Hi guys, this is more general question. I have successfully implemented LSTM models for anomaly detection for IoT devices, super thanks to deeplearning4j.
Now I got another possible case on my table. Imagine there is building. In such building there is input of some material and machines (multiple machines for different type of purpose), material flows trough these machines by processing input material (can be steel blocks, etc. simply some material which has some attributes: weight, size, but much more). Now we have 3D modeled and existing simulations of this material flow trough machines in building (modeled by humans), all modeled in very low detail. This you can see as fully featured model of manufacturing with detail to button on some panel.. What do you think AI can help here especially by improving the efficiency of process, so flow of material is improved and time of result stuff produced is reduced. In very gross numbers how difficult will be design and implement such AI - I am looking only for some kind of prototype? Thanks for feedback.
I am more interested what type of approach already existing could be used for such type of stuff. AI is used already for make shape of objects more efficient by studying physics and improving shape for aircrafts, so I am looking for something similar except my "physic laws" are in form of "process configuration - buidling size, machines size/speed/etc, material attributres, humans working with machinery capabilities.. I understand this is already quite challenging task, but can someone just point me to correct direction of possibly existing study paper/sample prototype?