Application of the Bees Algorithm to the Training of Learning Vector Quantisation Networks for Control Chart Pattern Recognition

Abstract

Control charts are employed in manufacturing industry for statistical process control (SPC). It is possible to detect incipient problems and prevent a process from going out of control by identifying the type of patterns displayed by the control charts. Various techniques have been applied to this control chart pattern recognition task. This paper presents the use of learning vector quantisation (LVQ) networks for recognising patterns in control charts. The LVQ networks were trained, not by applying standard training algorithms, but by employing a new optimisation algorithm developed by the authors. The algorithm, called the bees algorithm, is inspired by the food foraging behaviour of honey bees. The paper first describes the bees algorithm and explains how the algorithm is employed to train LVQ networks. It then discusses the recognition of control chart patterns by LVQ networks optimised using the bees algorithm