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Day 1
Introduction
- Definition of Production Problems
- Assumption and Expected Solution
- Strategy and Approach
Experiments Using Standard Orthogonal Arrays
- Design of Experiment Basics
- Experiments with 2-level Factors
- Full Factorial Design with Seven 2-level Factors
- Tools for Experiment Designs
- Three Major Steps in Applications
- Procedure for Experiment Planning (Brainstorming)
Results with Multiple Criteria of Evaluations - Analysis of Results Experiment Designs with Larger Number of Factors
Basic Experiment Design and Analysis strategy
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Day 2
Designs With Interactions
- Understanding Interactions
- Scopes of Interaction Studies
- Experiment Design for Interaction
Studies
- Application Examples
- Testing for Presence of Interaction
- Correction of Performance Prediction Based on Interaction
- Overview of Analysis of Variance (ANOVA)
Designs with Mixed Levels and Interactions
- Column Upgrading 7 Downgrading
Robust Design Principles
Noise Factors and Outer Array Designs
S/N Ratio Analysis
Quantification of Benefits from Performance Improvement
- Brief overview of Taguchi LOSS FUNCTION
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Who Should Attend
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Product/Process Design Engineer & Technicians and QA Personnel, Manufacturing. Managers, production problem solving specialists. Consultant and Trainer (who wish to help their clients work with interdisciplinary teams and optimize product designs and solve production problems)
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