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2.830J/6.780J Control of Manufacturing Processes

2.830J/6.780J Control of Manufacturing Processes (SMA 6303) (Spring 2008, MIT OCW). Taught by Prof. David Hardt and Prof. Duane Boning, 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. (from ocw.mit.edu)

Lecture 11 - Introduction to Analysis of Variance

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Lecture 01 - Introduction - Processes and Variation Framework

Lecture 02 - Semiconductor Process Variation

Lecture 03 - Mechanical Process Variation

Lecture 04 - Probability Models of Manufacturing Processes

Lecture 05 - Probability Models, Parameter Estimation, and Sampling

Lecture 06 - Sampling Distributions and Statistical Hypotheses

Lecture 07 - Shewhart SPC and Process Capability

Lecture 08 - Process Capability and Alternative SPC Methods

Lecture 09 - Advanced and Multivariate SPC

Lecture 10 - Yield Modeling

Lecture 11 - Introduction to Analysis of Variance

Lecture 12 - Full Factorial Models

Lecture 13 - Modeling Testing and Fractional Factorial Models

Lecture 14 - Aliasing and Higher Order Models

Lecture 15 - Response Surface Modeling and Process Optimization

Lecture 16 - Process Robustness

Lecture 17 - Nested Variance Components

Lecture 18 - Sequential Experimentation

Lecture 19 - Case Study 1: Tungsten CVD DOE/RSM

Lecture 20 - Case Study 2: Cycle to Cycle Control

Lecture 21 - Case Study 3: Spatial Modeling

Lecture 22 - Case Study 4: Modeling the Embossing/Imprinting of Thermoplastic Layers