Multi-attribute optimisation of submerged arc welding process parameters using Taguchi GRA-PCA hybrid approach

ABSTRACT

Submerged arc welding (SAW) is an astounding, high-deposition rate-welding process typically utilised to bond together plates of higher thickness in load-bearing portions. This system of arc welding gives a cleaner high volume weldment that has respectably a higher material deposition rate appeared differently in relation to the traditional welding methodologies. In SAW, weld quality is incredibly influenced by various input parameters, for example, welding current, arc voltage and electrode stick out since they are firmly identified with the geometry of weld bead, a relationship which is believed to be convoluted due to the non-direct attributes. The multi-performance attributes including bead width, dilution and weld bead hardness are the quality functions considered for the optimisation. Be that as it may, experimentation strategies to decide ideal conditions acquire extensive time and cost. Keeping in mind the end goal to beat these issues, hybrid approaches, specifically grey relational analysis and principal component analysis , have been recommended. Finally, suggested settings of process parameter are observed to welding current (A2 = 310 amp), arc voltage (B5 = 28 volt), electrode stick out (C1 = 19 mm).

KEYWORDS:

• GRA; PCA; SAW; weld quality

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Abhijit Saha

Abhijit Saha has obtained his Bachelor’s degree in Production Engineering from National Institute of Technology Agartala, India and Master’s degree in Manufacturing Technology from National Institute of Technical Teachers' Training & Research (NITTTR), Kolkata, India. Dr. Saha completed his PhD in Mechanical Engineering from Indian Institute of Engineering Science and Technology (IIEST), Shibpur, India. Currently he is working as an Assistant Professor in the department of Production Engineering at Haldia Institute of Technology, West Bengal, India. He is doing research in the field of welding, WEDM, soft computing and multi-objective optimization, etc.

Himadri Majumder

Himadri Majumder has obtained his Bachelor’s and Master’s degree in Production Engineering from National Institute of Technology Agartala, India and completed his PhD in Mechanical Engineering from National Institute of Technology Rourkela, India. He has one year Industrial experience. Currently he is working as an Assistant Professor in the department of Mechanical Engineering at G.H. Raisoni College of Engineering and Management, Pune, India. He is doing research in the field of traditional and non-traditional machining processes, soft computing and optimization, etc.