Robotic Assembly Sequence Planning and Optimization by Cuckoo Search Algorithm

Abstract

The assembly sequence optimization problem is challenging as number of sequences rises staggeringly with part count making it combinatorically explosive, tedious and time consuming to solve. A Computer-Aided Process Planning (CAPP) system for robotic assembly by a discrete cuckoo search algorithm has been proposed by us to generate feasible and optimal sequences considering minimization of orientation changes, tool/gripper changes, assembly stability and base component location. A case study and comparison results with an established soft computing approach are presented to show its effectiveness. It is further integrated with an upstream assembly product database to extract information on assembly directions, contact details, assembly precedence constraints and tool/grippers. Further the assembly sequence output from CAPP system is integrated with a robot task planner developed using Knowledge Based System capable of automatically generating executable robot level program for performing the assembly.