Continuous Improvement without Mathematics using GPC

Management approaches for Continuous Improvement, using approaches and tools such as 6-sigma, lean, and statistical process control (SPC) are tremendously successful in reducing process variation and improving performance. Limitations include high training requirements in mathematical statistical methods and the general restriction to single-variable statistics.

Geometric Process Control (GPC) as implemented in C Visual Explorer (CVE) expands this dramatically, giving engineers the tools for self-service multivariate investigation and analytics visually, without a statistical background, allowing every engineer to participate and drive continuous process improvement.

This webinar introduces the technology and tools that allow multi-variate visualization across hundreds of variables, finding sources of process variability, ideal operating targets and places where multi-modal operation may be confounding analysis. These tools are entirely visual, allowing them to be used without statistics or data science backgrounds, leveraging the existing intuition and knowledge of process and operations engineers.

We’ll spend a little time looking at CPM as well, identifying changes in multi-variate relationships, identifying changes in these relationships allowing rapid response to new variation.

We will use live demonstrations throughout, showing how you can easily make use of this technology in your process.