Senior Consultant Maintenance Repair & Overhaul at ADSE Consulting & Engineering
Condition Based Maintenance in aerospace – cross industry learning
Condition based maintenance (CBM) is nothing new. However, with the onset of more advanced sensor technology, cost effective data transfer possibilities and Big Data analytics the barriers to using more and more sensor data for CBM have gone down. One sector, where sensor based CBM has been widely used for some decades is the aerospace industry. This paper lays out the current best practice and use of sensor data in the aerospace. In aerospace, the use of sensor data can be roughly classified in three areas. • Inflight transfer of Diagnostics data allowing for more effective and in advance troubleshooting. This allows for a reduction of ground time and therefore an increase in aircraft availability. Examples of diagnostics data are seen in various Aircraft electronics components, aircraft complex integrated aircraft systems.
- The collection and transfer of Health data allowing for optimized and more effective maintenance scheduling. The use of sensor data on cost critical components has allowed a shift from a traditional time based maintenance to a usage based maintenance effectively reducing ‘over maintenance’ and reduce cost. The gas turbine engine (with overhaul cost in excess of 4m euro’s) is a good example of where health data has been extensively used for this purpose.
- As aircraft become more embedded with sensors and data transfer becomes more affordable, the aerospace industry is moving towards advanced analytics to better predict system failure. Correlation of aircraft sensor- and maintenance-data is now used to make better prediction about part usage and failure behavior.
After graduating from Oregon State University in 2002, Arjan has held various positions within the airline maintenance industry. He started off as an Avionics Engineer with KLM Engineering & Maintenance and moved on to VLM Airlines where he was responsible for engine maintenance and became Engineering Manager. In 2008 he moved to JetNetherlands where he worked as Maintenance Manager. Arjan then worked with the Amsterdam University of Applied Science where he focused on practical research in LEAN and Data Mining in small and medium MROs. Arjan is currently employed at ADSE Consulting & Engineering, where he is responsible for MRO and Big Data services. He is also an active RAM/LCC consultant in the rail industry. His expertise is in aerospace and rail maintenance & asset management with a special emphasis on the application of LEAN, Six Sigma, TOC and the use of Data Science.