Design for CBM

Outcomes

An analysis solution for the OEM that provides:

1. Identification and validation of legacy diagnostic system coverage
2. Identification of potential options to increase system coverage by introducing new sensor locations
3. Sensors allocation based on user defined parameters and restrictions to enable maximal coverage
4. Identification of diagnostic rules to enable isolation of faults (Ambiguity resolution)
5. Propagation tables to detect component responses

Process

The OEM analysed the maintenance records for the platform to identify components that were failing more frequently than expected, and used MADE to:

1. Generate a MADE model of the engine and its expected mission profile/s
2. Generate FMECA to identify / document critical failure modes for the system
3. Assess inherent diagnostic capability (coverage) of the system (incl. BIT, control sensors)
4. Identify additional sensors required to cover all critical / nominated failure modes
5. Select appropriate sensors for nominated diagnostic solutions
6. Compare the metrics for alternate diagnostic solutions (cost, weight, reliability)
7. Select the optimal diagnostic solution (efficacy & business case)
8. Generate diagnostic rules (model-based) for each failure mode

Outputs

MADE was used to generate the following deliverables:

Functional block diagram

Functional block diagram of the selected systems

PHM Coverage

Generation of sensor sets

Diagnostic rules

Identifies failures based on sensor response

FMEA / FMECA

Automatically generated from the MADE model to identify critical failure modes

Sensor Set Comparison

Allows users to compare sensor sets parameters (coverage, size, weight, cost)