MIT / Engineering / Mechanical
Lecture : Introduction Processes and Variation Framework
By David Hardt | Control of Manufacturing Processes
Lecture 1 of 22
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Course Description
This course explores statistical modeling and control in manufacturing processes. Topics include the use of experimental design and response surface modeling to understand manufacturing process physics, as well as defect and parametric yield modeling and optimization. Various forms of process control, including statistical process control, run by run and adaptive control, and real-time feedback control, are covered. Application contexts include semiconductor manufacturing, conventional metal and polymer processing, and emerging micro-nano manufacturing processes.
Courses Index
1 : Introduction to MEMS Design   (Clark Nguyen / Berkeley)
2 : Introduction to Solid State Chemistry   (Donald Sadoway / MIT)
3 : Atomistic Computer Modeling of Materials   (Gerbrand Ceder / MIT)
4 : Symmetry, Structure, and Tensor Properties of Materials   (Bernhardt Wuensch / MIT)
5 : Underactuated Robotics   (Russell Tedrake / MIT)
6 : Supply Chain Management   (Multiple Instructors / MIT)
7 : X PRIZE Workshop: Grand Challenges in Energy   (Erika Wagner / MIT)
8 : Special Topics in Mechanical Engineering : The Art and Science of Boat Design   (Christopher Dewart / MIT)
9 : Various Sources of Energy - Seminar   (Multiple Instructors / Stanford)
10 : Nonlinear Finite Element Analysis   (Klaus-Juurgen Bathe / MIT)
11 : Renewable Energy and Alternative Fuels   (Weismann . / Berkeley)
12 : Engineering for the Future   (Multiple Instructors / UC Davis)
13 : Manufacturing Processes   (Multiple Instructors / UC Irvine)