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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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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;

  • ·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.


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.


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


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.


Current Industrial Usage

Six Sigma Methods

  • Industry is training engineers, decision-makers, process owners in quality improvement methods


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


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


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


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


To Receive Six Sigma Black Belt

  • 4 weeks of training

  • Plus, save your company $100K on an improvement project


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