Design of Experiments - Basic Simplified Taguchi

Design of Experiments is a statistically based, structured approach to product or process improvement that will quickly yield significant increases in product quality and subsequent decreases in cost.  Products and processes can be designed to function with less variation and with less sensitivity to environmental factors or customer usage. While still maintaining high quality from a customer's viewpoint, products and processes can utilize lower cost materials and methods.  Specifications can be opened-up with wider tolerances while still maintaining high quality for customers.  In summary, products and processes can be designed and developed in shorter times to reduce costs and become more competitive in the marketplace from a delivery and profit standpoint.

This course covers the fundamentals required in planning, conducting, and analyzing orthogonal experiments, which are the major steps in the Design of Experiments (DOE) process.  Emphasis is placed on the DOE process, which, if diligently followed will yield an effectively completed experiment. 

An introduction to parameter design is included. A short video introduces the experimental approach; the end of the session allows practice with the new methods in a hands-on workshop.

What Will You Learn

By attending this course, you will be able to:
  • Choose appropriate factors and factor levels to effectively plan DOEs
  • Define an appropriate set of tests to evaluate the chosen factors and levels
  • Utilize appropriate randomization strategies and choose appropriate sample sizes for conducting tests for DOE
  • Utilize basic analytical methods to identify influential & non-influential factors in analyzing and interpreting DOE results
  • Set specification limits for all factors for effective performance and low cost

Is This Course For You

This course is designed for product and process design engineers, manufacturing engineers, quality engineers, testing and development engineers. Although it would be helpful, no statistical education or background is required for this course; only fundamental mathematical skills are necessary.

Materials Provided

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Course Requirements

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Topics

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