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Design of Experiments (Online Version)

Today’s semiconductor manufacturing lines require a level of precision that is unlike any other manufacturing process in the world. In order to make millions of state-of-the-art ICs exactly alike, one requires an extreme level of process control. One slight variation in any of the millions of inputs to the process can impact yield and/or performance. This is made even more complex by the tremendous amount of data produced by fab tools and test systems. Engineers need to understand process control in order to monitor and prevent these problems from occurring. This requires not only knowledge of the process, but also problem solving, statistics, and methods to identify issues. Design of Experiments Overview is a course that offers an overview on the methods, statistics, as well as the overall flow for developing a Design of Experiments (DOE) in a modern manufacturing environment. This course is designed for every manager, engineer, and technician working in the semiconductor field, using semiconductor components or supplying tools to the industry.

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What Will I Learn By Taking This Class?

By focusing on tried and true methods for DOE, participants will learn the appropriate methodology to successfully identify problems, characterize them, and determine the root cause of failure.

Participants learn to develop the skills to determine what tools and techniques should be applied, and when they should be applied. This skill-building series covers these aspects:

  1. Foundational Elements. Participants learn about the foundational elements of DOE, including: basic statistics, methods to visualize data, sampling distributions, t-Test, z-Test, Power curves, and basic problem solving.
  2. Design of Experiments. Participants learn about Analysis of Variance (ANOVA) and other DOE methods like Factorial and Taguchi methods.

Course Objectives

  1. The seminar will provide participants with an in-depth understanding of the tools, techniques and methods used in DOE.
  2. Participants will be able to identify the different techniques to analyze data related to a Design of Experiments.
  3. The seminar will identify the advantages and disadvantages of the various techniques for DOE.
  4. The seminar offers a variety of example problems, so the engineer can gain an understanding of the types of issues they might expect to see in their job assignment.
  5. Participants will be able to set up a Design of Experiments to gather more data related to a particular problem.

Course Outline

  1. Introduction to DOE
  2. Comparing Distributions
    • t-Test
    • z-Test
    • Power Curves
  3. Analysis of Variance (ANOVA)
    • Sum of Squares
    • ANOVA Table
    • Randomized Block Experiments
    • Two Way Designs
  4. Factorial Designs
    • Two-Level Factorials
    • Fractional Factorials
    • Analysis of Factorials
  5. Taguchi Method
    • Categorizing Process Variables
    • Signal-to-Noise Ratio
    • Orthogonal Arrays
    • Data Analysis
  6. In-class Exercises: Design of Experiments
  7. Wrap-Up Discussion