Predicting engine failures in advance will enhance operations and reduce flight delays. Observing engine’s health and condition through sensors and telemetry data is assumed to facilitate this type of maintenance by predicting Time To Failure (TTF) of in-service equipment. Predictive maintenance lets you estimate when machine failure will occur. This way, you can plan maintenance, better manage inventory, eliminate unplanned downtime, and maximize equipment lifetime.
IBM Cloud Pak for Data (CP4D) is an end-to-end data and AI platform enabling organizations to collect, organize, and analyze all of their enterprise data. It is a well-integrated collection of microservices built on cloud native architecture that can be deployed on premise or any public cloud.
Wireless data acquisition from IoT devices and machine equipment, big data pre-processing, cleaning, future extraction, integration, and transformation are all done in a data warehouse. Data mining with machine learning: diagnosis and prognosis. Decision support AI/ML Intel with KPI dashboard insights, fault detection, identification and prediction, degradation assessment, and maintenance implementation.