Quality-oriented optimization of wave soldering process by using self-organizing maps

Authors:
Mika Liukkonen;Elina Havia;Hannu Leinonen;Yrjö Hiltunen
Affiliations:
University of Kuopio, Department of Environmental Sciences, P.O. Box 1627, FIN-70211 Kuopio, Finland;3K-Factory of Electronics, Laitaatsillantie 3, FIN-57170 Savonlinna, Finland;3K-Factory of Electronics, Laitaatsillantie 3, FIN-57170 Savonlinna, Finland;University of Kuopio, Department of Environmental Sciences, P.O. Box 1627, FIN-70211 Kuopio, Finland
Venue:
Applied Soft Computing
Year:
2011

Citing 6
Cited 7

Neural Networks: A Comprehensive Foundation

Neural Networks: A Comprehensive Foundation
Industrial Applications of Neural Networks

Industrial Applications of Neural Networks
Self-Organizing Maps

Self-Organizing Maps
Electronics Process Technology: Production Modelling, Simulation and Optimisation

Electronics Process Technology: Production Modelling, Simulation and Optimisation
Application of self-organizing maps in analysis of wave soldering process

Expert Systems with Applications: An International Journal
SOM-Based method for process state monitoring and optimization in fluidized bed energy plant

ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I

Modeling of the fluidized bed combustion process and NOx emissions using self-organizing maps: An application to the diagnosis of process states

Environmental Modelling & Software
Analysis of flue gas emission data from fluidized bed combustion using self-organizing maps

Applied Computational Intelligence and Soft Computing
Expert system for analysis of quality in production of electronics

Expert Systems with Applications: An International Journal
Application of visual clustering properties of self organizing map in machine-part cell formation

Applied Soft Computing
Review: Computational intelligence in mass soldering of electronics - A survey

Expert Systems with Applications: An International Journal
Growing Self-Organizing Map with cross insert for mixed-type data clustering

Applied Soft Computing
Cluster analysis by self-organizing maps: An application to the modelling of water quality in a treatment process

Applied Soft Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, the optimal process parameters of a wave soldering process were defined. The optimization was performed in respect to soldering quality by minimizing a cost function describing the total repairing cost of a wave-soldered printed circuit board (PCB). The data analysis stages were as follows. First, the process data were coded into inputs for a self-organizing map (SOM). Next, a function for the repairing cost was constructed and used to find the optimal map neurons. At the last phase, the optimal parameters were approximated on the basis of the reference vectors of the optimal neurons. The results showed clearly potential in the optimization of the wave soldering process, especially in the visualization of the optimal process conditions. Therefore, it would be useful to exploit the method more widely in the electronics industry.