Title: Parametric optimisation of friction welded 17-4 PH SS alloy using Taguchi techniques
Authors: S. Mahendiran; R. Ramanujam; V. Mohanavel; M.M. Ravikumar; G. Madhan; P. Vinothkumar
Addresses: School of Mechanical Engineering, Vellore Institute of Technology (VIT), Vellore 632 014, Tamil Nadu, India ' School of Mechanical Engineering, Vellore Institute of Technology (VIT), Vellore 632 014, Tamil Nadu, India ' Department of Mechanical Engineering, Kingston Engineering College, Vellore 632 059, Tamil Nadu, India ' Department of Mechanical Engineering, Kingston Engineering College, Vellore 632 059, Tamil Nadu, India ' Department of Mechanical Engineering, Kingston Engineering College, Vellore 632 059, Tamil Nadu, India ' Department of Mechanical Engineering, Kingston Engineering College, Vellore 632 059, Tamil Nadu, India
Abstract: Friction welding (FW) is a solid state technique used mostly for joining similar or dissimilar materials owing to batch production with less time consumption. In friction welding, the joints are formed in the solid state by utilising the heat generated by friction. The objectives of this project is to obtain friction weld element of 17-4 PH Stainless steel alloy (Grade 630) and optimising the friction welding parameters in order to establish the weld strength and its quality. In this research work, the experiment is undergone to examine the tensile strength of friction welding 17-4 PH Stainless steel alloy. The experiment is conducted by varying the input parameters like rotational speed, friction and forging force, friction and forging time using Taguchi's L9 orthogonal array. For each experiment tensile strength was examined and the optimum welding condition for maximising tensile strength was determined.
Keywords: precipitation hardening; rotary friction welding; tensile strength; Taguchi techniques; ANOVA; analysis of variance.
Progress in Industrial Ecology, An International Journal, 2018 Vol.12 No.1/2, pp.3 - 13
Received: 07 Oct 2017
Accepted: 05 Jan 2018
Published online: 25 Oct 2018 *