Accelerate your progress by understanding your system and knowing what to try next.
Experimental and production systems can be hard to understand. When multiple inputs interact, it becomes difficult to comprehend what’s driving outcomes, thus slowing optimization and leading to missed targets – and when measurements change over time, that information is often underused because it is difficult to assemble and interpret.
Modeling offers a practical way forward, uncovering complex relationships in data and turning them into useful guidance.
In this on-demand webinar, you will learn how to build a model that fits your data and use the Prediction Profiler to visualize your system. Explore “what-if” questions and see how to explain your results clearly to others.
Key takeaways:
How modeling can uncover complex relationships in your data.
How JMP helps you build a model that fits your data.
How to visualize and understand complex systems quickly.
How to interpret curves and profiles over time when measurements change during a run or batch.
How to explore “what-if” questions and communicate results clearly, even to non-specialists.
What if I’m new to modeling?
No prior experience is required. This webinar provides thorough explanations, peer insights, and short demos that are suitable for any skill level.
Speakers
Jonas Rinne and Ben Barroso-Ingham
Systems Engineers at JMP
Jonas Rinne and Ben Barroso-Ingham are Systems Engineers at JMP who bring together deep technical expertise and a practical approach to data analysis. Rinne has a background in mechanical engineering and materials science, with Ph.D. research focused on laser welding process development at Leibniz University Hannover. Barroso-Ingham draws on his experience as an upstream and analytical scientist in biotechnology, with strengths in data analysis, statistical modeling, and design of experiments. Together, they help scientists and engineers make better use of their data, tackle complex challenges, improve processes, and communicate results with clarity.
