Parameter optimization of pulsed Nd:YAG laser for obtaining desired cut characteristic using Taguchi technique and ANN

2^nd World Congress on Automation and Robotics

June 13-15, 2016 Philadelphia, USA

Sachin Salunkhe and Mahesh Kulkarni

JSPM Narhe Technical Campus, India

Posters & Accepted Abstracts: Adv Robot Autom

Abstract :

The current requirement of the industrial sector with respect to machinability of work piece, work piece shape complexity, miniaturization, automation of data communication, surface integrity and precision requirement and introduction of newer material and products is unseen before. Thus there exists need to explore the possibilities of tackling the issue by adopting high-end technologies like LASER machining. Laser cutting is serial, stochastic and dynamic in nature. It demands to control the behavior of heat (energy imbibed through laser beam) and fluid flow (assist gas) with respect to work piece properties (optical, thermal and geometry). The numbers of process variables are very high. Each variable affects the process output, also the interaction of these variables leads to different results. Thus the laser cutting process assumes very complex nature. Laser cut is characterized by top kerf width, bottom kerf width, heat affected zone, dross and material removal rate. In the current work attempts are made to minimize the top kerf width, bottom kerf width and maximize the material removal rate. The control over the kerf width ultimately controls the heat-affected zone (HAZ) and hence no separate attempts are made to control HAZ. The design of experiments and Taguchi technique application are applied to obtain the required process parameter. An artificial neural network (ANN) model is developed for optimization of process parameter of pulsed Nd:YAG laser. The proposed ANN model is trained by using experimental data of process parameters.

Biography :

Email: kashid32@gmail.com