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Control of Manufacturing Processes

MIT, , Prof. David Hardt

Overview

Introduction Processes and Variation Framework - Semiconductor Process Variation - Mechanical Process Variation - Probability Models of Manufacturing Processes - Probability Models, Parameter Estimation, and Sampling - Sampling Distributions and Statistical Hypotheses - Shewhart SPC and Process Capability - Process Capability and Alternative SPC Methods - Advanced and Multivariate SPC - Yield Modeling - Introduction to Analysis of Variance - Full Factorial Models - Modeling Testing and Fractional Factorial Models - Aliasing and Higher Order Models - Response Surface Modeling and Process Optimization - Process Robustness - Nested Variance Components - Sequential Experimentation - Case Study 1: Tungsten CVD DOE/RSM - Case Study 2: Cycle to Cycle Control - Case Study 3: Spatial Modeling - Case Study 4: Modeling the Embossing/Imprinting of Thermoplastic Layers.

Includes

Lecture 1:

4.1 ( 11 )

Lecture Details

Lecture 1 Introduction -- processes and variation frameworkInstructor Duane Boning, David HardtView the complete course at httpocw.mit.edu2-830JS08License Creative Commons BY-NC-SAMore information at httpocw.mit.edutermsMore courses at httpocw.mit.edu

Ratings

3.4


24 Ratings
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Comments
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Sam

Excellent course helped me understand topic that i couldn't while attendinfg my college.

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Dembe

Great course. Thank you very much.

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