International Journal of Advanced Technology and Engineering Exploration, Vol 5(44) ISSN (Print): 2394-5443 ISSN (Online): 2394-7454 http://dx.doi.org/10.19101/IJATEE.2018.544002 214 Multi objective optimization in friction stir welding using Taguchi orthogonal array and grey relational analysis D.Bahar 1* , N. Arvind 2 , V. V Yadav 2 and P.Raju 2 Assistant Professor, Department of Mechanical Engineering, RGUKT-Basar, Nirmal, Telangana, India 1 Students, Department of Mechanical Engineering, RGUKT-Basar, Nirmal, Telangana, India 2 ©2018 ACCENTS 1.Introduction In fusion welds the chemical composition of melt catches more attention, and fillers or consumable electrodes may be used. Also process may require a neutral atmosphere to avoid the oxidation of melt. Sometimes surface preparation before welding is also essential. Several defects and difficulties due to the melting and solidification come to pass, resulting in weakness of mechanical properties such as tensile strength, fatigue properties and formability. Solid state welds are the processes in which the joint is formed below the melting temperature of material. Therefore, the oxidation does not occur and there is no need for shield gas, neutral atmosphere, and consuming material. One of the solid state welding is friction stir welding. Friction stir welding (FSW) is a material joining process. FSW is highly important and recently developed joining technology that produces a solid phase bond. It is particularly appropriate for the welding of high strength alloys. Main characteristic of FSW is to join material without melting. FSW enables to weld almost all types of aluminium alloys, even non-weldable by fusion welding owing to hot cracking and poor solidification micro structure in the fusion zone. *Author for correspondence FSW is observed to be the most significant development in metal joining in a decade and is a “green” technology due to its energy efficiency, environment friendliness, and versatility. In FSW a cylindrical shouldered tool with a profiled probe is rotated and slowly plunged into the joint line between two pieces butted together. Frictional heat is generated between the welding tool and work pieces without reaching the melting point. Tool traverse along the weld line and plasticized material is transferred the front edge of the tool to back edge of the tool probe. A non-consumable friction stir welding tool of hardened steel or carbide consists of a shoulder, normal to the axis of rotation of the tool, and a pin. The shoulder diameter is relatively larger than pin diameter to prevent highly plasticized material from being expelled from the joint. It also controls the depth of the pin and helps to create additional frictional heating above the work piece surfaces and minimizes the formation of gaps in the welding area. Friction stir welding tool of stainless steel used in this project having tool tip length of 4mm, tool tip diameter of 3mm and shoulder diameter of 24.8mm as shown in Figure 1. Research Article Abstract Friction stir welding (FSW) is a recent and effective solid state joining technique for joining similar and dissimilar metals. In this communication FSW is carried out on mating pieces made of aluminum alloys AA5083 and AA6061 having dimensions of 65×60×6 mm. An attempt has been made to optimize the process parameters of FSW for Hardness and Toughness of weld bead using Taguchi Technique and grey relation analysis (GRA). In this study, 3 parameters: rotational speed, tool transverse speed and tool depth are considered with 3 levels. Consequently L9 orthogonal array is constructed and 9 experiments are performed to employ aforementioned optimization technique. Taguchi technique and GRA is analyzed in MINITAB software to find out the optimum value of process parameters and observe their contribution. From this study is found that contribution of rotation speed is higher for hardness and contribution of plunge depth is higher for toughness. Keywords Friction stir welding (FSW), AA5083, AA6061, Hardness, Toughness, Taguchi, Grey relational analysis (GRA), L9 Orthogonal array, Optimization, MINITAB.