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 seminar 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.

For more advanced study, attend C0714 ANOVA for Design of Experiments. It is strongly recommended that any registrant attend a Basic Design of Experiments course prior to taking the advanced course.

What Will You Learn

By attending this seminar, 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 seminar 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

This data is not available at this time

Course Requirements

This data is not available at this time


  • Training Objectives
  • Design Of Experiments Background
    • DOE definition
    • DOE and Taguchi history
    • DOE in the product life cycle
    • implementation strategy
  • Design Of Experiments Process
    • flowcharts
    • injection molding case study
    • water pump leak case study overview
  • Planning Phase
    • state problem(s)
    • state objective(s)
    • determine measurement method(s)
    • quality characteristic(s)
    • select factors
    • identify control and noise factors
    • select levels of factors
    • select orthogonal array
    • assign factors
    • locate interactions
    • modification of standard orthogonal arrays
    • parameter design
  • Conducting The Experiment
    • trial data sheets
    • testing logistics & assignments
    • identification of trial results
    • sample size per trial
    • randomization
    • good and bad data sets
  • Analyzing And Interpreting Results
    • observation method
    • column effects method
    • plotting
    • ranking
    • analyzing variability
    • factor classification
    • attribute data
    • interpreting experimental results
    • confirmation experiment
  • Experimental Workshop
    • popcorn experiment review
    • pendulum experiment