APPLICATION OF NEURAL NETWORKS TO CONDITION BASED MAINTENANCE: A CASE STUDY IN THE TEXTILE INDUSTRY

The development of complex and sophisticated equipment makes necessary to enhance modern maintenance management systems. Conventional Condition-Based Maintenance (CBM) reduces the uncertainty of maintenance according to the needs indicated by the equipment condition. This paper describes a novel predictive maintenance system for textile machine systems based upon a neural network approach. This approach avoids the need for costly measurement of system parameters. The obtained results lead to the conclusion that neural networks represent an effective tool in supporting CBM policies.