Artificial Intelligence and Airlines – 200,000 maintenance cases addressed 90% faster

I thought this article published by IBM Watson deserved a post as it is a great example of artificial intelligence at work, in this case, the efficiency being created is so large I am sure others reading this will start to envision similar synergies for their companies and industries.


Korean Air has years worth of historical maintenance records for hundreds of aircrafts in its fleet. But until recently, this vast amount of critical data was virtually unsearchable. That meant that maintenance technicians had to diagnose and fix issues without being able to tap into or interpret implications from valuable past learnings and courses of action.

Enter Watson

Watson ingested structured and unstructured data from multiple sources including technical guidelines, non-routine logs, technician notes, inventory, trouble shooting time and material cost data, and in-flight incident history.

Watson Explorer, Natural Language Understanding and advanced content analytics locate previously hidden connections that helping maintenance crews diagnose and solve problems more quickly, with more confidence. Instead of spending hours diagnosing each potential issue, technicians can easily search and get near real-time analysis.

Further, if an issue occurs in flight, the cabin crew can report it immediately to ground operations. Watson will access data from similar issues in the past and compare this information against technical guidelines including necessary materials and fixing time. Maintenance technicians fix the issue on the ground and enter their actions into the system to add to Watson’s knowledge.

With Watson, maintenance managers can also identify trends of issues in each season and can take these insights to the original equipment manufacturers for improvement.

Over 200,000 maintenance cases per year are addressed 90% faster

Korean Air needs their over 2,000 maintenance employees to be able to act faster. When Watson delivered actionable insights on the root causes and solutions of issues, Korean Air shortened its maintenance defect history analysis lead times by 90%.

The maintenance employee can now see patterns of defect and failure on equipment to make preventive maintenance allowing them to spend more time getting people places on time—and working to keep their 25 million passengers happy.

Airlines, hospitals, businesses, educators and governments are working with Watson. In 45 countries and 20 industries, Watson is helping people make sense of data so they can make better decisions while uncovering new ideas.

How Korean Air worked with Watson

(In 5 simple steps)

1. Watson ingested a variety of structured and unstructured data related to maintenance for the hundreds of planes in Korean Air’s fleet.

2. Maintenance defect issues are reported by flight or cabin crews to ground operations.

3. Maintenance employees access data from look-a-like cases against technical guidelines.

4. Watson assists to decide probable cause and recommends solutions so that they can be quickly addressed by technicians.

5. More flights are on time, keeping 25 million passengers happy.

The full article can be seen here:

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