The Future of AI in the Aerospace Industry

As safety and dependability lie at the forefront of the aerospace industry’s operations, it is constantly looking for ways to improve its various sectors. From military and commercial aviation to space exploration, the aerospace market is boundless in its reach. Recently, artificial intelligence (AI) has garnered popularity in these fields, as it has proven to help companies streamline manufacturing processes and address safety concerns.

The aerospace industry is a mission-critical industry and its success depends on the reliability and accuracy of the components it produces. As such, it is tasked with reducing human errors and labor costs, monitoring the health of aircraft devices, and more. In the past, the aerospace industry would fall behind in terms of technology due to its long regulatory cycles. However, AI has proven a suitable solution.

AI and its computational capabilities for data interpretation has the ability to streamline and simplify analytics, system management, customer service and various other processes. It has already demonstrated promise in other sectors, including banking, advertisement, retail, and health. Furthermore, AI systems can analyze inputs from several assets and process large amounts of data faster than would be achieved manually, leading to its adaptation by major businesses like Raytheon, General Dynamics, Airbus, and Boeing.

Smart Maintenance

Aircraft maintenance is an essential part of ensuring aircraft are working optimally. As servicing is carried out on a regular basis, the process can be time-consuming. Furthermore, unexpected malfunctions and errors can result in a significant loss of resources and time. For these reasons, predictive maintenance facilitated by AI is being implemented by aviation businesses across the board. For example, cloud-based applications are being used by Airbus for data processing, retrieval, and analysis. Algorithms embedded in such systems can detect and track possible faults in real-time and forecast repair times.

Better Fuel Efficiency

Since aerospace companies place an emphasis on fuel quality, even a slight decrease in fuel consumption can have a tremendous impact on the company’s emissions. With the help of AI systems, fuel consumption can be cut by 5 to 7 percent. For instance, a French firm called Safety Line has devised a machine learning tool that can optimize climb profiles for pilots prior to each flight.

Better Customer Experience

Customer satisfaction and quality care are particularly important for commercial aviation. AI serves as one of the best ways of improving customer engagement and delivering exceptional customer support. Chatbots are a good example of AI-based automated platforms that provide rapid response times for consumer inquiries. In fact, according to a SITA poll, 68% of airlines are said to deploy AI-driven chatbots in the near future.

Training

AI can also be used to improve pilot training facilities by creating suitable flight simulation environments. This is achieved by utilizing AI-enabled simulators, alongside virtual reality systems, to capture and analyze practice data. This allows practicing pilots to acquire personalized training data.

Conclusion

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