Robotic Assembly Sequence Generation Using Improved Fruit Fly Algorithm By Applying Gross And Fine Motion As Fitness Equation

Abstract

Robotic assembly plays a major role in manufacturing industries to reduce the cost of overall product. As the assembly is one of the major manufacturing processes, which involves much information like contact information between the parts, tools needed during assembly, part orientation information during assembly and many more. Most of the researchers considered grippers changes, assembly time, directional changes, part orientation and energy of the part as fitness function. In this research work authors made attempt to consider gross and fine motion as fitness equation to generate optimal assembly sequences with Improved Fruit Fly Algorithm (IFFA). The proposed algorithm is implemented on many industrial products to obtain the optimal assembly sequences.