No Cover Image

Journal article 1329 views 175 downloads

Optimisation process for robotic assembly of electronic components

K. T. Andrzejewski, M. P. Cooper, C. A. Griffiths, C. Giannetti, Cinzia Giannetti Orcid Logo, Christian Griffiths

The International Journal of Advanced Manufacturing Technology

Swansea University Authors: Cinzia Giannetti Orcid Logo, Christian Griffiths

  • andrzejewski2018.pdf

    PDF | Version of Record

    This article is distributed under the terms of the Creative Commons Attribution 4.0 International License

    Download (3.69MB)

Abstract

Adoption of robots in the manufacturing environment is a way to improve productivity, and the assembly of electronic components has benefited from the adoption of highly dedicated automation equipment. Traditionally, articulated 6-axis robots have not been used in electronic surface mount assembly....

Full description

Published in: The International Journal of Advanced Manufacturing Technology
ISSN: 0268-3768 1433-3015
Published: 2018
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa43763
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract: Adoption of robots in the manufacturing environment is a way to improve productivity, and the assembly of electronic components has benefited from the adoption of highly dedicated automation equipment. Traditionally, articulated 6-axis robots have not been used in electronic surface mount assembly. However, the need for more flexible production systems that can be used for low to medium production builds means that these robots can be used due to their high degrees of flexibility, excellent repeatability and increasingly lower investment costs. This research investigated the application of an articulated robot with six degrees of freedom to assemble a multi-component printed circuit board (PCB) for an electronic product. A heuristic methodology using a genetic algorithm was used to plan the optimal sequence and identify the best location of the parts to the assembly positions on the PCB. Using the optimised paths, a condition monitoring method for cycle time evaluation was conducted using a KUKA KR16 assembly cell together with four different robot path motions. The genetic algorithm approach together with different assembly position iterations identified an optimisation method for improved production throughput using a non-traditional but highly flexible assembly method. The application of optimised articulated robots for PCB assembly can bridge the gap between manual assembly and the high-throughput automation equipment.
Keywords: Sequencing optimisation, Electronics assembly, KUKA robotics, Flexible manufacture, Genetic algorithm
College: Faculty of Science and Engineering