When you are not feeling well your body probably shows you symptoms such as nausea, headache or body pain alerting you to see the doctor at the earliest. Similarly, your fleet exhibits its illness by showing dashboard light, alerting the driver about its illness but most of the time it is at the eleventh hour and you can’t do much about it without spending a hefty amount on repairs and messing around.
Have you think how great it would be if your fleet is always under the supervision of a doctor, so it can be diagnosed when the early indications appear, and the perspective course can be decided based on its significance. This is what predictive maintenance does to your fleet to avoid breakdown time.
Predictive maintenance is a strategy to avoid random mechanical failure. This strategy is based on the observation of the degradation process of an asset and distinguishes the eccentric symptoms from regular behavior of an asset. Predictive maintenance is another application of the Internet of things using the data generated by the sensor to eliminate the unanticipated breakdown
Predictive maintenance module is basically divided into two major systems: a diagnostics system and a prognostics system. Both systems require real-time data and historical data for data mining. Predicative maintenance analysis is a powerful tool for identifying the mechanical failure of an asset by supervising its condition and constantly aiding the analytics process of diagnosis and prognosis. The unanticipated breakdown can be diagnosed by using time-series data by well-developed analytic processes.
Predicative maintenance is now possible will Eagle-I fleet management and tracking solution. Eagle-I now offers you OBD II data integration. With this data integration, you can not only diagnosis the engine problems but can also have access to other information such as engine revolutions, vehicle speed, fault codes, fuel usage. This integration allows the fleet managers to not only monitor their asset but also their performance.
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Please call Mr. Jamal +966 56 638 7859 or write us at email@example.com