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Module Summary
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Design of Experiment (DOE) is a powerful statistical technique for improving product/process designs and solving production problems. A standardized version of DOE, as forwarded by Dr. Genichi Taguchi, allows one to easily learn and apply it in manufacturing and production problem investigations. Since its introduction in the U.S.A. in early 1980's, the Taguchi approach of DOE has been a design optimization tool in the hands of the engineering and scientific professionals.
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Topics of Discussion
DAY 1
Overview- concepts of quality engineering
- New Definition of Quality
- Loss to the society from poor quality
- Standardized technique
Review basic concepts in experimental design
- Types of factors and levels
- Common experiment designs
- Orthogonal array vs. one-factor-at-a-time
experiments
Project objective Evaluation Criteria
- Need for combining multiple evaluation criteria into a single index
Experiments designed using orthogonal arrays
- Experiments with all factors at two levels
- Experiments mixed level factors
- Experiments with all factors at three levels
- Experiments with all factors at four levels
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DAY 2
Experiments to study interaction
- Trade off between factors and interactions
- Test for presence of interactions
- Test for relative influence of interaction
Basic analysis and strategy for experimentation
Dealing with mixed level factors
- Upgrading 2-level columns into a 4-level array
- Downgrading (dummy treatment) columns
- 15 different experiments using an L-8 array
Experiment Planning Review
- TEAM: the new disciplines in workplace
- Order of discussions in planning session
- Participants and facilitation of planning
Measuring cost of quality by Loss Function
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Who Should Attend
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Product/Process Design Engineer, R&D Scientists, or QA Personnel, Manufacturing. Manager, Plant Managers and Production technicians.
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