Jaroszewski thinks his software outperformed Airman in spotting several bleed-valve problems because it looked at correlations of all the data, not just one signal. He says the approach is applicable to many aviation components, so long as data is plentiful, as it increasingly is with new aircraft. Apparently others agree: FCE has been talking to several aviation companies, including Lufthansa Technik, in recent months.
Other consultants are also active. “No one has all the tools,” stresses Vijitha Kaduwela, CEO of Kavi Associates. He says good analytical tools are available from SAS, IBM, SAP and others. “But you cannot just buy off the shelf and go; you must customize it.”
That is what Kavi consultants, drawn from United Airlines and GE, do. Kaduwela believes there is great value to be gained in spotting chronically defective units, minimizing aircraft downtime, assessing supplier quality and finding the “bad apples” among aircraft. “There are lots of opportunities to find the outliers and fix them,” he says.
For example, text comments on job cards could help spot chronically failing units, but this data has not been digitized and mined. Text-mining techniques are now making that possible. “There is big money if you can weed chronically failing avionics items out of your supply,” Kaduwela says.