Over the next few decades, we are going to transition to a new economy where highly complex, customizable products are manufactured on demand by flexible robotic systems. This change is already underway in a number of fields. 3D printers are revolutionizing production of metal parts in aerospace, automotive, and medical industries. Manufacturing electronics on flexible substrates opens the door to a whole new range of products for consumer electronics and medical diagnostics. Overall, these new machines enable batch-one manufacturing of products that have unprecedented complexity.
This course gives an introduction to the new field of computational design that is essential for the next revolution in manufacturing. Participants will be given an overview of the advanced manufacturing hardware, methods for creating digital materials, and computational design of objects at voxel-level. The course will cover generative design workflows that automatically translate functional specifications of objects to manufacturable designs. The course will also introduce participants to AI methods for computational design that utilize expert knowledge and large data repositories. Finally, the course will showcase new workflows for design across multiple domains (e.g., shape, materials, control, and software) that simplify the process and fully utilize the design space.
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.
- Understand capabilities and limitations of current advanced manufacturing hardware.
- Learn how to design digital materials and how to compute their physical properties.
- Understand voxel-based representations for computational manufacturing.
- Experience demonstrations of hierarchical material designs.
- Design and manufacture objects using multi-material additive manufacturing.
- Understand principles of generative design.
- Design objects using topology optimization methods.
- Learn how AI methods can aid design workflows.
- Understand how new concurrent design workflows can simplify design of complex integrated systems.
- Optimize a design across multiple domains.
Who Should Attend:
This course is designed for research scientists, engineers, developers, designers, and project managers in industries that are involved in translating concepts to physical objects/products. 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 and additive manufacturing is not needed.
Laptops or tablets with Windows and with which you have administrator privileges are required for this course.
Course introduction and overview
Multi-material digital manufacturing
- Introduction to multi-material 3D printing
- Introduction to digital materials and multi-material composites
- Translating between multi-material composites and material properties
New directions for declarative design
- Voxel-level design
- Multi-material hierarchical design
- Scalable software architectures
Lab 1: Multi-material design and 3D printing
Generative design workflows
- Introduction to generative design
- Topology optimization
- Multi-material generative design
Next generation design optimization workflows
- Interactive design space exploration and optimization
- Translating functional requirements to manufacturable designs
Lab 2: Design for 3D printing using topology optimization
AI tools for computational design
- Expert systems for computational design
- Data-driven/machine learning methods for computational design
Automating design across multiple-domains
- Introduction to concurrent design
- Integrated design tools for domain-specific applications
Lab 3: Integrated design and optimization of custom drones
This course runs 9:00 am - 5:00 pm Monday through Wednesday.
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.
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%)||30|
|Latest Developments: Recent advances and future trends (40%)||40|
|Industry Applications: Linking theory and real-world (30%)||30|
|Lecture: Delivery of material in a lecture format (45%)||45|
|Discusson or Groupwork: Participatory learning (25%)||25|
|Labs: Demonstrations, experiments, simulations (30%)||30|
|Introductory: Appropriate for a general audience (40%)||40|
|Specialized: Assumes experience in practice area or field (40%)||40|
|Advanced: In-depth explorations at the graduate level (20%)||20|