Control of Manufacturing Processes - MIT OpenCourseWare · PDF fileAgenda • The...

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MIT OpenCourseWare http://ocw.mit.edu 2.830J / 6.780J / ESD.63J Control of Manufacturing Processes (SMA 6303) Spring 2008 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms.

Transcript of Control of Manufacturing Processes - MIT OpenCourseWare · PDF fileAgenda • The...

  • MIT OpenCourseWare http://ocw.mit.edu

    2.830J / 6.780J / ESD.63J Control of Manufacturing Processes (SMA 6303) Spring 2008

    For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms.

    http://ocw.mit.eduhttp://ocw.mit.edu/terms

  • Control of Manufacturing

    Processes

    Subject 2.830/6.780/ESD.63 Spring 2008 Lecture #2

    Semiconductor Process Variation

    February 7, 2008

    Manufacturing 1

    http:2.830/6.780/ESD.63

  • Agenda The Semiconductor Fabrication Process

    Manufacturing process control

    Types of Variation in Microfabrication Defects vs. parametric variations Temporal variations: wafer to wafer (run to run)

    Spatial variations: wafer, chip, and feature level

    Preview of manufacturing control techniques Statistical detection/analysis of variations Characterization/modeling of processes & variation Process optimization & robust design Feedback control of process variation

    Manufacturing 2

  • Semiconductor Fabrication Process, Part 1

    R. J. Shutz, in Statistical Case Studies for Industrial Process Improvement, pp. 470-471, SIAM, 1997.Manufacturing Courtesy of the Society for Industrial and Applied Mathematics. Used with permission.

    3

  • Semiconductor Fabrication Process, Part 2

    R. J. Shutz, in Statistical Case Studies for Industrial Process Improvement, pp. 470-471, SIAM, 1997.Manufacturing Courtesy of the Society for Industrial and Applied Mathematics. Used with permission.

    4

  • Semiconductor Fabrication Process, Part 3

    R. J. Shutz, in Statistical Case Studies for Industrial Process Improvement, pp. 470-471, SIAM, 1997.Manufacturing Courtesy of the Society for Industrial and Applied Mathematics. Used with permission.

    5

  • Semiconductor Fabrication Process, Part 4

    R. J. Shutz, in Statistical Case Studies for Industrial Process Improvement, pp. 470-471, SIAM, 1997.Manufacturing Courtesy of the Society for Industrial and Applied Mathematics. Used with permission.

    6

  • (Semiconductor) Manufacturing

    Process Control

    Image removed due to copyright restrictions. Please see Fig. 26 in Boning, D. S., et al. A General Semiconductor Process Modeling Framework. IEEE Transactions on Semiconductor Manufacturing 5 (November 1992): 266-280.

    Manufacturing 7

  • Agenda The Semiconductor Fabrication Process

    Manufacturing process control

    Types of Variation in Microfabrication Defects vs. parametric variations Temporal variations: wafer to wafer (run to run)

    Spatial variations: wafer, chip, and feature level

    Preview of manufacturing control techniques Statistical detection/analysis of variations Characterization/modeling of processes & variation Process optimization & robust design Feedback control of process variation

    Manufacturing 8

  • Defect vs. Parametric Variation

    Manufacturing 9

  • Yield & Variation from Defects Electrical test

    measure shorts in test

    structures for different spacings between patterned lines (at or

    near the design rule or DR

    feature size)

    measure opens in other test

    structures

    Images removed due to copyright restrictions. Please see: Hess, Christopher. "Test Structures for Circuit Yield Assessment and Modeling." IEEE International Symposium on Quality Electronics Design, 2003.

    Manufacturing Hess, ISQED 2003 Tutorial 10

  • Manufacturing 11

  • Manufacturing 12

  • Temporal Variation

    Manufacturing 13

  • Manufacturing 14

  • Manufacturing 15

  • Spatial Variation

    Wafer scale Chip scale Feature scale

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  • Manufacturing 27

  • Modeling of Processes

    and Variation

    Empirical modeling Physical modeling

    Manufacturing 28

  • Manufacturing 29

  • Manufacturing 30

  • Manufacturing 31

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  • Manufacturing 33

  • Manufacturing 34

  • Manufacturing 35

  • Manufacturing 36

  • Manufacturing 37

  • Manufacturing 38

  • Manufacturing 39

  • Process Optimization & Robust Design

    Manufacturing 40

  • Manufacturing 41

  • Image removed due to copyright restrictions. Please see Fig. 7 in Lakshminarayanan, S., et al. Design Rule Methodology to Improve the Manufacturability of the Copper CMP Process. Proceedings of the IEEE International Interconnect Technology Conference (2002): 99-101.

    Manufacturing 42

  • Feedback Control of Variation

    Manufacturing 43

  • EQUIPMENT MATERIALCONTROLLER

    The General Process Control Problem Desired

    MATERIAL ProductProduct

    EQUIPMENTCONTROLLER

    Equipment loop

    Material loop

    Process output loop

    Control of Equipment:

    Forces,

    Velocities

    Temperatures, ...

    Control of Material

    Strains

    Stresses

    Temperatures,

    Pressures, ...

    Control of Product:

    Geometry

    and

    Properties

    Manufacturing 44

  • Manufacturing 45

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  • Summary The Semiconductor Fabrication Process

    Manufacturing process control

    Types of Variation in Microfabrication Defects vs. parametric variations Temporal variations: wafer to wafer (run to run)

    Spatial variations: wafer, chip, and feature level

    Preview of manufacturing control techniques Statistical detection/analysis of variations Characterization/modeling of processes & variation Process optimization & robust design Feedback control of process variation

    Manufacturing 55

    Control of Manufacturing ProcessesAgenda(Semiconductor) Manufacturing Process ControlAgendaDefect vs. Parametric VariationYield & Variation from DefectsTemporal VariationSpatial VariationModeling of Processes and VariationProcess Optimization & Robust DesignFeedback Control of VariationThe General Process Control ProblemSummary