Session 2: Insights Revealed via DOE
Discover an easier, faster way to take on your most complex chemical engineering data challenges. Join this two-session webinar and learn how JMP software can help you analyze data more effectively, improve your approach to designing experiments and broaden your knowledge of how to use data to solve problems. Learn how to save your company time and money using the powerful statistical analysis tools you’ll see in action here.
Through a case study, you’ll walk through the entire experimental process, starting with data gathering and cleanup. You’ll discover which factors are important and design an experiment to efficiently create a model for these factors. You’ll also examine how to analyze the experiment, use the results to set meaningful and robust specification limits and verify that the now-improved process does not drift over time.
See the concepts you learn demonstrated using JMP software:
Session 2: Insights Revealed via DOE
Next, you’ll identify the yield issue within the organized data. You’ll see how to run the experiment, assess results and optimize the process while saving your company time and money. Via a model-driven multivariate control chart and root cause data analysis, you’ll deepen your understanding of the process and how to know it is in control.
Learn how to organize the featured data in the previous webinar, Session 1: Yield Data Exposed. Click here to learn more about this webinar.
You’ll learn:
• How factors relate to output via mathematical models
• How to analyze data from multiple sources
• How to design efficient experiments tailored to specific problems
• How to evaluate the results of experiments and choose specific settings to maximize value
Sponsored webinars bring technical information from reputable firms and suppliers to AIChE members. The content reflects the views, opinions, and recommendations of the sponsoring organization. AIChE does not warrant or represent, expressly or by implication, the correctness or accuracy of the content of the information presented. As between (1) the AIChE, the presenter and author(s) of this work, their employers, and their employers' officers and directors, and (2) the user/viewer of this work, the user/viewer accepts any legal liability or responsibility whatsoever for the consequence of its use or misuse. Contact information for attendees of this webinar, including email address, will be shared with the sponsoring firm. You will always have the opportunity to unsubscribe from email from that organization.
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