I've been tasked with taking up some modeling (perhaps predictive) for chemical formulations and some resultant performance characteristics. I have experience with finite element analysis (mechanical and fluid) and some more basic statistics, which identified me as a candidate for taking this on. I'd like to learn more in order to better understand this request.
I'm being trained by someone and it seems the software my company is using for this is Dassault iSight.
- I'm a bit disadvantaged as it was hard for me to search this site without even understanding the proper terminology. I'm hoping someone with iSight experience (or from scanning the page) could let me know what "class" of software this is -- neural network? Machine learning? Bayesian modeling? Predictive analysis?
- Might I be pointed to some resources to learn more about this type of modeling so I can understand what iSight is doing on a more theoretical level?
- If someone knows iSight, are there other packages that aim to do the same? I'm not sure how they chose this software package; if something else would be better suited (preferably in R, which I have experience with), I'd love to know about it.
For reference and without getting very specific we've conducted a DOE of various chemical formulation ratios for a material and have five or so responses we've tested on each of our ~80 lots. Now we're looking to determine the interactions between the X's (formulation components) as well as how the X's affect the Y's (performance attributes).
I realize this is a total noob/ignorance question... just looking to understand the proper terminology and direction for learning more as it's been hard to search on my own.