An interpretable predictive modelling framework for the turning process by the use of a compensated fuzzy logic system

Hardware implementation of Monte Carlo and RSM method for the optimization of cutting force during turning of NiTi shape memory alloy

“…The ability to predict and optimization cutting force before machining has attracted great interest from many scientists, being the main goals of many research studies. The prediction and optimization of cutting force is currently determined by using various techniques such as theoretical models [14][15], FE method [4,[15][16][17], the Taguchi procedure [1,2,11,[17][18][19][20], response surface methodology (RSM) [13,[21][22][23], the Multi-Objective Ant Lion Optimizer MOALO [21] the multi-response TOPSIS method [3,19], artificial intelligence through the use of the artificial neural networks (ANNs) [15,, genetic algorithms (GAs) [18] and fuzzy logic (FL) [26]. any research works show the use of these methods in the forecasting and also optimization of cutting force [13].…”