It’s no secret that artificial intelligence (AI) is on the rise. Snapchat, a mobile messaging application used to share photos, videos, text, and drawings, recently unveiled an AI chatbot powered by ChatGPT that users can interact with, but one you can’t unfriend or remove. If alarm bells are ringing in your head, you’re not alone. However, with technology continuing to advance at an accelerated pace, AI is becoming increasingly more popular and pretty soon, may be part of our everyday lives.
In the aviation realm, AI is also leaving its mark. With the recent tech fiascos that several major airlines have experienced, it’s no surprise that more and more commercial aircraft are moving to finally invest in much-needed updated and cutting-edge products and solutions to protect their bottom line.
These recent issues have not only served as a reminder that the aviation industry is ripe for system modernization across the board, but that now is the time for airlines to evaluate if they are using antiquated software that puts them, and others, at risk.
A significant challenge arises from organizations where employees are resistant to change, preferring to stick with familiar routines and approaches that have proven successful in the past. However, this mindset hinders individuals from critically evaluating how emerging technological advancements, such as artificial intelligence, can optimize operational efficiency and safety, as well as how cloud computing can facilitate seamless collaboration among peers across multiple locations. And not only can machine learning help to improve maintenance and safety, but it can also assist with flight and crew scheduling.
Below, we’ve outlined the potential impact of AI and machine learning on visibility in aviation software and what we expect to see in the future.
Even the most modernized aircraft will have an issue to report during one of its many voyages, and while it’s customary for operators to dive into the data to determine the problem, the sad reality is many organizations still rely on outdated methods like pen and paper to track mission-critical fleet data. As a result, ATA codes are recorded incorrectly and hinder the detection of repeat defects. In some cases, it can trigger a false positive, as the incorrectly coded defect may be grouped with an entirely unrelated defect.
When it comes to defect analysis software, these systems use natural language processing to analyze aircraft defect information, automatically pinpointing and organizing issue clusters. The complete advanced web and mobile solution provides automatic identification of chronic aircraft defects, chronic resolution management, and defect analysis to improve aircraft safety and reliability.
The solution performs textual analysis of maintenance logbook records in order to identify similar descriptions written by different line mechanics. It can be used to help match two faults that were entered using different codes. Using natural language processing, the system can analyze and categorize large amounts of text data and understand similarities. It also can determine and assign the correct ATA code to a defect record.
Currently in use on 25% of the world’s commercial airline fleet, this software can uncover recurring defects and previously undetected issues, at both the tail and fleet levels. It can also detect emerging failure modes that are yet to reach critical status. Defect analysis software proactively enables engineers to respond with greater speed and accuracy to reduce delays and aircraft downtime.
Leveraging artificial intelligence and machine learning to assist in the diagnosis of issues enables users to solve problems the first time. This eliminates wasted parts and temporary fixes used to pass the problem to the next repair facility. Utilizing a software solution that works with AI, a major airline reduced unexpected flight delays due to repairs needed by 60 percent, saving them over $50 million in annual repair costs. Another aviation customer reported a 20 percent reduction in repeat defects, resulting in $400,000 in savings per year.
For different roles within an organization, AI can be utilized as a virtual assistant. Operators can use machine learning to pinpoint areas in order to prevent delays and cancellations as well as lower unscheduled part removal rates. For pilots, AI can assist with quickly checking the tail history of an aircraft and understanding any defects that were deferred in accordance with the minimum equipment list (MEL). Directors of maintenance can use AI to help better understand issues and their best corrective actions or have support to prioritize various tasks balancing cost and time to repair.
Another added benefit? Efficiency. In aviation, it can be difficult to get access to clear information quickly, especially when you have an overabundant amount of information pertaining to manuals, defects, corrective actions, sensor data, and more. With the help of AI, information can be found and grouped together in a way that humans would take much longer to do.
With aviation software, new collaboration capabilities allow users to share experiences and ask for help from experts — all within the context of the aircraft or type of aircraft being worked on in real time. With the addition of new dashboards and deep integrations, customers can access a command center view to help better understand what repair centers excel at which areas of an aircraft, providing more focused improvements than was ever possible before.
By using AI, the defect management software can learn from user feedback, which allows it to identify future recurring defects with increased accuracy. It also reduces the amount of time that maintenance control analysts need to spend recoding defects, which in turn can help them focus on other fleet maintenance issues. Capturing repeat defects earlier leads to reduced delays, fewer flight cancellations, and most importantly, contributes to overall fleet safety by accurately helping to understand the health of the entire fleet and individual aircraft — all in real time.
Vinay Kumar, Senior Vice President of Engineering at Veryon, shares his thoughts about the advances in technology and what it can mean for customers.
“We definitely have our eyes on the new wave of AI hitting the market, such as ChatGPT, Google Bard and Bing chat. I personally am of the opinion that this is a revolutionary step for a new way for the general public to interact with technology and simplify their lives. That being said, it is still early and as technology advances at lightning speed we must be prudent in its application. Aircraft maintenance is not something that can be taken lightly and easily publicly tested – the stakes are too high when safety and maintenance costs are on the line. We understand the importance of our algorithms providing deep contextual and accurate results – getting our customers more uptime. So in short, there is a potential for this technology to improve troubleshooting aircraft maintenance, but it’s not there yet and we’ll be keeping a close watch on it to see if/when it would be the right time to leverage it as part of our solutions and product offerings.”
Overall, the advances in natural language processing and machine learning have already greatly improved the way aviation operates. While we’ve outlined some of the ways AI can improve maintenance and safety, there are infinite applications of AI in the aviation industry. While AI is only becoming smarter and more efficient at recognizing critical matters, the results of such technology are promising and can have an impact on the industry that we haven't yet been able to imagine. Finding the best solution for your operation is paramount when it comes to ensuring more uptime. Contact us today for a customized demo!