Titel Luftfahrt
Lufthansa Technik unterzog ein ausrangiertes Düsentriebwerk ausgiebigen Prüfstandversuchen, um Daten zu sammeln. © Lufthansa Technik

Lufthansa Technik aims for more efficient maintenance

Big data should improve forecasts about ageing and wear marks - project is part of digitalisation strategy

Aircraft stay on the ground when engines malfunction. Maintaining and repairing complex engines is an expensive and complex undertaking. Now, the Hamburg-based maintenance, repair and overhaul (MRO) firm, Lufthansa Technik, has adopted a new approach to more efficient engine maintenance. And to this end, it headed a research project called Advanced Prediction of Severity Effects on Engine Maintenance (APOSEM) involving the German Aerospace Centre (DLR), Braunschweig Technical University, Stuttgart University, ANSYS and a U.S. engineering simulation firm from January 2014 to December 2016.

Improved prediction of ageing processes in jet engines

Lufthansa Technik will use its data base on engine performance and life cycles to develop digital predictive models that can be used to anticipate the development of ageing processes, wear and tear and other parameters during the life cycle of an individual engine. Lufthansa Technik collected the data during its engine monitoring effor over several years. The firm has been electronically monitoring its clients’ engines during day-to-day operations for around 30 years now. These data are collected and analyzed in the firm’s data centre in Frankfurt.

Engine trials

As part of APOSEM, researchers also used data gathered during trials with a real jet engine. Lufthansa Technik took a retired CFM56-5C jet engine and equipped it with additional sensors. Then, the engine was run for a prolonged period on a test rig. “Thus, we were able to gather more data,” explained Thomas Erich, spokesman for Lufthansa Technik. He added: “The engine was evaluated in a variety of scenarios.” This allowed the experts to take a deeper look into the workings of the engine in rain, dry weather, during powering-up, during take-off, landing and moving on the ground, but also under extreme climatic conditions. This has led to improved understanding of both the effects of the airstream flowing through the engine and the jet turbine’s ageing process. Moreover, this test served to verify the digital models and the predictions devised during APOSEM.

Benefits of big data

Until now, it has been difficult to predict an engine’s ageing process and the effects of wear and tear. Lufthansa Technik relies on information gathered during flight operations and regular maintenance, repair and overhaul work. However, so-called big data technologies that allow for the gathering and processing of huge amounts of data are making more precise predictions possible. “Now, we have the opportunity to predict ageing and wear and tear with more precision, and we have a deeper reach into the engine,” said Erich. If the experts know, for instance, that an engine is operated in desert conditions, they will expect damage caused by sand and dust. This may be blocked cooling holes and damaged turbine blades or ceramic parts ground down by sand particles. Then, they would examine the data. APOSEM aimed to gain expertise that will lead to new products later.

Lufthansa Technik’s digitalisation strategy

The project is part of Lufthansa Technik’s broader digitalization strategy. The company’s predictive maintenance approach uses data gathered on the various aircraft of the company’s clients to improve the scheduling of maintenance cycles. Moreover, the firm is able to offer MRO plans that are both economically viable and in accordance with current aviation industry standards for customers. “Predictive maintenance allows us to devise bespoke programs that are based on the actual state of the aircraft,” Erich pointed out.

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