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DOE - Design Of Experiments Training

DOE - Design Of Experiments Training - Understand and use simple methods to establish quality loss. Design simple experiments and analyze data through the 2-Step Optimization to improve process.

DOE Basic - Trainings for Six Sigma, APQP and TQM projects

DOE Basic Introduction

  • Do you believe that quality is not achieved by trial-and-error but by being designed-in?
  • Do you use one-at-a-time factor tweaking to improve quality?
  • Do you blame your operators for poor quality?
  • Do have low Process and Product yields?

Design of Experiments (DOE Basic) emphasizes the 2-Step Optimization of first reducing variation, and then, adjusting to target performance in processes and products. This course is designed on a take-back-and-do approach. The course keeps statistics to the minimum and practical aspects to the maximum so that even engineers with little mathematics can understand. Delegates should see immediate applications to improve quality and reduce loss.

Benefits Of Attending The DOE Basic Training

The DOE Basic Training enables the delegates to:

  • Understand and use simple methods to establish quality loss.
  • Design simple experiments and analyze data through the 2-Step Optimization
  • Improve processes by first reducing variability and then adjusting to target.
  • Perform confirmation experiment and calculate quality improvement.

Who Should Attend The DOE Basic Training ?

DOE Basic is particularly useful for those involved in controlling process or product parameters. It will be most appropriate for those involved in Design, Quality, R&D, Reliability, Maintenance, Engineering, Manufacturing and Production. Teams are encouraged to attend for maximum benefit.

Brief DOE Basic Training Outline

Day 1 (AM)
Quality Loss Evaluation
  • Quality loss function
  • Nominal-the-best
  • Smaller-the-better
  • Larger-the-better
Day 1 (PM)
Simple Experiments
  • Simple calculations
  • Response Table
  • Response Graph
  • Prediction
  • Basis for further work
Day 2 (AM)
Basics of Experimentation
  • Designing experiments
  • Conducting experiments
  • Performance analysis
  • Verifying experiments
  • Attribute analysis
Day 2 (PM)
Robust Quality
  • Factors
  • Conducting experiments
  • Additively, Interactions
  • Linear Graphs
Day 3 (AM)
Practical Experimentation
  • Aim, Objective
  • Brainstorming
  • Designing experiment
  • Helicopter experiment
Day 3 (PM)
Course conclusion
  • Minimize Variation
  • Achieve Target
  • Cost-Gain calculations
  • Confirm results
  • Management report
 
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