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2.830J 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)

Introduction


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

References
2.830J/6.780J Control of Manufacturing Processes
Instructors: Prof. David Hardt and Prof. Duane Boning. Lecture Notes. Exams and Solutions. Assignments and Solutions. This course explores statistical modeling and control in manufacturing processes.