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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

Industrial Design of Experiments

STAT 321

Winona State University

day one let s get started
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
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
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
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
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 training analysis phase week 2
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
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
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
To Receive Six Sigma Black Belt
  • 4 weeks of training
  • Plus, save your company $100K on an improvement project