Statistical_Design_of_Experiments__Team_2_Presentation__June_29

Statistical_Design_of_Experiments__Team_2_Presentation__June_29

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    The Role of Statistical Design of Experiments in Six Sigma: Perspectives of a Practitioner by T. N. Goh Summarized by Group 2
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    DMAIC Define Measure Analyze Improve Control
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    DEFINE Project selection Impact and benefit analysis Project roadmapping
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    MEASURE CTQ (critical-to-quality) identification Quality function deployment Process mapping Failure mode and effects analysis Target and specification formulation Quality benchmarking Descriptive statistics Measurement system analysis
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    ANALYZE 1. Capability analysis 2. Short-term and long-term performance indices 3. Hypothesis testing 4. Confidence intervals 5. Sample size determination 6. Identification of causes of variation 7. Multi-vari analysis 8. Analysis of variance 9. Correlation analysis 10. Regression analysis
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    IMPROVE 1. Design of experiments framework 2. Factorial designs 3. Fractional factorials 4. Balanced block designs
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Unformatted text preview: 5. Nested designs 6. Response surface designs 7. Mathematical modeling 8. Evolutionary operation CONTROL 1. Control plans 2. Tolerancing 3. Process monitoring and control 4. Mistake proofing 5. Team building 6. Documentation 7. Quality systems PROCESS CAPABILITY INDEX (CPI) Used to measure the quality of a product. CPI= Allowed amount of variation Actual amount of variation Upgrade over traditional testing and inspection, which provided damage control on the existing products, but no quality improvement and defect prevention. CPI is a tool to improve quality and prevent defects Options for Variance Reduction Materials that have parts that dont meet specifications Possible Solutions PROCESS MONITORING (passive) vs. DESIGN (active) The Future of Six Sigma...
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This note was uploaded on 10/13/2010 for the course MINE 340 taught by Professor Geinady during the Summer '04 term at University of Cincinnati.

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Statistical_Design_of_Experiments__Team_2_Presentation__June_29

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