Control of Manufacturing Processes
MIT, , Prof. David Hardt
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Updated On 02 Feb, 19
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.
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Lecture 5 Probability models, parameter estimation, and sampling Instructor 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
Sep 12, 2018
Excellent course helped me understand topic that i couldn't while attendinfg my college.
March 29, 2019
Great course. Thank you very much.