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Cenacle Research offers Condition-based Predictive Maintenance solutions that reduce maintenance costs and improve asset life-time by optimizing the maintenance schedules. This requires calculating the asset's remaining-useful-life (RUL) based on the current and historic usage patterns and building a mathematical model that is capable of extrapolating failures from the past to the future. The Predictive Maintenance API offers: - failure rate estimation based on real-time operating conditions - failure rate estimation based on historic failure patterns The *Real-time Failure Rate API* allows you to calculate the failure rate of various components, such as Accumulators, Actuators, Belts, Clutches, Brakes etc. in real-time based on the prevailing operating conditions of the assets. This helps you in estimating the RUL for various assets such as: - vehicles in motion, based on the sensors attached to the vehicles to various key parts - stationary machinery in manufacturing plants - individual components inside machines etc. When you do not have the previous failure records or maintenance records available, or if your machinery is brand new with provisions to capture the required data using sensors, this API is the best option for high accuracy predictions. The *Historic Failure Rate API* allows you estimate the asset failure risks for a population of assets based on the maintenance records and previous failure patterns. This helps when you do not have provision to attach sensors and have adequate history of maintenance records for a population of machinery. [Get in touch](http://Cenacle.website/#contact) with us if you are interested in utilizing our Predictive Maintenance API in your applications.

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