A molecular simulation based computational intelligence study of a nano-machining process with implications on its environmental performance

摘要: Abstract Determining the optimum input parameter settings (temperature, rotational velocity and feed rate) in optimizing properties (strength time) of nano-drilling process can result an improvement its environmental performance. This is because essential component power consumption during drilling therefore by determining appropriate value required optimization properties, trial-and-error approach that normally results loss waste resources be avoided. However, effective requires formulation generalized explicit mathematical model. In present work, Boron Nitride Nanosheet (BNN) panels studied using model formulated a molecular dynamics (MD) based computational intelligence (CI) approach. The consists nano scale modeling MD simulation which further fed into paradigm CI cluster comprising genetic programming, was specifically designed to formulate relationship nano-machining BNN panel with respect temperature, drill bit. Performance proposed evaluated against actual results. We find our integrated able very well, used complement analytical solution developed simulation. Additionally, we also conducted sensitivity parametric analysis found temperature has least influence, whereas highest influence on panel.