The aerospace industry is one of the strictest for precision, quality, traceability, and maintenance. Because of this, aerospace manufacturing is a process with strict regulations and smart machinery. Historically, the aerospace industry used robots for repetitive tasks like fabrication, painting, sanding, and polishing. Today, smarter automation is now entering the industry.
Although the aerospace industry struggled in 2020 because of the pandemic, 2023 is a new frontier for automation in aerospace manufacturing for improved quality assurance. Manufacturers are finding that automation in aerospace manufacturing can prevent machine breakdowns, teach employees new tasks, manage data, and learn information faster than humans can. In turn, automation is contributing less scrap and more efficient manufacturing.
This blog will discuss the specifics of how automation is changing the aerospace industry for the better.
AI Replacing Employees
Although pandemic shutdowns and layoffs have subsided, the effects are still prevalent. Aerospace demand is once again thriving after the drastic plunge, yet many skilled manufacturers have retired or exited the industry.
As a result, there is a gap of skilled workers and an influx of unskilled workers. Because of this predicament, one new aspect of automation in aerospace manufacturing is replacing laborers with imported software and automated mobile robots (AMR).
Training new employees is undeniably essential, but it runs up production time and budget. Furthermore, the natural learning curve for human workers means there will be quality errors within the implementation.
However, the aerospace industry learned that robots can be the solution. Unlike humans, already manufactured robots equipped with learning patterns and processes can seamlessly share their knowledge through software exchange.
Manufacturers can upload learned AI software into a new robot and grant it immediate access to the information. Even more, robots can use this software as a foundation for learning even more patterns and processes. This transformative capability decreases quality errors from unskilled employees or untrained robots.
Automated Mobile Robots
Regardless of who is working, quality assurance cannot be compromised in the aerospace industry, so automated mobile robots (AMR) have stepped in.
AMR is a beacon of hope for continuing quality production when there’s a lack of employees. These robots travel to the production site, complete the tasks, and leave the site when finished. AMRs are a step toward automation beyond simple repetition on the production line. They symbolize a new era of automation that replaces the need for employees to manage machines and be at the production site. AMRs keep quality assurance with or without the correctly trained employees.
AI Training Humans
In the instances above, robots are the solution for keeping quality assurance by replacing humans. However, it’s impossible to completely replace every human manufacturer. Because of this, manufacturers are also using automation in aerospace manufacturing as a tool to assist manufacturers in real-time for better quality. Two notable methods are predictive maintenance and decision intelligence (DI).
Predictive maintenance employs AI to analyze a robot’s production and patterns. The AI collects this information and determines if maintenance will be needed in the near future. Once determined, the robot utilizes this data to notify manufacturers. Predictive maintenance decreases the chance of a machine malfunction that results in a quality problem.
Think of this as evaluating your symptoms before telling the doctor you’re sick. The predictive maintenance catches these “symptoms” before they result in a defect or halt in production.
Decision intelligence, or DI, involves robots utilizing existing patterns and knowledge to make decisions in response to unexpected events. This intelligence is a new way that robots are thinking more like humans critically.
For instance, if a measuring device with decision intelligence detects a misaligned part, it can decide whether to recalculate the measurement based on the angle or adjust the focal point. Without DI, the device would produce an error message. This decision information guides unskilled workers when they’re faced with troubleshooting. In turn, workers and machines are more precise when it comes to aerospace metrology and inspection.
As AI trains employees and gives insight into problem-solving, aerospace production companies are investing in user-friendly software interfaces. With easy use, the software isn’t another learning curve that unskilled employees have to conquer. Instead, it can be immediately integrated into the manufacturing process, where employees learn skills while the AI prevents human error.
AI Data Management Systems
Traceability, the practice of tracking a product through its journey in the supply chain, is vital to the aerospace industry. The FAA requires almost every component to have identification marks to facilitate rapid recall, data organization, and anti-counterfeit efforts.
The efficacy of traceability relies on data management and optimization. Unorganized and unshared data is counterintuitive to the traceability process. AI data management systems that organize, analyze, and share product data are elevating traceability standards and, in turn, quality.
These systems are integrated into inspection and measurement devices, enabling cross-functional utilization of the gathered data. They can produce graphs, statistical analysis, and industry traceability reports with the data collected by the machine. Using these tools, manufacturers receive precise data from the entire supply chain and can easily access and evaluate the data at their production site to identify problems in real-time.
The Future of Aerospace Manufacturing
Automation in aerospace manufacturing is expected to become more digital and advanced as time goes on. Even though it’s currently held to high standards and production, incorporating these new technologies is a way to boost efficiency, decrease energy, improve precision, and have less downtime.
The future of AI in aerospace manufacturing is also moving towards the defense industry. Deloitte predicts cyber security officers will improve AI’s security against data breaches. Once security is obtained, this technology can be used in aerospace defense manufacturing for secret projects.
Automation is currently working alongside new employees and will keep shaping the industry. It will continue to take on new roles, teach new skills, help with data, and take the aerospace industry to new heights.