Aerospace is a growing, changing industry. More information is being collected, creating more data that needs to be analyzed and extrapolated to continue to innovate and advance a company in this industry. Companies want to create aircrafts that are more efficient, more customizable, better designed, faster, cheaper, safer, and more environmentally friendly. To do so, all of that information needs to be processed and understood.
Hundreds of pages of technical text can be difficult to read and organize, which could lead to an important requirement being missed. As the industry grows and changes, new solutions to the problem of text data are being created.
Changes, data and regulations
Sensors onboard aircraft are constantly collecting data. Information on the systems, equipment, and current and future weather conditions are sent from aircraft to pilots and ground operations. In the near future, planes could be able to minimize turbulence and maximize fuel efficiency by altering their routes using real-time data. Autonomous flight is getting closer to reality.
Using analytics to improve maintenance efficiency is increasing in popularity. Predictive maintenance uses analytics to determine when to replace certain parts of an aircraft. This helps maximize the lifespan of these parts, ensuring safety and minimizing equipment checks.
The space industry is getting bigger and more varied. Commercial flights and cubesats are providing a completely new business model and service design for the industry. New technologies are being introduced, making the engineering projects more complex.
Customer demand and the goal of achieving sustainable growth are factors for growth and change in every industry. In aerospace, there is a new focus on reducing emissions, innovation in cabin design, and a reduction in travel time. Production line efficiency is a way for companies in aerospace to achieve sustainable growth. These factors are reshaping the industry, changing how companies operate.
This increase in complexity is providing more and more data that needs to be processed, analyzed, and implemented. With a lot of safety critical aspects to take into account, text data for safety requirements, engineering requirements, and new regulations are expected to increase. With all of these changes, there will be even more text data to process and organize to ensure all regulations and requirements are being met.
Issues with processing vast amounts of text data
During procurement, time can be of the essence, and reading through hundreds of pages of technical text takes a lot of time. A large document may need to be read and understood very quickly so that a new project can get underway. Unfortunately, this can lead to some parts being misunderstood or missed entirely. Leaving room for error is a huge risk to the company, and can put them in breach of the contract they’ve signed, not to mention the potential for grievous errors in the finished project.
Engineering projects in the aerospace industry are based on a set of written specifications. These text documents are typically very large and can be difficult to navigate to the desired or applicable sections. They are also very complicated when the reader is trying to extract only the sections relevant to certain groups.
For each new space mission, a very large set of written requirements is passed down the supplier chain, all of which needs to be met and verified. Missing a relevant set of requirements can complicate projects and impact the project’s bottom line significantly.
With all of the advancements in technology, the aerospace industry is changing at an alarming rate. Devices are improving, becoming more complex, and increasing in popularity. All of these changes are creating more data in the form of requirements and regulations that need to be processed and analyzed before a project can be completed successfully. Trusting this job to a group of people who are assigned the task of reading through hundreds or thousands of pages of technical text can leave room for human error.
What would happen if a company missed a new regulation put forth by a governing body? Or if they didn’t catch an engineering requirement that directly contradicted a new safety requirement?
People can misunderstand requirements or fail to catch contradictory requirements when given the task of analyzing vast amounts of text data. Human error is not always something that we can afford. Fortunately, however, there are tools that can help alleviate these risks.
Solutions to help with processing text data
Where Ansys Esterel helps with critical system code, there are a set of tools that can also relief complexity on the text data and requirement side.
Skywise, by Airbus, aims to connect all aspects of the aviation sector, and eventually all of aerospace, by allowing companies to improve efficiency through the use of one digital platform to integrate all data sources. Compiling shareable information on maintenance, safety, and other workflows allow for greater transparency and increased communication and efficiency.
Selko Analytics uses AI to help locate specifications specific to certain groups, using “Intelligent Search” for a fast analysis of the text data, or user-trained machine learning that requires only 100 samples.
Using Artificial Intelligence to categorize and analyze vast amounts of data ensures that a person can spot risks, important requirements and regulations. All results can be verified by a person before export, and any changes made will be learned to produce better results next time.
Surrounded by today’s complex technology, it is important to stay on top of the game. Solutions such as these helps reduce risks and help manage all that text information. They help companies optimize their efficiency in an industry that is very quickly changing.