Predictive maintenance on aircraft and applications with digital twin
Heim, Sam Clemens, Jason R. Steck, James E. Basic, Christopher Timmons, David Zwiener, Kourtney
Heim, Sam
Clemens, Jason R.
Steck, James E.
Basic, Christopher
Timmons, David
Zwiener, Kourtney
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Issue Date
2021-03-19
Type
Conference paper
Genre
Keywords
Aircraft,Big data,Digital twin,Supply chains
Subjects (LCSH)
Citation
Heim, S., Clemens, J., Steck, J. E., Basic, C., Timmons, D., & Zwiener, K. (2020). Predictive maintenance on aircraft and applications with digital twin. Paper presented at the Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020, 4122-4127. doi:10.1109/BigData50022.2020.9378433
Abstract
The concept of predictive maintenance in aiding the manufacturing and operation of equipment is moving several industries forward, allowing for a more detailed description and justification of maintenance routines. This paper provides several methods of describing the remaining useful life of given parts for aircraft maintenance through two separate aircraft data sets. It is then shown how these results, in conjunction with a digital twin model, can be used to aid in designing a sufficiently stable supply chain and maintenance strategy.
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Publisher
IEEE
Journal
Book Title
Series
2020 IEEE International Conference on Big Data (Big Data);