Join JMP and Solvay industrial scientist Francisco Navarro for a webinar on optimising production process using JMP software.
Engineers, scientists and other industrial data explorers need their process data to be accessible and interactive. In the recording of this live session, you will discover how to better understand and optimise your processes via powerful interactive visualisations and point and click advanced analytics.
Learn how to effectively use explainable machine learning to select relevant tags (sensors) while capturing non-linear interactions. All steps are demoed for a concrete case but apply throughout the chemical industry.
- The industrial data analytics life cycle
- The value of providing quick access to industrial data in historians
- Learn how bootstrap forest and partition trees can filter tags (sensors)
- Capture non-linear interactions using neural networks
- Recommend corrective action based upon analytical findings
Speaker: Francisco Navarro
Industrial data scientist and chemical engineer at advanced materials and speciality chemicals company Solvay
Navarro helps solve challenging optimisation and process engineering problems for a wide array of industries around the globe by transforming operations through digital and industrial data analytics, which it uses on top of advanced control and process engineering. He has a PhD in modelling and simulation.
Moderator: Benjamin Valsler
Digital Editor, Chemistry World
Ben Valsler is the digital editor of Chemistry World magazine, producing video and podcasts to accompany the magazine and website. Prior to joining the Royal Society of Chemistry, he was the producer of the award-winning Naked Scientists, making local and national radio programmes for the BBC, the Australian Broadcasting Corporation and Primedia in South Africa.