ProSensus is excited to announce that we will be attending this year’s AIChE Spring Meeting in New Orleans from March 31 – April 4, 2019. We are looking forward to showcasing our expertise and recent work, and we hope to see you there. Here are the places and times that you are most likely to find us:
- ProSensus’ exhibit booth from Sunday evening through to Wednesday morning.
- Our booth will showcase our full collection of advanced analytics offerings and solutions.
- General information on the expo is available here.
- ProSensus’ poster in the Industry 4.0 and Big Data Reception on Tuesday at 5:15-6:30pm.
- This poster will highlight our expertise in the area of Rapid Product Development (RPD).
- ProSensus’ joint presentation with Dow Chemical on Wednesday at 1:30pm in Marlborough A.
- Read the full abstract here or at the bottom of this page.
- This talk will summarize our latest work for Dow on the RPD of Silicone Antifoams.
- Topics to be covered include the development of: a multi-block multivariate model, constrained optimization, and customized software.
- This talk is part of the session called Big Data Analytics – Industry Perspective II.
Accelerating Product Innovation at Dow through Multivariate Modeling
Brandon Corbett1, Marlene Cardin1, Kristin Wallace1, Alix Schmidt2, Haseeb Moten3 and Rebecca Beeson3, (1) ProSensus, Burlington, ON, Canada, (2) Continuous Improvement Center of Excellence, The Dow Chemical Company, Midland, MI, (3) Dow Consumer Solutions, Dow Chemical Company, Midland, MI
In the era of Industry 4.0, manufacturers such as Dow are focused on gaining more value from their historical data than ever before. ProSensus has distinguished itself as a trusted, global leader in Big Data analytics by helping many Fortune 500 companies across numerous industries use their data to innovate for the future.
ProSensus has recently worked with Dow to accelerate innovation on one of their key product lines – silicone antifoams. For product development applications such as this, ProSensus combines powerful multi-block latent variable modeling with constrained optimization. This approach allows clients to simultaneously optimize the selection of raw materials, recipe formulations, manufacturing conditions and costs to reach targeted product performance properties while adhering to custom constraints. A model-based approach allows Dow to rapidly develop and scale up custom silicone antifoam formulations for the dynamic technical and regulatory needs of customers in the pulp and paper, food and beverage, wastewater treatment, metal working, and other industries.
This presentation will examine the approach taken (data assembly, multivariate modeling, model validation, and optimization), challenges encountered, and results obtained. Perspectives from both ProSensus and Dow will be included.