Back-Propagation Artificial Neural Network Approach for Selection of a Rapid Prototyping Machine
Boppana V. Chowdary · 2006
A decade ago, rapid prototyping (RP) machine selection process was much easier since the breadth of choice was smaller, and the strengths of each technology were distinct and readily apparent. With advances in established technologies, materials and the introduction of new methods, selecting the right RP machine has become much more difficult. These advances have blurred the lines of distinction. The artificial neural network (ANN) research has opened a new dimension for scientific research and industrial/business applications. Although ANNs have been introduced for several years, their use in manufacturing area is quite recent and the applications to manufacturing problems are still very few. This paper attempts to demonstrate one of the potential applications of back-propagation ANN for selection of a Stereolithography apparatus (SLA) machine. The results of the study show the developed ANN model is capable of solving the RP machine selection problem with notable consistency and reasonable accuracy.