G2

Supriyo D.

Research Scientist

Enterprise (> 1000 emp.)

11/7/2019

"Perfect tool for design, screening and optimization of experiment"

4.5/5

What do you like best about Design-Expert?

I am using Design expert (Version 8.0.7.1) from last so many years. As I am working in formulation development research, I am quite familiar with this software for designing screening and optimization of experiment. We are generally doing both formulation as well as process screening/optimization using this software. It is loaded with so many designs like factorial design, optimal design, Plackett-Burman design, Taguchi design, response surface designs etc. it demonstrated the interpretation of statistical models and linking it to chemical understanding. It helps to understand potentially significant factor and their cause-and-effect relationships on an experimental outcome. It is loaded with lots of graphical representation which provide ease understanding about the effect of variety of factors at different levels. It has also features like mixer design which is very useful in optimization of formulation. Also I can easily identify about the interaction effects of different factors. Also in 2-level factorial design you can select number of experiments based on design resolution (res III, res IV, res V). Another good feature is that this application is very easy to use and organized. Review collected by and hosted on G2.com.

What do you dislike about Design-Expert?

There are not so much limitations for design expert, as it is very beautiful and perfect application for designing experiment. The graphical representation could be better for easy understanding and perfect representation. Review collected by and hosted on G2.com.

Recommendations to others considering Design-Expert:

Definitely use it for designing, screening or optimization of experiments Review collected by and hosted on G2.com.

What problems is Design-Expert solving and how is that benefiting you?

This application helps in identifying potentially significant factor that may experimental outcome. It identifies suitable responses to measure the effect of changes in factors. It helps to identify design space. It also easily identifies interaction effect of different factors. It provides a platform to us to make experiments using qbd (Quality by design) approach. Ultimately it provides a pathway to deliver a quality formulation. Review collected by and hosted on G2.com.