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DOE Dynamic Characteristics Training

DOE Dynamic Characteristics Training

DOE Dynamic Characteristics - Trainings for Six Sigma, APQP and TQM projects

DOE Dynamic Characteristics Introduction

  • Do you customize product features for your customers?
  • Do you need to optimize a family of products?
  • Do you have a feature that the user can vary over a wide range?
  • Do you have analogue and digital dependent products that need optimization?

Design of Experiments Dynamic Characteristics (DOE Dynamic Characteristics) is a very advanced method for studying quality characteristics where the characteristic can be controlled by the operator. There are several methods that can be used for continuous-continuous, continuous-digital, digital-continuous and digital-digital systems. Delegates will be able to design and develop original processes and products in the most systematic and efficient way.

Benefits Of Attending The DOE Dynamic Characteristics Training

The DOE Dynamic Characteristics Training enables the delegates to:

  • Use Dynamic Characteristics with continuous (C) and digital (D) functions.
  • Apply C-C, C-D, D-C and D-D techniques where appropriate.
  • Use orthogonal polynomial techniques for fitting curves.
  • Conduct complex and advanced research at a professional level.

Who Should Attend The DOE Dynamic Characteristics Training ?

DOE Dynamic Characteristics 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 Dynamic Characteristics Training Outline

Day 1 (AM)
Dynamic Characteristics
  • Classification
  • Line through zero
  • Line through mean
  • Line through reference
Day 1 (PM)
Information transfer
  • Continuous-Digital
  • Digital-Continuous
  • Examples
Day 2 (AM)
Digital-Digital
  • 1 signal
  • Example
  • Example
Day 2 (PM)
Digital-Digital
  • 2 signal
  • Example
  • Example
Day 3 (AM)
Methodology
  • Example
  • Simulation
  • Data analysis
Day 3 (PM)
Course conclusion
  • Discussion
  • Summary
  • Close
 
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