Parametric Optimization of Surface Roughness of Deburring Process on Aluminum Alloy Using SCARA Manipulator

This paper presents an attempt to analyze deburring operation using a SCARA (Selective Compliance Articulated Robot Arm) manipulator. There are various deburring techniques available in the literature but this work aims at deburring of small sized components. In this paper parametric optimization of surface roughness using SCARA Manipulator using various deburring parameters has been performed with Genetic and TLBO optimization algorithms. A rectangular work piece of Aluminum is considered and the end effector used in this case is a grinding wheel of aluminum oxide. The machining parameters considered are Spindle speed, Feed rate and Depth of cut. An orthogonal array L9 was modeled using Taguchi Method to conduct the experiments. The surface roughness of the workpiece is measured using an instrument called Talysurf. Later the end effector of SCARA is used for deburring on the same workpiece to check the efficiency of SCARA for removal of burrs. Regression analysis is employed to analyze the effect of the deburring parameters on material. Optimization of parameters was done using Genetic and TLBO algorithms in MATLAB environment. An optimum deburring parameters for minimizing the surface roughness was obtained at the Spindle speed 5250 (rpm), feed rate 0.859 (mm/sec) and depth of cut 0.3 (mm) and Spindle speed was found to be the most significant factor followed by feed rate for Surface roughness. (C) 2018 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Advances in Materials and Manufacturing Applications [IConAMMA 2017].