Discover what design of experiments (DOE) can do for you when catalyzed with DX13’s world-class statistical tools. Learn about factorial design, followed by a peek at response surface methods (RSM) for process optimization and lastly, a look into mixture design for optimal formulation.
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Date: Tuesday, November 22, 2022
Time: 10:00am Central US Time
By way of example, this presentation lays out a strategy for mixture design of experiments (DOE) that provides maximum efficiency and effectiveness for development of an ideal product recipe. It provides a sure path for converging on the ‘sweet spot’—the most desirable combination of components. Learn how to screen down many ingredients to find the vital few and then discover their optimal formulation.
Step up your design of experiments (DOE) know-how via this essential briefing on this multifactor-testing tool. A quick demo lays out what makes statistical DOE so effective for accelerating R&D. Discover how DOE will find your vital few factors and reveal breakthrough interactions.
After decades of continuous development, Design-Expert® software (DX) leads the field for making design of experiments (DOE) easy. In response to many requests from loyal users, we are proud to now produce Stat-Ease® 360 (SE360). This webinar provides a briefing on the major innovations now available with SE360, and bit of what's in store for the future.
Via a series of case studies, this webinar demonstrates multicomponent and multifactor design-of-experiment (DOE) tools for optimal formulation and refining of oil, gas and petrochemicals. See how these tried-and-true statistical methods, made easy by Stat-Ease software, empower experimenters to quickly converge on the “sweet” spot—component and factor settings that meet all specifications at minimal cost.
By way of a variety of case studies, this webinar by Mark Anderson on design of experiments (DOE) provides insights into graphical approaches (half-normal and Pareto plots) that assess effects at a glance—a huge advantage for experimenters who get overwhelmed by esoteric statistical reports. See how Stat-Ease makes selection of factor effects easy for its users.
Advance your R&D experimentation skills via this essential webinar on mixture experiments. A compelling demo lays out what makes mixture design of experiments (DOE) so effective for accelerating your formulation efforts. Discover how to: identify key characteristics leading to a mixture experiment, use mixture DOE to create optimal formulations, and map out your sweet spot with graphical tools.
Save time and costs by utilizing smaller designs! In this webinar Stat-Ease consultant, Shari Kraber, reveals the information provided by both regular-fraction versus more-modern minimum-run designs—a Stat-Ease invention. Take away a clear guide for selecting the best design based on your factorial DOE objective: screening or characterization.
Aprimore seus conhecimentos em Planejamento Experimental (Design of Experiments, DOE) por meio deste webinar que abordará os fundamentos desta ferramenta multivariada essencial. Esta explicação rápida irá mostrar porque o Planejamento de Experimentos (DOE) é uma ferramenta estatística tão eficaz para acelerar sua pesquisa e desenvolvimento. Descubra como é possível identificar fatores importantes e possíveis interações.
Discover what design of experiments (DOE) can do for you when catalyzed with DX13’s world-class statistical tools. Learn about factorial design, the core tool for DOE, followed by a peek at response surface methods (RSM) for process optimization and last, but not least, a look into mixture design for optimal formulation.
Via a series of case studies, this webinar demonstrates multicomponent and multifactor design-of-experiment (DOE) tools for optimal formulation and processing of foods. See how these tried-and-true statistical methods, made easy by Stat-Ease software, empower experimenters to quickly converge on the “sweet” spot—ingredient and factor settings that meet all specifications at minimal cost.
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Learn the differing impacts of running repeated samples or measures, versus replicating runs. Knowledge of the sources of variation in the system and the costs of replicating the DOE run and/or repeating the measure can help one decide which is the best option.
Response surface methods (RSM) provide a quick path to the peak of process performance. This webinar presents an array of RSM designs to choose from – central composite, Box-Behnken and optimal (custom). Learn when each design excels. Also find out how to handle categoric factors, discrete numeric levels and complex constraints involving multiple factors. Discover how to set up the right RSM design for your unique experimental needs.
This case-study driven webinar is a must for all who experiment on APIs. Learn how to apply statistically valid, multifactor and multicomponent testing strategies that catalyze your development work.