Afshin Ghanbarzadeh - Mechanical Engineering Department, Faculty of Engineering, Shahid Chamran University

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 radial basis function networks for recognizing patterns in control charts in order to determine if the process being monitored is operating normally or if it shows gradual changes (trends), sudden changes (shifts) or periodic changes (cycles). The radial basis function networks were trained, not by applying standard training algorithms, but by employing a new optimization algorithm developed by the authors. The algorithm, called the Bees Algorithm, is inspired by the food foraging behavior of honey bees. The paper briefly explains the Bees Algorithm and gives the results obtained.

Bees Algorithm, Neural Network, Pattern Recognition, Control Charts, Swarm Intelligence