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Industrial Design of Experiments

Industrial Design of Experiments. STAT 321 Winona State University. Day One – Let’s get started!. Course Objectives · outline the basic steps of an industrial experiment; · design experiments using the concepts of randomization and blocking;

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Industrial Design of Experiments

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  1. Industrial Design of Experiments STAT 321 Winona State University

  2. Day One – Let’s get started! Course Objectives • ·outline the basic steps of an industrial experiment; • ·design experiments using the concepts of randomization and blocking; • ·design and analyze two level factorial and fractional factorial designs; • ·contrast Taguchi's methods with classical methods; • ·recognize examples of poor statistical statements and graphics.

  3. Design of Experiments - Definition: • A scientific method for designing the collection of information about a phenomenon or process, and then analyzing the information to learn about relations of potentially important variables. Economy and efficiency of data collection have high priorities.

  4. Advantages of DoE: • ·Process Optimization and Problem Solving with Least Resources for Most Information. • ·Allows Decision Making with Defined Risks. • ·Customer Requirements --> Process Specifications by Characterizing Relationships • ·Determine effects of variables, interactions, and a math model • ·DOE Is a Prevention Tool for Huge Leverage Early in Design

  5. Steps to a Good Experiment • Define the objective of the experiment. • Choose the right people for the team. • Identify prior knowledge, then important factors and responses to be studied. • Determine the measurement system. • Design the matrix and data collection responsibilities for the experiment. • Conduct the experiment. • Analyze experiment results and draw conclusions. • Verify the findings. • Report and implement the results.

  6. Current Industrial Usage Six Sigma Methods • Industry is training engineers, decision-makers, process owners in quality improvement methods

  7. Topics in Six Sigma Black Belt training (20 full days): • Define & Measure Phase - Week 1 • Flow chart total process • Create cause & effect diagram • Control chart project metrics • Estimate capability/ performance of project metrics • Create Pareto charts • Conduct measurement system analysis

  8. Six Sigma TrainingAnalysis Phase - Week 2 • Create multi-vari charts • Determine confidence intervals for key metrics • Conduct hypothesis tests *** • Determine variance components • Assess correlation of variables • Conduct regression analysis *** • Conduct analysis of variance

  9. Six Sigma Training Improvement Phase - Week 3 • Select designed experiment (DoE) factors and levels • Plan DoE execution • Conduct DoE • Implement variability reduction designs & assessments • Consider response surface methods

  10. Control Phase - Week 4 Six Sigma Training • Determine control plan • Implement control charts • Consider short run control charts • Consider CUSUM and moving average control charts • Consider pre-control • Mistake-proof processes

  11. To Receive Six Sigma Black Belt • 4 weeks of training • Plus, save your company $100K on an improvement project

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