Semiconductor Statistics

A modern semiconductor manufacturing process is one of the most difficult and complex processes to successfully control. There are thousands of variables that must all be tightly controlled in order to have a chance at repeatedly manufacturing a chip within a tight tolerance so that it can be successfully used in an electronics system. Furthermore, a modern semiconductor manufacturing process generates an incredible volume of data. This requires that engineers be able to not only choose the right data to examine, but also examine it in such a way as to understand the behavior of the process. We do this through statistical process control. This course is designed specifically for engineers who work in semiconductor manufacturing operations. We provide numerous real-world examples from semiconductor operations such as wafer fabrication, assembly, test, and reliability.

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Course Dates | Location

May 22-23, 2017 | Munich, Germany
(Price available until Mon. May 1)

Cost

$1,295
$1,195

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Please fax the printable registration form for public courses to us at 1-866-205-0713 to complete your order.

Additional Information

For dates and locations in South East Asia, please contact us at se-asia.courses@semitracks.com.

Refund Policy

If a course is canceled, refunds are limited to course registration fees. Registration within 21 days of the course is subject to $100 surcharge.

What Will I Learn By Taking This Class?

By focusing on tried and true methods for SPC, 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 is divided into four segments:

  1. SPC Foundational Elements. Participants learn about the foundational elements of statistical process control, including: basic statistics, methods to visualize data, process capability, and basic problem solving.
  2. Process Monitoring Techniques. Participants learn the various techniques for monitor a semiconductor process. They discuss on-wafer measurements like thin film measurements, defects, and electrical measurements.
  3. Process Control. Participants learn about the various control charts and how to identify key variables in process control charts. They also discuss the fundamentals of process control and the various control methods.
  4. 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 SPC.
  2. Participants will be able to identify the different methods to visualize data related to SPC.
  3. The seminar will identify the advantages and disadvantages of the various control charts that are used for SPC.
  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.
  6. Participants will understand the types of data on might gather, related to SPC.
  7. Participants will be able to set up a control chart and monitor it for excursions and analyze the results.

Course Outline

Day 1

  1. Wafer Fab Related SPC
    1. Statistical Process Control
      1. Control Chart Basics
      2. Control Charts for Variables
      3. Moving Average Charts
      4. X and R, S
      5. How to Monitor a Control Chart
      6. Multiple Equipment same process control charts
      7. Multivariate Control
      8. Distributions
      9. Cusum Charts
    2. Process control index Cpk and Ppk
    3. Defect Density & Yields
    4. Wafer Acceptance Test parameters
      1. Sort yield & Defect Density
      2. Set outlier limit
      3. Statistical Bin Limits methodology
    5. Design of Experiments
      1. Randomized Block Experiments
      2. Two Way Designs
      3. Student T-test
      4. Analysis of Variance (ANOVA)
      5. ANOVA Table
      6. Taguchi Methods
  2. Assembly and Packaging Related SPC
    1. Variables
    2. Control Charts for Variables
    3. Process Capability Index (Cpk) - Review
    4. Multiple Equipment
    5. DOE Bonding optimization

Day 2

  1. Test Related SPC
    1. Gauge Repeatability & Reproducibility Principles
    2. Test Limits
    3. SBL Setting
    4. Tester correlations
    5. Average Outgoing Quality
    6. Sample Size, AOQ, LTPD, etc.
    7. Confidence interval
    8. Exercises with Marvell-supplied data
  2. System Level Test Related SPC
    1. Reliability Statistics
    2. Distributions
      1. Normal Distributions
      2. Lognormal Distributions
      3. Weibull Distributions
      4. Exponential Distribution
    3. Gathering Accelerated Testing Data
    4. PPM and FITS Calculation
    5. Exercises with Marvell-supplied data
  3. Reliability Statistics
    1. Gathering Accelerated Testing Data
    2. In-class Exercise: Determining Time to Failure
    3. Using the Poisson Distribution to Estimate PPM, FITS
    4. In-class Exercise: PPM and FITS Calculation
  4. Field Returns and SPC
  5. Wrap-Up Discussion

Instructional Strategy

By using a combination of instruction by lecture, video, problem solving and question/answer sessions, participants will learn practical approaches to the failure analysis process. From the very first moments of the seminar until the last sentence of the training, the driving instructional factor is application. We use instructors who are internationally recognized experts in their fields that have years of experience (both current and relevant) in this field. The handbook offers hundreds of pages of additional reference material the participants can use back at their daily activities.

Instructor Profile

Christopher Henderson, President of Semitracks

Christopher Henderson

Christopher Henderson received his B.S. in Physics from the New Mexico Institute of Mining and Technology and his M.S.E.E. from the University of New Mexico. Chris is the President and one of the founders of Semitracks Inc., a United States-based company that provides education and semiconductor training to the electronics industry.

From 1988 to 2004, Chris worked at Sandia National Laboratories, where he was a Principal Member of Technical Staff in the Failure Analysis Department and Microsystems Partnerships Department. His job responsibilities have included failure and yield analysis of components fabricated at Sandia's Microelectronics Development Laboratory, research into the electrical behavior of defects, and consulting on microelectronics issues for the DoD. He has published over 20 papers at various conferences in semiconductor processing, reliability, failure analysis, and test. He has received two R&D 100 awards and two best paper awards. Prior to working at Sandia, Chris worked for Honeywell, BF Goodrich Aerospace, and Intel. Chris is a member of IEEE and EDFAS (the Electron Device Failure Analysis Society).

At Semitracks, Chris teaches courses on failure and yield analysis, semiconductor reliability, and other aspects of semiconductor technology.