Discover methods for creating experiment designs progressively so that knowledge can be gained steadily via iterative steps. Learn how to augment completed designs that fall short of adequately modeling the critical response(s). This might salvage a great deal of experimental work that would otherwise go for naught.
Renforcez votre savoir-faire sur les Plans d’Expériences (DOE) grâce à ce webinaire sur cet outil de test multifactoriel. Une démonstration rapide vous expliquera pourquoi les DOE sont si efficaces pour booster votre R&D et vous aider à approfondir vos procédés. Découvrez comment les DOE permettent d’identifier vos facteurs critiques et de mettre en lumière les interactions essentielles.
Before embarking on expensive experiments, it often pays to mine existing data. It may be gold, or it may be garbage, but why not try? This webinar demonstrates how easily Stat-Ease software imports results so you can then apply its powerful tools for evaluation, analysis and optimization.
Learn how Python has been integrated into Stat-Ease 360. This tutorial walks through connecting Python, extracting data from SE360, and some other more complex examples.
This talk features four examples making use of Design-Expert’s comprehensive design-building facilities to build the desired design while not revealing everything to DX.
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.