OPTIMIZATION OF LASER CUTTING PROCESS PARAMETERS ON SS347 USING GRA AND TOPSIS

Laser cutting is a one of the e +/- cient manufacturing processes in industry to cut the hard materials by vaporizing. Stainless steel (SS347) is the most popular material for many applications due its unique characteristics such as e +/- ciency to retain good strength with no inter-granular corrosion even at elevated temperatures. However, the cutting or machining of this material is very di +/- cult. On the other side, the machining cost of laser process is high when compared with other processes. In this work, GRA and TOPSIS techniques are used to study the laser cutting process parameters of SS347. The obtained results were compared with the data mining approach. The input parameters are power, speed, pressure and stand-o (R) distance (SOD) and the output responses of surface roughness, machining time and HAZ are considered. The set of experiments were constructed by using the Taguchi's L9 method. The predicted closeness value of TOPSIS is greater than the GRA technique and the predominant factor observed is SOD followed by pressure, speed and power. In this work, C4.5-decision tree algorithm is applied to <overline>nd the most in degrees uential parameter. It also represents the low-level knowledge of data set into high level knowledge (If-Then rules form). This investigation reveals that both TOPSIS and data mining suggested the SOD as predominant factor. This result of the optimized process parameters supports the laser assisted manufacturing industries by providing optimized output. Better results were obtained using the optimized set of parameters with the machining time, HAZ and surface roughness being 7.83 s, 0.09mm and 0.86 mu m, respectively. The results of this work would be very useful for automobiles and aircrafts industries where SS347 is highly employed.