ANFIS modeling to predict the friction forces in CNC guideways and servomotor currents in the feed drive system to be employed in lubrication control system

In this research work, Adaptive Neuro-Fuzzy Inference System (ANFIS) modeling is implemented to predict the friction force in the CNC linear guideways and servomotor current in the feed drive system in dry lubrication condition. Initially, the friction forces in the CNC linear guideways are calculated from the cutting force analysis during cutting in dry lubrication condition. Second, the servomotor currents on the X and Z-axes are measured during cutting in the same condition. Finally, ANFIS modeling to predict the friction force in CNC linear guideways and servomotor current is established using the training data obtained from cutting. Furthermore, the ANFIS prediction error and accuracy for both friction force and servomotor currents are investigated. The results demonstrate that the proposed ANFIS model can predict friction forces and servomotor currents with 1.38% and 4.1% errors, respectively. The low error percentages indicate that ANFIS modeling can be employed in a new technique for a lubrication control system for green manufacturing.