Experimental Study and Optimization of Energy Consumption During end Face Turning of AISI 4140

This study focuses on energy consumption during “end face” turning operation of AISI 4140 steel under dry conditions. An experimental study was conducted to establish the energy consumption model based on the specific machine parameters, considering crucial machining parameters such as feed rate
$(f)$
, cutting speed (
$v$
), and depth of cut
$(a_{p})$
. This study led to a formula using multiple regression model which represents energy consumption of a machine lathe. Subsequently, the Genetic Algorithm (GA) optimization technique parameters were calibrated using the Taguchi design with L16 orthogonal array table. With the goal of minimizing energy consumption, this optimization approach was performed using tournament selection. This integrated approach between experimental studies and optimization provides a reliable means to continuously improve manufacturing processes, thereby contributing to a more economy use of energy.