Multi objective optimization of process parameters of AA2014 Friction Stir Weldments using Genetic Algor

• Main Authors: L. Suvarna RAJU, Borigorla VENU, G. MALLAIAH
• Format: Article
• Language: English
• Published: National Institute for Aerospace Research “Elie Carafoli” - INCAS 2020-09-01
• Series: INCAS Bulletin
• Subjects: friction stir welding; mechanical properties; microstructure; regression anova; genetic algorithm
• Online Access: https://bulletin.incas.ro/files/raju__venu__mallaiah__vol_12_iss_3.pdf

The influence of tool pin profile and process parameters on microstructure and mechanical properties of AA2014 weldments was studied. Tool pin profiles such as a Straight Cylindrical Threaded (SCT) and Taper Cylindrical Threaded (TCT) profiles are used for experimentation. The process parameters such as constant tool rotational speed of 900 rpm, welding speed and tool tilt angles at 30, 40, 50, and 60mm/min and 1o, 2o, respectively, are used to fabricate the weldments. A set of experiments was conducted with two different tool pin profiles and mechanical properties were evaluated. The better mechanical properties such as tensile strength of 367N/mm2, impact strength of 10J and hardness of 139HV were obtained by using TCT pin when compared to SCT pin. The observed mechanical properties have been correlated with microstructure. The mechanical properties were analyzed by ANOVA and regression analysis. Objective functions and constraints are developed for the three responses in terms of factors. The factors are optimized using Genetic Algorithm (GA). From the GA results, it is observed that the welding speed of 58mm/min and tool tilt angle of 1.95o are found to be the better combination for carrying out the experiments using TCT pin profile.