Monte Carlo Tree Search for high precision manufacturing

Weichert, Dorina, Horchler, Felix, Kister, Alexander, Trost, Marcus, Hartung, Johannes, Risse, Stefan

arXiv.org Artificial Intelligence 

They can be treated as deterministic, as the noise of the manufacturing Monte Carlo Tree Search (MCTS) has shown its outcomes influence the processing result only to a minor strength for a lot of deterministic and stochastic extent. In this paper, we deal with the less common case examples, but literature lacks reports of applications of high precision manufacturing: here, the manufacturing to real world industrial processes. Common tolerances of the different processing steps are in the range reasons for this are that there is no efficient simulator of the product tolerance. As the manufacturing outcomes of the process available or there exist problems vary, the chain of manufacturing steps has to be adapted.