Proper Knowledge Management and Machine Maintenance

Proper Knowledge Management and Machine Maintenance

One of the best ways to paint a picture of how Mindbreeze InSpire and consolidating information into a single application can help your enterprise is by providing concrete examples. One of our most prominent use cases and areas that have benefited from the power of Mindbreeze InSpire is with teams involved in the maintenance and fixing parts on all sorts of machines – including aircraft.

With any piece of equipment, taking steps to ensure maintenance is done accurately and reliably is crucial for safety and avoiding reworks. Defects in machines or other devices cause downtime for a business, resulting in interruptions to operations that directly impact performance and profits.

A large airline could have up to a million documents of structured and unstructured information relating to their aircraft components. This colossal number of records is also frequently stored across hundreds of applications, making it highly complicated for employees to find the information they need at the time they need it.

Using AI to connect these data sources eliminates the complication and creates a simple solution for maintenance workers to search and see what they need in a matter of seconds.

Mindbreeze InSpire works behind the scenes to filter only the most relevant documents to the user – this could be inventory lists, logistics information, or other maintenance plans and blueprints. Filtering relevant documents to the user's needs avoids digital clutter on whatever tablet or computer they are working on and ensures accurate and productive operations. Like a Google search and not having to scroll to page ten to find the link you are looking for, Mindbreeze InSpire takes steps to ensure the relevant files are at the top of your results.

You can find more information about how Mindbreeze InSpire optimizes relevance in a previous blog post.

Predictive Maintenance

While an insight engine provides value to a worker when fixing the system, artificial intelligence makes it possible to detect possible defects well before – a term called predictive maintenance.

In short, predictive maintenance is a technique used to monitor the performance and current condition of equipment so businesses can address fixes and replacements before a failure or shutdown occurs.

Using sensors to measure key indicators of a machine's lifetime results in alerting a business when any deviations from the norm occur.

Routine checks on equipment will always be a part of the process, especially in aviation. However, using state-of-the-art technology to get ahead of a machine failure can save a business an exceptional amount of time and dollars.