Aerospace engineering has a data issue beyond mechanical and automation details. Life is getting more digital as aircrafts. Data is in all around us. It is easier to evaluate data ever than before. Do you know how aircraft data is being processed in aerospace engineering?
Detailed weather information, lifetime and maintenance of critical parts, flight plan details and fuel consumption analysis… In an aircraft all of data that collected by sensors is being monitored minute to minute even second to second. It’s important to analysis all data that collected in an aircraft.
An aircraft has more than 140.000 sensors. And more than 5 thousand engine parts which followed continuously. During flight data about plan, route, weather and mechanical parts are collected. Sensors on an aircraft covers more than 300.000 parameters. Each parameter is not stored but nearly 20 terabytes of data is collected and analyzed during an hour of flight. How is it? Really big!
In aerospace engineering a lot of data which means big data analyzed in different ways. Basic big data philosophy of big data in aviation industry is using scalable algorithms. With this algorithms continuously collected data is processed for visualization and customization.
Analyzing complex data is not only manner for aerospace engineering big data technologies. Accessibility is another meaning of big data in aerospace engineering. Sometimes accessing needed data in the right place and right time is more critical than analyzing. Beyond basic algorithms big data is used for maintenance. Safety and security requirements of aerospace engineering fulfilled by using big data. In every scenario aircraft engine data is collected continuously. At the same time of analyzing continuously accessible data is available.
Predictive analysis of maintenance is major point for aircraft. Ensuring actionable information helps executing the right maintenance steps. Preventive or predictive maintenance approach make possible lower unplanned downtime.
Cost of flight is important. Reducing costs by optimum planning is another spool of big data in aerospace engineering. Collection of big data from takeoff and landing points is useful for minimization of flight cost.
There is really big data in aircrafts. And it is possible to increase it in a sensible way. But evaluation of data is more critical than having it. An algorithm or filtering can make big difference for safety, security and cost. All aircraft manufacturers are working on different big data technologies especially about decreasing fuel consumption and optimizing flight paths. With new technologies it less delays and maximum efficiency will be possible.
In future real time analyzing of data will be possible in aerospace engineering. Big data technologies that is connected with ground services and synchronizing it in both sides can ensure safer and more expedited travel experience. It is possible to record every aspect of operation by using sensors. But evaluation of data is not as easy as recording. Aircraft engineering need time and experience for it.
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