Design of Experiments (DoE) facilitates the screening for relevant factors and the optimization of the latter in terms of one or several responses. The number of factors that can be included in screening designs is substantial, but may still be a bottleneck if complex processes with interdependent steps have to be optimized.
Here we present an iterative approach to structure the multi-parameter problem and illustrate how challenges regarding the experimental implementation of a design can be handled.
[Slides and video from this presentation are not currently available. The research is ongoing. Once the results are published they will be posted.]
Non-ionic surfactants are an important component of industrial metalworking cleaners. For beverage can manufacturing these cleaners need to deliver good cleaning performance with low foaming properties. These attributes can be strongly influenced by different types of non-ionic surfactants.
With the help of Design-Expert® software an experimental design was set up to find an optimal balance between three selected surfactants. The experimental formulations were tested for foaming properties and cleaning performance. All experimental data was analyzed by the software to calculate models with good fit.
Stratasys’ PolyJet technology jets a thin layer of resin materials onto the surface, which is then polymerized on the surface using UV light. The process is then repeated multiple times, each layer adding thickness to the model.
When jetting ink for 3D printing, a support material must be also printed beneath model material overhangs. Due to the printing sequence and the internal environment inside the printer, the support material must have a certain resilience and thermal stability, and provide adequate surface quality of the model post support removal.
The primary topic of this experiment was to add thermal stability to the support material, as the existing formulation would melt as ambient temperature increased during the printing process. Since runs are expensive, a goal is to use a minimal number of trials.
The control of ingredients quantities in pharmaceutical formulations is critical to a drug product quality. Often, the Active Pharmaceutical Ingredient (API), and sometimes specific excipients, concentrations testing in the final product is required to release a batch.
By applying Design of Experiments (DoE) and Multi-Variate Data Analysis (MVDA), a UV-Vis spectroscopy chemometric model has been developed which is capable of measuring simultaneously both ingredients contents in the formulation. The test can easily be applied to finished or bulk product and the results are immediately available.