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

D. Srinivasan (), H. Ramakrishnan, R. Balasundaram () and M. Ravichandran ()
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D. Srinivasan: Department of Mechanical Engineering, K. Ramakrishnan College of Engineering, Samayapuram, Tiruchirappalli 621112, Tamil Nadu, India
H. Ramakrishnan: Department of Mechanical Engineering, K. Ramakrishnan College of Engineering, Samayapuram, Tiruchirappalli 621112, Tamil Nadu, India
R. Balasundaram: ��Department of Mechanical Engineering, SRM Institute of Science and Technology, Irungalur, Tiruchirappalli Campus 621105, Tamil Nadu, India
M. Ravichandran: Department of Mechanical Engineering, K. Ramakrishnan College of Engineering, Samayapuram, Tiruchirappalli 621112, Tamil Nadu, India

Surface Review and Letters (SRL), 2023, vol. 30, issue 06, 1-13

Abstract: Laser cutting is a one of the efficient 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 efficiency to retain good strength with no inter-granular corrosion even at elevated temperatures. However, the cutting or machining of this material is very difficult. 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-off 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 find the most influential 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, 0.09 mm and 0.86 μm, respectively. The results of this work would be very useful for automobiles and aircrafts industries where SS347 is highly employed.

Keywords: Stainless steel; laser cutting; GRA; TOPSIS; ANOVA; data mining (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0218625X23500397

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