You can’t believe that data – it’s just noise. Oh yeah, try this – DOE!

by admin_root

You can’t believe that data – it’s just noise. Oh yeah, try this – DOE!

by admin_root

by admin_root

Take a look at the Six Sigma toolbox and you’ll find a whole host of useful, effective instruments including DFSS and DMAIC. One of the most valuable of all is Design of Experiments (DOE). Much more than an ordinary tool, DOE is an approach, technique, and method designed to uncover relationships often hidden inside mountains of data. Most importantly, it’s the secret to distinguishing between noise and real factors that have real effects.

Within the structure of a Six Sigma project, DOE provides for the identification of factors in a process that contribute to particular effects. Six Sigma professionals can then create meaningful tests that verify possible ideas or theories for improvement.

If these ideas sound familiar, that’s because they’re the essence of all methods based on inferential statistics. For a “real world” example, look to Nate Silver’s bestseller, The Signal and the Noise: Why So Many Predictions Fail – but Some Don’t.

What is it about DOE that makes it such an essential tool for producing reliable data and opportunities for process improvements?

DOE is the Key to Unlocking ROI Again and Again

At the heart of DOE is ROI. The statistical tool works to improve the data delivered by  the testing phase of the project at hand. ROI comes into play as DOE helps deliver data that can guide future process improvements. Furthermore, the approach highlights cause and effect that may exist within different factors present in the project. These cause and effect relationships may affect the results produced by the process.

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But the actual capabilities of DOE extend far beyond merely separating variation labeled as noise and variation identified as an effect. Six Sigma professionals rely on DOE to optimize processes and products. The powerful tool allows you to quantify effects as well as build mathematical models and simulations. DOE can also be used to decipher and control variations as well as increase the predictability of processes.

DOE has a number of benefits and possibilities for application including:

  • Reduction of variability to ensure the same quality of output
  • Comparison of alternatives solutions
  • Achieve desired output and level of quality by determining which changes to make in the process
  • Selection of design experiments that will deliver the target results

To discover how to achieve similar benefits and results in your organization, register for NWCPE’s upcoming Module SS 505 – Intro to Design of Experiments.

 

Training in DOE for Real World Application and Success
In the world of process design and improvement, DOE is always welcome. Apply it whenever it is possible and practical to do so to achieve maximum ROI. To immerse yourself in DOE with a practical and easy to understand approach, register for NWCPE’s Module (DOE) SS 505 – Intro to Design of Experiments, where you’ll learn how to unlock the most powerful Six Sigma related tool of all.

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