Paper Title
"A PREDICTIVE MAINTENANCE FRAMEWORK FOR REMAINING USEFUL LIFE PREDICTION: A CASE STUDY WITH INGRESS PROTECTION TESTING MACHINES"

Abstract
Abstract - Nozzles are key components in many businesses, including those that use Ingress Protection (IP) testing machines, and nozzle deformity flaws can have an impact on their performance and durability. The forecast of nozzles' remaining usable life (RUL) is critical for preventive maintenance and decreasing unplanned downtime. In this paper, we present a unique method for determining nozzle RUL based on nozzle deformities faults seen in IP testing equipment. This study provides a predictive maintenance approach for calculating the RUL of an IP testing machine, with a specific focus on the fan nozzle. The fan nozzle is an important component of the machine, and its failure can have a substantial impact on the quality of the testing findings. To address this issue, we created a system for monitoring the health of the fan nozzle and estimating its RUL based on the diameter's degradation trend. Artificial data for the nozzle diameter is created. The nozzle's deformation is monitored, and when it hits a certain threshold, the RUL is computed using historical data. The proposed method is a cost-effective and practical technique for measuring the RUL of fan nozzles, and it can be applied to other mechanical systems having deformities and flaws. Keywords - Remaining Useful Life; Nozzle; Ingress Protection Machine; Predictive Maintenance;