Day 1: Product and Process Optimization
- Introduction
- The product design process
- Developing manufacturing processes
- The history and nature of tolerances
- Tolerance assignment practices
- Attributes versus variables data
- Developing appropriate acceptance tests
- Reliability testing versus acceptance testing
- Operating characteristic curves and their application
- Acceptance testing risk
- Hypothesis testing
- Using z-tests and t-tests for hypothesis testing
- Excel’s features for evaluating the normal curve, the z-test, and the t-test
- ANOVA history
- The f-test
- ANOVA’s mathematical underpinnings
- Using Excel to accelerate ANOVA
- Case studies
Day 2: Fractional Factorial Experiments
- Brief review of prior material
- The “scientific method” versus design of experiments
- Full factorial experiments
- Fractional factorial experiments
- Taguchi philosophies
- Taguchi test approaches
- Identifying potential test parameters
- Selecting the appropriate Taguchi matrix
- Assigning factors to Taguchi columns
- Assessing potential factor interactions
- Identifying appropriate factor levels
- Defining Taguchi test sample configurations
- Identifying appropriate output parameters for evaluation
- Minimizing Taguchi test risks
- Mathematically evaluating Taguchi test results
- Assessing signal-to-noise significance
- Follow-on Taguchi tests
- Using Excel features to accelerate the process
- Case studies
- Recap, Q/A, and evaluations
(Optional Third-day): Experiment Design Workshop
The participants will work together under the instructor’s guidance to analyze a product or process design issue in your organization.