It is highly recommended that you apply for a course at least 6-8 weeks before the start date to guarantee there will be space available. After that date you may be placed on a waitlist. Courses with low enrollment may be cancelled up to 4 weeks before start date if sufficient enrollments are not met. If you are able to access the online application form, then registration for that particular course is still open.
This course will introduce participants to basic concepts as well as cutting-edge developments in the world of computer-aided design (CAD) as it is applied to digital manufacturing. Attendees will become familiar with the entire CAD pipeline, from developing a concept to designing a three-dimensional surface or volume. This process also highlights the virtual simulations of various materials, numerical optimizations for automatic design, and taking into account the considerations when interfacing with manufacturing hardware.
Participants will have the chance to experiment with state-of-the-art CAD software through laboratory-style activities designed to exemplify common challenges when working with CAD software and to highlight potentially interesting components of the CAD pipeline. The course will conclude with talks by industry experts who design CAD tools and apply them to large-scale engineering projects. Participants will leave with an understanding of the full stack of modern CAD and experience using state-of-the-art tools. In addition to experiencing the advantages of software-powered design for manufacturing firsthand, attendees will learn how relatively easy-to-use software and algorithms can optimize the quality of the artifacts they design. Furthermore, interaction with faculty and guest speakers will reveal best-practices, tricks of the trade, and “war stories” collected while transitioning CAD from theory to practice.
Takeaways from this Course Include:
- Understanding and manipulating the assorted expressions of geometry in a CAD system (NURBS, subdivision, volumes, point clouds, meshes, parametric models)
- Understanding the underpinnings of and experiment with assorted software/algorithms for simulating physical objects before they are manufactured
- Formulating optimization problems for improving a design based on coupling with simulation, constraints of manufacturing hardware, and design objectives
- Writing software for translating a high-level surface or volume representation into a printable object suitable for communication to hardware
- Identifying drawbacks of assorted additive and subtractive manufacturing hardware and the potential disconnect between a digitally-designed object and its printed counterpart
- Experiencing demonstrations of assorted CAD-driven manufacturing pipelines firsthand
- Recognizing assorted challenges of implementing and using CAD within larger engineering pipelines through case studies presented by industry members
Who Should Attend:
This course is designed for research scientists, engineers, developers, designers, and project managers in industries that interact with CAD software to fabricate physical objects. Relevant areas include the automotive industry, robotics, aerospace, defense, mechanical engineering, product design, computer graphics, shipbuilding, biomedical engineering, textiles, prosthetics manufacturing. Experience with specific CAD software is not needed.
Laptops or tablets with the ability to run Onshape (a full-cloud CAD system) are required for this course.
Day 1: Modeling
- Modeling surfaces (NURBS)
- Modeling volumes
- Points, meshes, and acquisition methods
- Parametric modeling
- Laboratory: Designing the boundary representation of a simple object
- Evening reception for students, faculty, and Boston-area CAD engineers
Day 2: Simulation
- Basics of mechanics
- Modeling materials
- Finite element method
- Multiphysics simulation
- Laboratory: Simulation of rigid bodies and fluids
Day 3: Design optimization
- Introduction to optimization
- Optimization of parametric models
- Topology optimization
- Laboratory: Topology optimization for minimum compliance
- Evening: Team engineering challenge combining optimization, simulation, and design
Day 4: The hardware--software interface
- Subtractive and additive manufacturing hardware and materials
- Low-level software/algorithms for manufacturing pipelines
- Demonstration of hardware and software tools
- Lab tours at MIT
Day 5: Interactive case study
- An interactive demonstration of the complete workflow
Morning: Product design, simulation/verification
Afternoon: Optimization and fabrication
- Guest speakers from industry
This course runs 9:00 am - 4:30 pm Monday through Friday.
There will be a networking reception on Monday evening, and a team engineering challenge on Wednesday evening.
Professor Wojciech Matusik is an Associate Professor of Electrical Engineering and Computer Science at the Computer Science and Artificial Intelligence Laboratory at MIT, where he leads the Computational Fabrication Group. Before coming to MIT, he worked at Mitsubishi Electric Research Laboratories, Adobe Systems, and Disney Research Zurich. He studied computer graphics at MIT and received his PhD in 2003. He also received a BS in EECS from the University of California at Berkeley in 1997 and MS in EECS from MIT in 2001. His research interests are in direct digital manufacturing and computer graphics. He holds more than 40 US patents. In 2004, he was named one of the world's top 100 young innovators by MIT's Technology Review Magazine. In 2009, he received the Significant New Researcher Award from ACM SIGGRAPH. In 2012, PI Matusik received the DARPA Young Faculty Award and was named a Sloan Research Fellow. He currently serves on the DARPA ISAT Study Group.
Professor Justin Solomon is an Assistant Professor of Electrical Engineering and Computer Science at the Computer Science and Artificial Intelligence Laboratory at MIT, where he leads a new Geometric Data Processing Group. Prior to joining the MIT faculty, Solomon was an NSF Mathematical Sciences Postdoctoral Research Fellow in Princeton's Program in Applied and Computational Mathematics. He received his PhD in computer science from Stanford University in 2015, where he also received an MS in computer science (2012) and a BS in mathematics and computer science (2010). During his PhD, Solomon was supported by the National Defense Science and Engineering Graduate Fellowship (NDSEG), the Hertz Fellowship, and the NSF Graduate Research Fellowship Program (GRFP). Solomon also has worked at Pixar Animation Studios (2007-2012) and MITRE Corporation (2005-2007). His textbook Numerical Algorithms covers numerical methods for geometry, graphics, robotics, and other computational applications.
This course takes place on the MIT campus in Cambridge, Massachusetts. We can also offer this course for groups of employees at your location. Please complete the Custom Programs request form for further details.
|Fundamentals: Core concepts, understandings, and tools||30|
|Latest Developments: Recent advances and future trends||30|
|Industry Applications: Linking theory and real-world||40|
|Lecture: Delivery of material in a lecture format||65|
|Labs: Demonstrations, experiments, simulations||35|
|Introductory: Appropriate for a general audience||50|
|Specialized: Assumes experience in practice area or field||50|