TY - GEN
T1 - TOPSIS Based Optimization of Laser Surface Texturing Process Parameters
AU - Pradhan, Satish
AU - Shivakoti, Ishwer
AU - Roy, Manish Kumar
AU - Ghadai, Ranjan Kumar
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - Laser surface texturing (LST) is proving to be a promising technique for surface texturing of different work materials. The selection of suitable parameters to conduct LST has become one of the vital criteria for texture quality. In this work, the texture was made on Zirconia ceramic employing a fibre laser set at different parametric combinations to modify the surface of the material. Average power, scanning speed, pulse frequency and transverse feed has been considered as control variable whereas, surface roughness (Ra and Rz) has been considered as the process response. Furthermore, Technique for order performance by similarity to ideal solution (TOPSIS) based Multi Criteria Decision Making Methods (MCDM) was adopted to determine the suitable parametric combination for improving the process efficiency. The mean weight method has been utilized for providing weightage to TOPSIS. The results shows that the TOPSIS method is relatively simpler to use to determine the suitable combination.
AB - Laser surface texturing (LST) is proving to be a promising technique for surface texturing of different work materials. The selection of suitable parameters to conduct LST has become one of the vital criteria for texture quality. In this work, the texture was made on Zirconia ceramic employing a fibre laser set at different parametric combinations to modify the surface of the material. Average power, scanning speed, pulse frequency and transverse feed has been considered as control variable whereas, surface roughness (Ra and Rz) has been considered as the process response. Furthermore, Technique for order performance by similarity to ideal solution (TOPSIS) based Multi Criteria Decision Making Methods (MCDM) was adopted to determine the suitable parametric combination for improving the process efficiency. The mean weight method has been utilized for providing weightage to TOPSIS. The results shows that the TOPSIS method is relatively simpler to use to determine the suitable combination.
UR - https://www.scopus.com/pages/publications/85180785920
UR - https://www.scopus.com/pages/publications/85180785920#tab=citedBy
U2 - 10.1007/978-3-031-50330-6_4
DO - 10.1007/978-3-031-50330-6_4
M3 - Conference contribution
AN - SCOPUS:85180785920
SN - 9783031503290
T3 - Lecture Notes in Networks and Systems
SP - 37
EP - 42
BT - Intelligent Computing and Optimization - Proceedings of the 6th International Conference on Intelligent Computing and Optimization 2023 ICO2023
A2 - Vasant, Pandian
A2 - Shamsul Arefin, Mohammad
A2 - Panchenko, Vladimir
A2 - Thomas, J. Joshua
A2 - Munapo, Elias
A2 - Weber, Gerhard-Wilhelm
A2 - Rodriguez-Aguilar, Roman
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th International Conference on Intelligent Computing and Optimization, ICO 2023
Y2 - 27 April 2023 through 28 April 2023
ER -