Modelling and prediction of thrust force and torque in drilling operations of Al7075 Using ANN and RSM methodologies

URN:NBN:SI:DOC-VC494N7N2018Efkolidis, NikolaosGarcía-Hernández, CésarHuertas-Talón, José-LuisKyratsis, Panagiotisdocuments/doc/V/URN_NBN_SI_doc-VC494N7N_001.pdfdocuments/doc/V/URN_NBN_SI_doc-VC494N7N_001.txt664articlestr. 351-3610039-248016112155URN:NBN:SI:doc-VC494N7NengslvZveza strojnih inženirjev in tehnikov Slovenije etc.Strojniški vestnikInCAl7075artificial neural networksmetodologija odzivne površinemomentpodajalna silaresponse surface methodologysustainable manufacturingthrust forcetorquetrajnostna proizvodnjaumetne nevronske mrežeModelling and prediction of thrust force and torque in drilling operations of Al7075 Using ANN and RSM methodologies