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Activity Number: 503 - SPAAC Poster Competition
Type: Topic Contributed
Date/Time: Wednesday, August 2, 2017 : 10:30 AM to 12:20 PM
Sponsor: Scientific and Public Affairs Advisory Committee
Abstract #324182
Title: Utilizing Statistical DOE and Modeling to Understand Foaming for Low VOC Paint Formulations
Author(s): Wenyu Su* and Jeff Sweeney and Sudhakar Balijepalli and Sushma Sanketh and Caroline Hinson
Companies: The Dow Chemical Company and The Dow Chemical Company and The Dow Chemical Company and The Dow Chemical Company and Texas A&M University
Keywords: Statistical DOE ; Statistical Modeling ; High-Throughput ; Foaming ; Low VOC ; Paint

Due to recent environmental concerns, many commercial paint manufacturers want their products to utilize only low Volatile Organic Compound (VOC) materials. However, low VOC paint formulations tend to form air bubbles (foaming) resulting in noticeable film defects when bubbles break during application and drying. Thus, a project was initiated at The Dow Chemical Company to investigate how film foaming defects can be minimized. Dow's High-Throughput (HT) equipment was employed to collect 'foaming' experimental data utilizing efficient statistical experimental design (DOE). The Optimal DOE strategy reduced the total amount of lab work required by 2 months but yet still enabled the fitting of a relevant statistical model. From the statistical modeling, the impact of the factors was determined and promising formulations were identified to minimize foaming defects. Also star plots provided an effective way to graphically compare the formulations with respect to the various defect measurements considered. This poster demonstrates the power of statistical DOE for HT research coupled with statistical modeling and graphical model representations in low VOC paint formulation development.

Authors who are presenting talks have a * after their name.

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