Intelligent algorithms for technical documentation indexing in the Industry, how does it work?

Firstly, intelligent algorithms for documentation indexing are tools designed to facilitate the search and organization of large amounts of information within documents.
They employ advanced artificial intelligence and natural language processing techniques to automatically analyze, understand, and categorize the content of documents.

One key aspect of these algorithms is their ability to extract relevant information from the documents. They can identify entities such as names of individuals, locations, dates, events, phone numbers, email addresses, etc. They can also comprehend the structure of documents, including headings, subheadings, paragraphs, bullet lists, etc.

Indexing Algorithm for Technical Documentation - Autolink - Quickbrain - ENNOVIA - Saving time for Industrial Maintenance

These extracted pieces of information are then utilized to create an index or structured representation of the documentation.

Once the index is created, intelligent indexing algorithms enable efficient and precise searches. They can take into account semantic similarity between words and concepts to provide relevant results, even when the search terms don’t exactly match the document text.

For example, if you search for “car” in the documentation, the algorithm can also return results containing the term “automobile.”

Furthermore, these algorithms can employ machine learning techniques to improve search results over time based on user preferences and past interactions.

Thus, they enable efficient searching and provide relevant recommendations in environments where documentation is abundant.

Un exemple concret : la fonction Autolink dans QUICKBRAIN

What is Computerized Maintenance Management System (CMMS)?

The latest version of our CMMS tool, “QUICKBRAIN,” includes the intelligent algorithm “Autolink”.  This unique tool automatically classifies and associates 30% to 50% of the documentation, simplifying document search through functional tags or document references.

This functionality is particularly useful for automatically linking a document to the equipment in the plant’s hierarchy, thereby facilitating its retrieval.

It also automatically creates links to reference documents cited within technical documentation.

Autolink Algorithm for Documentation Indexing and Its Tagging System

ENNOVIA Indexing Algorithm for Technical Documentation - Autolink - Quickbrain - Industrial Maintenance
  • Firstly, it allows for cost reduction in maintenance through better resource management and preventive maintenance. By proactively planning maintenance operations, companies can avoid costly downtime and extend the lifespan of their equipment.
  • Additionally, CMMS improves the productivity of maintenance teams by automating processes, providing clear instructions, and reducing human errors. It also optimizes resource utilization by avoiding unnecessary purchases and reducing spare parts inventory.

Many documents have tags within their content, and reading the document to determine the relevant equipment (via its tag) can be cumbersome.

However, this search is crucial for “indexing” the document and associating it with relevant tags. This allows users to find documents related to the equipment for which they need information.

The “Autolink” function in Quickbrain extracts tags from documents, calculates a confidence index, and suggests semi-automatic tagging for tags that the document is not yet linked to.

It also has the capability to dynamically detect tags or document codes directly within PDFs, enabling unparalleled interactivity when reading a document. It is possible to directly open an interactive diagram or document from the processed text of the PDF in real-time by Autolink.

…In short, it provides a phenomenal time-saving advantage!

Video Demonstration

Because images are always more illustrative, here’s a preview of the Autolink module in video format:


Autolink in Video: Intelligent Algorithm for Technical Documentation Indexing - Smart Navigation - Quickbrain - ENNOVIA

Conclusion: Documentation indexing algorithms designed to save time for teams!

In conclusion, intelligent algorithms for documentation indexing enable the deployment of unique features for indexing and document search.

This is achieved, in particular, through advanced technologies for recognizing codes (equipment codes or tags, document codes or tags, etc.) within documents.

For maintenance technicians, the time-saving benefits are immense. They can focus on higher-value tasks and perform their interventions with peace of mind.

These tools also allow us to be more efficient in delivering our services and enhance the quality of your technical documentation at an optimized cost.

Intelligent documentation indexing algorithm - Autolink - Quickbrain - ENNOVIA - Saving time for industrial maintenance

If you’d like to discover the full power of our document management systems in QUICKBRAIN, request a demonstration!