Challenges and Promises of Big Data Maintenance Solutions for Commercial Aircraft
January 2019

Paul Neff of Honeywell Air Traffic Management Initiatives, will talk us about the leading technology of predictive maintenance.

Traditional aircraft maintenance and trouble shooting expertise has been a combination of aircraft and equipment OEM training, on-line and shop experience, and trial and error (with numerous examples of an anomaly exhibiting itself in one LRU, but with a root cause found in another connected device) and at experienced operators what some affectionately call tribal knowledge.

With the developments of advanced systems, industrial software design, development, testing and certification standards, and with the dawning of the so-called big data era, aerospace equipment suppliers have and are developing big data and analytic solutions to enhance the maintenance of those equipments. There is a growing expectation that these big data/analytics era will bring greater efficiencies, better fault-finding techniques, prescriptive maintenance capabilities and predictive (and therefore maintenance action avoidance) capabilities. These promising developments are not without their challenges and associated learning curves.

This lecture discussed so-called connected maintenance solutions via big data and analytics capabilities, using Honeywell equipment examples to provoke thinking and discussion on both the promise and challenges of these developments in the aerospace business arena.