23 episodes

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.

Control of Manufacturing Processe‪s‬ MIT

    • Technology

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.

    • video
    Control Lab Video

    Control Lab Video

    • 15 min
    • video
    Lecture 01: Introduction — processes and variation framework

    Lecture 01: Introduction — processes and variation framework

    • 1 hr 5 min
    • video
    Lecture 02: Semiconductor process variation

    Lecture 02: Semiconductor process variation

    • 1 hr 25 min
    • video
    Lecture 03: Mechanical process variation — physical causes and interpreting data

    Lecture 03: Mechanical process variation — physical causes and interpreting data

    • 1 hr 27 min
    • video
    Lecture 04: Probability models of manufacturing processes

    Lecture 04: Probability models of manufacturing processes

    • 1 hr 22 min
    • video
    Lecture 05: Probability models, parameter estimation, and sampling

    Lecture 05: Probability models, parameter estimation, and sampling

    • 1 hr 21 min

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