Online courses directory (19947)
This course aims to give students the tools and training to recognize convex optimization problems that arise in scientific and engineering applications, presenting the basic theory, and concentrating on modeling aspects and results that are useful in applications. Topics include convex sets, convex functions, optimization problems, least-squares, linear and quadratic programs, semidefinite programming, optimality conditions, and duality theory. Applications to signal processing, control, machine learning, finance, digital and analog circuit design, computational geometry, statistics, and mechanical engineering are presented. Students complete hands-on exercises using high-level numerical software.
Acknowledgements
The course materials were developed jointly by Prof. Stephen Boyd (Stanford), who was a visiting professor at MIT when this course was taught, and Prof. Lieven Vanderberghe (UCLA).
This course examines relationships among technology, culture, and politics in a variety of social and historical settings ranging from 19th century factories to 21st century techno dance floors, from colonial Melanesia to capitalist Massachusetts. We will be interested in whether technology has produced a better world, and for whom.
This workshop is designed to help you write clearly, accurately and effectively in both an academic and a professional environment. In class, we analyze various forms of writing and address problems common to advanced speakers of English. We will often read one another's work.
This is an advanced course on modeling, design, integration and best practices for use of machine elements such as bearings, springs, gears, cams and mechanisms. Modeling and analysis of these elements is based upon extensive application of physics, mathematics and core mechanical engineering principles (solid mechanics, fluid mechanics, manufacturing, estimation, computer simulation, etc.). These principles are reinforced via (1) hands-on laboratory experiences wherein students conduct experiments and disassemble machines and (2) a substantial design project wherein students model, design, fabricate and characterize a mechanical system that is relevant to a real world application. Students master the materials via problems sets that are directly related to, and coordinated with, the deliverables of their project. Student assessment is based upon mastery of the course materials and the student's ability to synthesize, model and fabricate a mechanical device subject to engineering constraints (e.g. cost and time/schedule).
This course was created for the "product development" track of MIT's System Design and Management Program (SDM) in conjunction with the Center for Innovation in Product Development. After taking this course, a student should be able to:
- Formulate measures of performance of a system or quality characteristics. These quality characteristics are to be made robust to noise affecting the system.
- Sythesize and select design concepts for robustness.
- Identify noise factors whose variation may affect the quality characteristics.
- Estimate the robustness of any given design (experimentally and analytically).
- Formulate and implement methods to reduce the effects of noise (parameter design, active control, adjustment).
- Select rational tolerances for a design.
- Explain the role of robust design techniques within the wider context of the product development process.
- Lead product development activities that include robust design techniques.
