Modeling and optimization on Nd:YAG laser turned micro-grooving of cylindrical ceramic material

Nd:YAG laser turning is a new technique for manufacturing micro-grooves on cylindrical surface of ceramic materials needed for the present day precision industries. The importance of laser turning has directed the researchers to search how accurately micro-grooves can be obtained in cylindrical parts. In this paper, laser turning process parameters have been determined for producing square micro-grooves on cylindrical surface. The experiments have been performed based on the statistical five level central composite design techniques. The effects of laser turning process parameters i.e. lamp current, pulse frequency, pulse width, cutting speed (revolution per minute, rpm) and assist gas pressure on the quality of the laser turned micro-grooves have been studied. A predictive model for laser turning process parameters is created using a feed-forward artificial neural network (ANN) technique utilized the experimental observation data based on response surface methodology (RSM). The optimization problem has been constructed based on RSM and solved using multi-objective genetic algorithm (GA). The neural network coupled with genetic algorithm can be effectively utilized to find the optimum parameter value for a specific laser micro-turning condition in ceramic materials. The optimal process parameter settings are found as lamp current of 19 A, pulse frequency of 3.2 kHz, pulse width of 6% duty cycle, cutting speed as 22 rpm and assist air pressure of 0.13 N/mm² for achieving the predicted minimum deviation of upper width of ?0.0101 mm, lower width 0.0098 mm and depth ?0.0069 mm of laser turned micro-grooves.