Modeling of friction stir welding process using adaptive neuro-fuzzy inference system integrated with harris hawks optimizer

摘要: Abstract Friction Stir Welding (FSW) has been paid more attention in recent years due to its efficiency welding materials that are difficult weld by conventional fusion methods. There several parameters affect FSW process, so it is important understand the relationship between different process maximize quality and strength of joint. This paper proposed an alternative method predict make a decision using modified version adaptive neuro-fuzzy inference system (ANFIS) integrated with harris hawks optimizer (HHO). HHO was used search for optimal values ANFIS determine operating conditions process. The shared effect speed, tool rotational plunge force on mechanical properties welded aluminium plates simulated. model, called ANFIS-HHO, Al terms ultimate tensile (UTS) as functions force. adequacy model tested; predicted data were good agreement experimental data. speed empirical index (EFI) have significant impact joints. ANFIS-HHO technique found be powerful optimization predicting achieve high joint strength.