-physical environments governed by large-scale, three-dimensional, multi-modal data streams that are confounded with noise, sparsity, irregularities and other complexities that are common with machines and sensors interacting with the real, physical world. Digital engineering domains—that is CAD, CAM, CFD, and so on—and advanced manufacturing settings provide exemplary environments to separate tried & tested SciML from unreliable “AI” and game engines. This talk elaborates on such digital-physical environments and the non-trivial needs from computational design and engineering tools. Special attention is given to differentiable programming in multi-physics settings, which done well is the catalyst for bringing autonomous, data-driven, machine-learnable techniques to advanced manufacturing and digital engineering worlds.

Speaker Bio

Alexander Lavin is a leading expert in AI-for-science and probabilistic computing. He’s Founder & CEO of Pasteur Labs (and non-profit “sister” Institute for Simulation Intelligence), reshaping R&D with a new class of AI-native simulators, commercializing in energy security, aerospace, materials & manufacturing sectors. For the last dozen years, Lavin has focused on artificial general intelligence (AGI) research with top startups in neuroscience and robotics (Vicarious, Numenta), and sold his prior ML-simulation startup Latent Sciences to undisclosed pharmaco in neurodegeneration R&D.

Lavin also serves as AI Advisor for NASA, overseeing physics-ML efforts for the NASA-ESA “Digital Twin Earth” projects. Previously, Lavin was a spacecraft engineer with NASA and Blue Origin, and won several international awards for work in rocket science and space robotics (including Google Lunar XPrize during graduate studies at Carnegie Mellon). Lavin was named Forbes 30 Under 30 in Science, and a Patrick J. McGovern Tech for Humanity Changemaker.

CDFAM Computational Design Symposium series brings together leading experts in computational design from industry, academia and software development for two days of knowledge sharing and networking.

Visit CDFAM.COM to learn about upcoming events around the world.