Designing Condition-Based Maintenance
for Next-Gen Aircraft Engines
|
Enabling a data-driven transition to Condition-Based Maintenance by optimising sensor strategies, validating diagnostic capability, and building a defensible business case using MADE.
Coverage
Cost Risk
Design
Twin
Designing a Defensible CBM Strategy for a Next-Generation Military Engine
The OEM was developing a next-generation turbine engine for military aircraft and needed to determine how best to enable a Condition-Based Maintenance approach. This meant identifying the right combination of sensors, assessing how effectively faults could be detected and isolated, and proving that the proposed diagnostic design would deliver real operational and commercial value.
Simply adding more instrumentation was not enough. The OEM needed to understand which sensor locations would maximise diagnostic coverage, reduce ambiguity, and support prognostics and health management without introducing unnecessary cost, weight, or reliability penalties.
Just as importantly, the OEM needed a defensible way to validate the design to its customer. That required a model-based approach capable of linking sensor decisions to fault coverage, diagnostic rules, and business case outcomes with confidence.
Model-Based Diagnostic Design and Validation Using MADE
The OEM created a MADE model of the turbine engine and its expected mission profiles to establish the analytical foundation for diagnostic design. This provided a structured representation of system behaviour, operating context, and how faults could propagate through the engine under real use conditions.
Using MADE, the OEM generated FMECA to identify and document the failure modes most critical to engine performance, safety, and maintainability. This ensured the diagnostic design was focused on the faults that mattered most from both an operational and business perspective.
The inherent capability of the existing diagnostic architecture—including BIT and control sensors—was assessed to determine how effectively critical failure modes could be detected. This allowed the OEM to validate legacy diagnostic coverage and clearly identify where gaps still existed.
MADE was used to identify additional sensor locations, allocate sensors against user-defined constraints, compare alternate diagnostic options across cost, weight, and reliability, and generate model-based diagnostic rules. This enabled the OEM to select the optimal solution for fault coverage, ambiguity resolution, and overall CBM business case performance.
“MADE gave the OEM a rigorous way to design and validate CBM capability—linking sensor strategy, fault coverage, and business value in one defensible model.”
Measurable Results. A Diagnostic Design Built to Perform.
Improved Diagnostic Coverage
Legacy coverage was validated and new sensor options were identified to expand coverage of critical failure modes.
Smarter Sensor Allocation
Sensors were allocated against user-defined constraints to maximise diagnostic value while managing weight, cost, and reliability impacts.
Validated Diagnostic Knowledge Base
Propagation tables and diagnostic rules created a reusable analytical foundation for diagnostics, prognostics, and ongoing support decisions.
See What MADE Can Do for Your CBM and Diagnostic Design Program
Talk to a PHM Technology RAMS MBSE specialist and discover how MADE can help you design, validate, and justify smarter Condition-Based Maintenance strategies.
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