Case Studies and White Papers
How Experimental Design Optimizes Assay Optimization
Optimizing biological assay conditions is a demanding process that scientists face daily. The requirement is to develop high-quality, robust assays that work across a range of biological conditions. The demand is to do this within a short time frame. To overcome these obstacles, automated assay optimization (AAO) systems often are used to accommodate large numbers of samples. Applying DOE to AAO is essential to make the best use of this high-tech equipment.
Screening Process Factors In The Presence of Interactions
This article introduces a new, more efficient type of fractional two-level factorial design of experiments (DOE) tailored for the screening of process factors. These designs are referred to as Min Res IV.
Success with DOE
A basic primer, taken from "DOE Simplified" text, on underlying statistics and simple forms of DOE.
To simplify formulation tasks when searching for hot-melt solutions, Stepan Co. developed a design of experiments (DOE) mapping' approach to their new ortho-phlathic-based polyol products. They wanted to discover how the products work within their specific applications. Requires login to view.
Researchers at Exatec, LLC, determined that the oscillating sand test reveals better wear assessment information for polycarbonates. This finding has allowed the company to optimize coating processes.
Changing and then re-testing just one parameter at a time still seems to be the norm for the formulation chemist, but it is not the most productive approach. In fact, this shotgun approach increases the probability of missing the best possible finished product. A more reliable and expedient method of optimizing a formulation is by design of experiments (DOE).
Unearthing Optimum Soil Treatments
Weak subgrade soils are often chemically treated, or modified, to add strength and stability to support the heavy construction vehicles required for building highways. DOE was used to develop a treatment that enabled contractors to quickly establish stable subgrades.
Combining Computer-Aided Statistical Design of Experiments with Traditional Design of Experiments to Meet EC2000 Criteria
New ABET criteria require that chemical engineering students be able to ﾓdesign and conduct experiments. Experimental design may be interpreted as either developing methods and procedures to achieve experimental goals, or as statistical Design of Experiments (DOE). Auburn University's Dept. of Chemical Engineering incorporates both approaches in their unit operations lab course to satisfy EC2000 criteria and achieve beneficial learning outcomes.
Keys to Successful Designed Experiments
We can improve experimentation results by studying organizations that have experienced both frustrations due to poor experimentation methodology and satisfaction from successful applications. This paper identifies eight factors essential to successful experimentation. A solid understanding of these key factors is the foundation to a successful design of experiments program.
Mixture design is used to develop a predictive model for estimating an entire range of glaze colours with far fewer test tiles than are normally required.