Thursday, November 7, 2019

Future of Aerospace and How AI is driving aerospace engineering?

When we think about the future of aerospace, our mind might go someplace big. Taking a commercial flight to mars at the speed of light, commuting to work on a passenger drone, or living in an airship the size of a small city.

All good ideas, albeit a bit far fetched. So, now I told you the real future of aerospace which is happening right now.
For the past couple of years, the world has been abuzz with news that we may be getting closer to commercial space travel.
Private space companies seem to be breaking barriers every week, getting us closer to the dream of spending our holiday orbiting the earth.
This is the one vision of the future of flight but there are other huge steps in the world of aerospace that are being taken to help improve holidays down here on earth.
In the future in the next 5 or 6 years, we are going to see a lot more tiny features on airplanes that the normal person in the street would not appreciate, but they make huge difference to both the emission of aircraft in terms of noise and the fuel burn. And it is going to be driving towards a more sustainable future in aviation. Because of the emission that we are going to put into the atmosphere the drive to reduce that is going to be absolutely critical.

Aircraft in the commercial world is all about getting people efficiently from point to point. So the companies are improving technologies on the flight deck to enhance the capabilities of getting an airplane in and out of the airfields sometimes when the weather is poor.
aircraft

We see the impact of artificial intelligence across different industries, how advances in AI could help aerospace companies better optimize their manufacturing processes. AI will allow the business to develop sustainable and lightweight aircraft components.

The challenges faced by the aerospace sector are labor cost, human error, health and safety concerns. Manufacturing and development procedures can be increasingly time-consuming due to industrial inspections to evaluate whether a component matches the required specifications. The aerospace industry is constantly looking for an effective way to speed up development processes in order to meet the growing demand as well as deliver high-quality components.

According to the Accenture report, 80% of leading executives within the aerospace and defense industries expect that every part of the workforce will be directly affected by AI-based decisions by 2021.

AI applications in aerospace

The use of AI in the aerospace industry will help businesses in the following manner:

Product design

In the aerospace industry, lightweight and sturdy components are always favored for an aircraft. To create such components, manufacturers can use a generative structure along with AI algorithms. Generative design is an iterative process, where engineers or architects use design goals as input alongside constraints and parameters like materials, available resources, and assigned spending budget to develop an optimal product design. 
Combining with AI, generative design software can enable product designers to evaluate numerous design options in a limited span of time. Using this technology, designers can create new products that are lightweight and sustainable. Artificial Intelligence enabled generative design coupled with 3D printing can be used to deliver various aircraft parts, for example, turbines, and wings.

Fuel efficiency

Globally, commercial airlines consume billions of gallons of fuel every year. As per insight, it is estimated that worldwide fuel consumption will reach an all-time high at 97 billion gallons in 2019. Hence, conserving fuel is a major concern for the whole aerospace industry. For this purpose, various organizations are already now fabricating lightweight parts with the aid of 3D printing. Artificial Intelligence can also help aerospace companies in improving their fuel efficiency.
A plane utilizes fuel at the highest rate in the climb phase. AI models can analyze how much fuel is consumed in the climb stage of different aircraft and by numerous pilots to create climb phase profiles for each pilot. These profiles can optimize fuel consumption during the climb phase. By utilizing AI-generated climb phase profiles, pilots can effectively preserve fuel during flights.

Operational efficiency and maintenance

Airplanes have various sensors that assist pilots measure speed, air pressure, and altitude. These sensors can be utilized to collect critical data like temperature, moisture, and pressure in different parts of an aircraft. Artificial Intelligence models can be trained to analyze the collected data to recognize abnormal behavior in aircraft parts. For example, sensors placed in turbines can collect data such as rotation speed, air pressure, and temperature of the part. The obtained data can be used to train AI models about traditional turbine behavior. By examining this data, AI models can detect when turbines turn away from their normal behavior and notify concerned staff about possible errors. Hence, airlines can recognize defective aircraft parts beforehand and fix them. In this manner, the utilization of Artificial Intelligence in the aerospace industry can help business leaders develop their operational efficiency by bypassing component failures that can lead to downtimes.

Pilot training

AI simulators coupled with virtual reality framework can be used to give pilots progressively realistic simulation of flying experience. AI-enabled simulators can be used to accumulate and analyze training data to know every pilot’s strengths and weaknesses to generate a detailed report that can be presented to their trainer. The received data can also be utilized to develop personalized training programs for each pilot. Personalized training programs can allow pilots to discuss their individual challenges more efficiently compared to traditional training programs.

Air traffic management

Air traffic control is one of the focus tasks of airports and airlines. However, as billions of travelers opt for air travel, air traffic control can be immensely complex. Hence, leveraging Artificial Intelligence for air traffic control can be an efficient solution. AI-powered intelligent assistants can help pilots in making informed decisions using weather data from sensors and flight data. Using such data, AI-based assistants can recommend alternative routes to pilots in order to make air travel more reliable and quicker.
AI can also be used along with smart cameras to recognize aircraft when they exit the runway and notify air traffic controllers. Using this data, air traffic controllers can clear the arrival runway for the next airplane. This technology can prove to be very helpful in low visibility situations such as fog. In this manner, the utilization of Artificial Intelligence in aerospace help in managing air traffic and reducing bottlenecks on airports.

Passenger identification

Security is one of the most important preferences of commercial airlines and Artificial Intelligence can offer powerful solutions to secure the security of passengers. AI-enabled smart cameras use facial recognition to recognize suspicious people at an airport. For this, AI systems trained with images of people with criminal records. Similarly, AI-powered smart cameras can also be used to detect malicious activity in an airport.

Customer service

Consumer satisfaction and loyalty are exceptionally important within commercially flying. The implementation of AI in aerospace industries enables commercial airlines to give enhanced customer service. For this purpose, commercial airlines use Artificial Intelligence-powered chatbots that are competent in resolving customer queries. Using chatbots, commercial airlines provide 24/7, automatic customer support. These chatbots guide customers while booking and canceling the tickets. Also, AI-powered chatbots continually learn by having interactions with different customers to develop their ability to understand a customer’s context in conversations and replicating human responses.
To sum up, these AI applications cannot function autonomously and require human intervention. However, with further research and development, AI may be capable of carrying out several tasks autonomously and may become a crucial part of autopilot systems.