@article{618,
  author = {Sasidhar Muttineni, Pandu R. Vundavilli},
  title = {Statistical Regression-based Modeling of Friction Stir Welding of AL7075},
  journal = {Journal of Intelligent Computing},
  year = {2011},
  volume = {2},
  number = {3},
  doi = {},
  url = {http://www.dline.info/jic/fulltext/v2n3/2.pdf},
  abstract = {Friction stir welding (FSW) is a solid state welding process, which is used for the welding of aluminum alloys. It is important to note that the mechanical properties of the FSW process depends on various process parameters, such as spindle speed, feed rate and shoulder depth. In the present study, two different tool materials, such as high speed steel (HSS) and H13 are considered for the welding of Al 7075. This paper provides an insight into the measurement of force required for welding and external surface temperature measurement for three input parameters, namely spindle speed, feed rate and shoulder depth and their corresponding three levels. During experimentation the data related to force along x and z directions, and heat transferred to the tool are recorded using dynamometer and IR camera. Regression analysis is performed to predict the forces and heat transfer to the tool for different parametric combinations.},
}