Get more insights from fewer experiments
Efficient experimentation can save both time and money in the long term when it helps optimize product or process performance. This webcast shows how a dynamic model can dramatically improve outcomes.
Who doesn't hope to get the most insights from the fewest experimental trials?
Efficient experimentation can save both time and money in the long term when it helps optimize product or process performance. And that's where a dynamic model can dramatically improve outcomes.
This presenter demonstrates how he quickly identifies performance trade-offs by building an interactive process model in JMP. A strategically designed model helps you to weigh performance goals and find the best trade-off in performance among multiple responses. Drawing on the example of a multi-layer packaging film development process, the presenter shows how he balances multiple factor ranges and types to inform and streamline experimentation. Among other key takeaways, you'll learn how JMP enables you to customize experimental design in order to test only those factors that have the biggest impact on your processes.
Watch the webcast
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