Design of Experiments (DOE) for
Semiconductor Manufacturing and Development

This one-day course provides industrial workers with the definitions, models and statistical tools needed for designing efficient and effective experiments. A working knowledge of “Statistical Design of Experiments,” as covered in this class, is one of the most powerful tools a worker can have for designing and/or improving industrial products and processes.

Next Available Course Dates:

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We offer this and all courses as On Site Training


WHAT THE COURSE COVERS:
  • Plan effective and efficient experiments
  • Design two-level full factorial and fractional designs
  • Understand how to use response surface designs to find optimal process settings
  • Become familiar with software DOE tools such as SAS JMP
  • Benefits of designed experiments
  • Choosing factors and factor levels
  • Importance of randomization 
  • Orthogonal coding
  • Two-level full factorial designs
  • Analyzing residuals and testing for lack of fit
  • Screening designs
  • Fractional factorial designs
  • Response surface designs
  • Optimizing process settings
  • Use of the JMP DOE Platform for designing experiments and analyzing experimental data


WHO SHOULD ATTEND?
  • This course is targeted towards industrial workers who can benefit from using effective statistical methods to characterize, model, evaluate, monitor and improve the quality and reliability of products, manufacturing processes and equipment Manufacturing Engineers

This course includes copies of the slides used during the class. The class will also make use the on-line NIST/SEMATECH e-Handbook of Statistical Methods. A soft copy of the Handbook will be provided on a handout CD-ROM.

INSTRUCTOR:
Dr. Paul Tobias currently offers consulting and training services for industrial clients. He retired from International SEMATECH, a semiconductor manufacturing research consortium, after managing the Statistical Methods Group for 9 years.

After receiving his PhD. in Mathematical Statistics from Columbia University, he spent 25 years as a statistician and manager at IBM’s semiconductor facility in East Fishkill, New York. During those years his primary focus was on modeling and projecting field reliability for new integrated circuit technologies and setting up field return and failure analysis monitoring systems.

Dr. Tobias has published over 40 technical reports and journal articles and he is the co-author of the textbook "Applied Reliability", now in its 2nd edition. He was the co-editor for the creation of the on-line NIST/SEMATECH e-Handbook of Statistical Methods. In addition, he has chaired several International Semiconductor Standards Task Forces that added statistical methodology to the E10 Equipment Reliability Standard and created a new Standard for Measurement Capability Analysis, E89. He currently holds the position of Technical Editor for the Semiconductor Equipment and Materials International Organization (SEMI ) Metrics Committee and he is the Treasurer for the annual American Statistical Association Quality and Productivity Research Conference.

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