and see what we might do for your bottom line.

Our methodology contains six steps combining experimental design, software analytics, and empirical data from laboratory simulations.
First, a scientific examination of the target process is performed to determine if it is a good candidate for application of the technology.
Next, we set optimization objectives and design process simulations to achieve them. We then perform the simulations using state-of-the-art methods at our facilities.
Then simulation data is input into our analytics software which performs the analysis. A new list of process variable combinations is generated to use for the next simulation.
Each of these analysis cycles represents a generation. After less than 20 generations over a time span of usually much less than 8 months, an optimized combination of variables emerges. The result will be a better profit margin through higher process yield, more efficient production, or other objectives established at the beginning of the engagement.