Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/2332
Title: Optimal Robotic Assembly Sequence generation using Particle Swarm Optimization
Authors: Bahubalendruni, M V A Raju
Biswal, B B
B B, V L Deepak
Keywords: Robotic assembly sequence
Particle swarm optimization
Optimal assembly sequence
Issue Date: May-2015
Citation: 2015 International Conference on Robotics and Artificial Intelligence (ICRAI 2015),Las Vegas, USA,May 9-10, 2015.
Abstract: The optimal feasible robotic assembly sequence leads to efficient manufacturing process by minimizing the assembly cost. Assembly cost is based on the energy required to assemble the components through collision free path and robot directional changes during the assembly operations. So, the determination of a feasible assembly sequence with minimum assembly cost is vital concern for manufacturing industries. Through obtaining optimal assembly sequences taking user inputs (assembly connection matrix, precedence relations, etc.,) is less complicate, the correctness of methodology depends on the skill of the engineer who supply these inputs. The present research aims to explore PSO based methodology to determine cost effective optimal robotic assembly sequence through CAD product. The integration of PSO with CAD environment ensures the correctness and completeness of the methodology. The methods to interface with the CAD data to extract liaison data, to test for liaison predicate and feasibility predicate is presented and analyzed briefly with an example. In this methodology, each component of the assembled product is considered as the particle (bird) and mutation operation is performed to generate a new assembly sequence for each iteration. To generate optimal assembly sequence, a fitness function is generated, which is based on the energy function and robot directional changes associated with assembly sequence. The sequence which is having the best fitness value is treated as the optimal robotic assembly sequence.
Description: Copyright belong to proceeding publisher
URI: http://hdl.handle.net/2080/2332
Appears in Collections:Conference Papers

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