Case Studies and White Papers
Fun and educational science projects for children and/or adults that demonstrate the value of design of experiments. Originally published Jan 2021; updated Jun 2024.
Updated version for 2024. Originally published in 2010.
The statistical design of experiments is an essential ingredient of successful product development and improvement, and provides an efficient and scientific approach to obtaining meaningful information. In contrast to traditional vary one-factor-at-a-time (OFAT) experimentation, variables are changed together, permitting evaluation of interactions. Standard texts give details about the construction of specific test plans, such full and fractional factorial, and response surface designs, and the analysis of the resulting data. This article gives a brief overview. The focus here is on the fundamental elements of experimental design: defining the purpose and scope of the experiment, differentiating between alternative types of experimental variables, understanding the underlying environment and constraints, and conducting stage-wise experimentation. Brief discussions dealing with the statistical analysis tools, multiple response variables, and some historical background are also provided.
The temperature dependence of the Mn⁴⁺ photoluminescence and lifetime has been measured in the red emitting K₂SiF₆:Mn⁴⁺ phosphor that is sold under the trade name, TriGain®. In the range 12-450 K, the ²E → ⁴A₂ emission intensity increases considerably while the lifetime decreases. Above 450 K, rapid decrease in the intensity and lifetime is observed. The results are interpreted in terms of dynamically induced increases in the emission intensity and decay rate coupled with an Arrhenius-type thermal quenching. The parameters of our fitting to physical models are compared with those reported on laboratory synthesized K₂SiF₆:Mn⁴⁺ phosphor. This comparative study sheds light on factors responsible for non-radiative relaxation processes, which is fundamental to the understanding of phosphor quantum efficiency and performance. The temperature dependence of the Stokes to anti-Stokes vibronic line intensity ratios is also measured and analyzed. Due to low thermal conductivity of K₂SiF₆, it was necessary to develop protocols to ensure that the surface temperature of the phosphor was close to that of the cold finger in the closed cycle He cryostat.
Chocolate Chip Cookie Mixture
Most people like Chocolate Chip Cookies, some like them soft and others like them crispy. The difference between soft and crispy is the thickness, height, and density of the cookie. This experiment will go through and measure the effectiveness that different combinations of the ingredients have on Chocolate Chip Cookies. The objective is to find the cookie resulting in the best taste and appearance.
The objective of the experiment is to identify and analyze the effects of 4 different ingredients, cooking temperatures, and cooking time. The experiment will be a KVC Model, mixture model.
This article details a delightful experiment that can be done at home or in class to illustrate the advantage of multifactor testing over the traditional one-factor-at-a-time (OFAT) scientific method. It uncovers multiple interactions that surprisingly cancel out OFAT main effects.
Energized by new tools in version 13 of Design-Expert (DX13) for modeling counts, Engineering Consultant Mark Anderson tests a cellphone app against built-in timing on his microwave for minimizing unpopped kernels (UPK). DX13 paves the way to nearly perfect popcorn via its Poisson-regression count-modeling capability.
Ever-increasing demand for monoclonal antibodies (mAbs) makes it imperative that their production be continually improved for cost, quality and yield. Design of experiments (DOE), by its multifactor testing methodology and statistical rigor, provides a sure path to mAb process optimization. This was demonstrated recently in a series of tests at a biotechnology company. By using the tools of DOE versus the traditional scientific method of one-factor-at-a-time (OFAT) experimentation, its mission was achieved in a matter of weeks rather than months with a far more comprehensive mapping of process conditions.
Response Surface Methods Point the Way to Higher rAAV Yields at Lower Levels of Transfection Reagent
Researchers at Adverum Biotechnologies have demonstrated that a novel multifactor design of experiments (DOE) methodology can optimize production of a recombinant adeno-associated virus (rAAV) vector. The methodology, an advanced form of DOE that incorporates response surface methods (RSMs), focused on the relative amounts of transfection agent polyethylenimine (PEI) and DNA.
This methodology is unique because of the way it keeps the ratio of PEI nitrogen to DNA phosphate—the N/P ratio—within a specified range. The N/P ratio is well known to influence the rAAV yields obtained via transient transfection.
Industrial product development can often be a frustrating process, especially in the case of formulations. Many commercial formulated products can have 20 or more components. With so many possibilities for multi-component blending effects to impact performance, it is difficult to optimize a formulation without design of experiments (DOE).
This case study explores how chemists at Quaker Houghton (Conshohocken, PA) explored reformulating an existing product to improve performance and reduce cost. Their use of Design-Expert led to discoveries they didn't expect.
Case studies, complete with data, that cover a wide range of applications of DOE in engineering and science. The collection is ideal for teachers and students of DOE. It is also useful for those who want to learn more about the power of DOE methods or who are looking for research ideas.
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