Data is the center of all modern business. Having a synchronized environment where the data from all the touch points gets updated and lets all parts of the business get an optimal result is what the future business demands.

The aviation industry handles lots of data/documents on both the ground and on the air. Especially in aircraft maintenance, hundreds & thousands of technical data will be scattered, and each engineer will have a fragment of information and knowledge about it. Maintaining all the records error-free, ensuring safety, and making the data accessible for all the teams is a stupendous task for companies in the aviation industry, and the expenses are also on the higher end of the spectrum.

AI-powered content intelligence platform lets aviation firms easily categorize scanned data, upload it to the corresponding system, create an intuitive knowledge graph, and help the different teams generate models and reports as per their requirements.

Challenges in the traditional data management

The biggest challenge in aircraft maintenance starts from the documents themselves. Each document will be in different formats like handwritten copies, images, scanned copies, unstructured information, etc.

What’s more complicated than maintaining the records is retrieving information from the records. It takes several hours of time and human resources to retrieve a piece of information based on the date, particular incident, chapters, etc. Generating maintenance requirements and allocating human resources to ensure timely delivery will also take time.

RecoSense – Aerobot is an AI-powered content intelligence solution that collects information from all unstructured data and processes them in a meaningful way so that the complex information is distilled into easy to understand format from various perspectives. As a result, the user can have a deeper understanding of the data and quickly perform the desired task.

AI-Powered Technical Knowledge Database

Knowledge is typically an indexed encyclopedia. An AI-powered knowledge graph is an interactive medium coupled with an encyclopedia, where the user can easily find what they want.

The Aerobot adopts a systematic way to start and keep the data clean in its central data platform. Natural Language Processing (NLP) and machine learning system automatically extract key information (including images) from the documents and map them to the desired data fields in the centralized system. Hence record maintenance and retrieving become simpler.

The Aerobot AI uses machine learning to identify patterns and NLP to extract the meaning. For instance, if a technical document has a task card number, images, stamps, handwritten information, and signatures, the AI bot identifies and extracts the data. Later these information will be automatically tagged and mapped to the corresponding fields in the centralized system.

The Aerobot has effective knowledge graph features that can make the aircraft maintenance process simpler and faster. Here are a few important features –

• Semantic search – Since Aerobot extracts information using the NLP, relevant documents like OEM documents, internal documents, records of troubleshooting steps, etc., are properly linked. Hence one can easily search for data based on keywords, ATA chapters, incident descriptions, etc., and retrieve data quickly.

• Knowledge graph- Creates associative relationships with key entities of documents and processed content. Therefore the AI can provide recommended actions and generate reports for the corresponding teams.

• Compliance management- Auto-audit documents and data to cross-check with Reference documents and compliance standards.

With all these features, Aeorbot can be used for various applications in the aviation industry. The following are the two primary use cases related to the aircraft maintenance sector.

Virtual Technical Services Engineer (TSE)

Aerobot’s intuitive knowledge base and recommendation engine make it the best companion for technical service engineers. The AI bot can automatically identify the type of defects, historical record of defects or events, records of troubleshooting steps taken to resolve a defect, and correlates the key entities in the knowledge graph. Therefore, AI can-

• Enable advanced search based on different ATA chapters or keywords or incident descriptions and also provide relevant interlinking to internal documents. This makes the technical follow-ups and retrieval of data more accessible for the service engineers.

• Provide recommended actions to the technical service teams based on past knowledge and experience.

Optimal Auto-Resolution with adaptive learning

Aerobot’s advanced machine-learning capability and intelligent deep-learning methodology can automatically identify events, faults, and defects, correlate Engine-Product-Part, reports of the troubleshooting actions taken to resolve a defect, and provide an optimal solution. With the scalable interface, the Aerobot can be used for-

• Creating necessary reports & solutions based on different user roles and requirements in the Engineering Division like Line Maintenance, Maintenance Control Centre, and Fleet Technical Management.

• Visualize data in an easy-to-understand format to have better insights and assist the engineering team in allocating the resources better and completing the maintenance task on time.

Impacts of deploying AI-powered data intelligence

• Helps the Operations Team troubleshoot aircraft defects, component failures, or reliability issues.
• Effortlessly keep track of Fleet Technical Digests and Technical Follow-ups with the knowledge graph
• Automatic error-free data extraction from the record with less human intervention
• Proper management of resources and ensuring timely delivery
• Improved customer satisfaction, which in turn results in customer retention & higher lifetime value
• Systematic and timely approach boosts productivity
• Early detection of anomalies reduces the operation cost

Aerobot is based on RecoSense’s tried and tested Docusense and Knowledge graph platform, which is being trusted by leading industry players. Enterprise-grade central data platform makes deployment on a large scale easier and keeps the data secured. The flexible infrastructure lets Aerobot adopt the custom requirements and be production-ready right out of the box.