ISSSP Announces July Webinar: Strategy of Mixture Experimentation

ISSSP

Design on experiments (DOE) for mixtures will be the topic at hand for the latest webinar presented by the International Society of Six Sigma Professionals (ISSSP), being presented Wednesday, July 17 at 2 p.m. CT.

Chemical engineers Mark Anderson and Pat Whitcomb, co-authors of the DOE/RSM/Formulation Simplified trilogy, will provide valuable tips and tricks for formulation development tailored to Six Sigma. They will present experiment-design and modeling methods for mixtures through real-world examples that ultimately lead to the “sweet spot”—a formulation meeting all product specifications.

They will provide the tools to make the winning recipe robust through advanced tools for minimizing propagation of error (POE) and framing the ideal formulation window with confidence or, stronger yet, tolerance intervals.

This webinar is a must for Six-Sigma experts from all industries. “Those professionals who produce or purchase products that depend on chemistry, such as food products, pharmaceuticals, plastics and paints will find this webinar particularly helpful,” said Mark Anderson, lead presenter. 

ISSSP is the leading Six Sigma non-profit organization, providing educational and networking resources for its members. Members can access past presentations, white papers, case studies and webinars by leading Six Sigma experts and renowned leaders.

Click here for more information about registering for the webinar. For more information about ISSSP, please visit isssp.org

About ISSSP

The International Society of Six Sigma Professionals (ISSSP) is the leading non-profit organization promoting the high standards and values that Lean Six Sigma operates by. ISSSP provides access to Lean Six Sigma resources, advice on choosing accredited training providers, and opportunities for members to submit webinars, presentations and white papers.

Source: ISSSP

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About ISSSP

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Founded in 1997, ISSSP is the oldest professional organization dedicated to Lean Six Sigma.