TY - CHAP
T1 - Multi-objective Optimization of FSW Process Variables of Aluminium Matrix Composites Using Taguchi-Based Grey Relational Analysis
AU - Prabhu, Subramanya R.B.
AU - Shettigar, Arun Kumar
AU - Herbert, Mervin A.
AU - Rao, Shrikantha S.
N1 - Publisher Copyright:
© 2019, Springer Nature Singapore Pte Ltd.
PY - 2019
Y1 - 2019
N2 - Successful joining of aluminium alloys using friction stir welding (FSW) opens a new window research in extending this technique to join aluminium matrix composites (AMCs). Current research is focused on optimization of process variables for multiple responses simultaneously. Experiments were performed using tool pin profile, rotational speed (RS) and welding speed (WS) as ideal process variables for multi-objective optimization in FSW of AMCs. Tensile strength, macro-hardness and elongation are considered as multi-response behaviour. Grey relational grade for the chosen multiple responses are obtained using grey analysis. Analysis of variance was utilized to understand the influence of process variables on the grey relational grade. Analysis reveals that RS and WS were the most influencing process variables on the output responses. Confirmation experiments were performed at optimized process variables to validate the present study. Predicted values were in good agreement with the experimental results.
AB - Successful joining of aluminium alloys using friction stir welding (FSW) opens a new window research in extending this technique to join aluminium matrix composites (AMCs). Current research is focused on optimization of process variables for multiple responses simultaneously. Experiments were performed using tool pin profile, rotational speed (RS) and welding speed (WS) as ideal process variables for multi-objective optimization in FSW of AMCs. Tensile strength, macro-hardness and elongation are considered as multi-response behaviour. Grey relational grade for the chosen multiple responses are obtained using grey analysis. Analysis of variance was utilized to understand the influence of process variables on the grey relational grade. Analysis reveals that RS and WS were the most influencing process variables on the output responses. Confirmation experiments were performed at optimized process variables to validate the present study. Predicted values were in good agreement with the experimental results.
UR - http://www.scopus.com/inward/record.url?scp=85104808750&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85104808750&partnerID=8YFLogxK
U2 - 10.1007/978-981-32-9072-3_12
DO - 10.1007/978-981-32-9072-3_12
M3 - Chapter
AN - SCOPUS:85104808750
T3 - Lecture Notes on Multidisciplinary Industrial Engineering
SP - 133
EP - 144
BT - Lecture Notes on Multidisciplinary Industrial Engineering
PB - Springer Nature
ER -