Critical failure identification
Identify critical failures based on functional dependencies within the asset and understand their consequences across the system.
MADE for Condition-Based Maintenance
Design, improve and justify CBM capability with confidence.
MADE PHM helps engineering teams design diagnostic solutions, assess sensor coverage, validate fault detection and isolation, and prove whether a Condition-Based Maintenance capability earns its place on the system.
Risk Reduction
Mitigate critical and catastrophic failure risk.
Sensor Selection
Automate test point and sensor set assessment.
Diagnostic Rules
Generate model-based diagnostic logic.
Trade Studies
Compare coverage, weight, reliability and cost.
Availability
Improve uptime and reduce unnecessary maintenance.
The Problem
Maintenance strategy is often based on expected reliability, not actual equipment health.
Traditional preventive maintenance can lead to unnecessary servicing, premature removal of healthy equipment, inadequate servicing or unscheduled failures. For complex assets, the economic and operational impacts of unnecessary or inadequate maintenance can be significant, but difficult to quantify.
The MADE PHM solution.
MADE PHM enables engineers to design diagnostic solutions for Fault Detection and Isolation, assess probability of detection for specific failure modes, optimise diagnostic capability and validate the business case for CBM across the product lifecycle.
Maintenance Strategy
Move from scheduled maintenance to evidence-based intervention.
The right information, at the right time
The optimal maintenance strategy minimises both corrective and scheduled maintenance, conducting only the actions required to ensure safe operational availability when they are needed.
How MADE supports CBM capability design, improvement and justification.
MADE PHM connects failure identification, failure propagation, diagnostic requirements, sensor trade studies and diagnostic rule generation into one model-based workflow.
1
Identify potential failures
Use functional dependencies and standardised taxonomies to identify failure modes, causes, mechanisms, faults and symptoms.
2
Understand effects
Model local, next and end effects through automated failure propagation and stepping.
3
Assess CBM feasibility
Compare maintenance approaches and determine whether CBM provides MTBM, downtime and cost benefits.
4
Define monitoring capability
Assess sensor location, expected performance and reliability, including existing BIT and control sensors.
5
Generate diagnostic rules
Create diagnostic logic that monitoring systems can use to detect and distinguish failures.MADE PHM
Design a diagnostic capability that is technically justified and economically defensible.
MADE is a model-based integrated toolset that enables informed CBM design decisions and trade studies to identify the most cost-effective diagnostic and monitoring approach for a specific asset and operating profile.
Assess probability of detection for specific failure modes.
Compare alternate sensor sets by coverage, weight, reliability and cost.
Leverage inherent diagnostic infrastructure already present on the asset.
Support model-based reasoners and executable diagnostic rules.
Digital
Diagnostic
Twin
Diagnostic
Twin
Key Benefits and Features
Validate whether CBM buys its way onto the system.
MADE PHM supports iterative CBM capability design, assessment and validation across the asset lifecycle.
Key benefits
- Risk mitigation for critical and catastrophic failures.
- CBM capability design, assessment and validation conducted iteratively.
- Analysis conducted at every stage across the asset lifecycle.
- Trade studies to determine whether CBM buys its way onto the system.
Key features
- Automated sensor selection and test point assessment.
- Comparison of alternate sensor sets including coverage, weight, reliability and cost.
- Automated generation of diagnostic rules.
- Support for development of model-based reasoners.
What MADE PHM provides
A practical model-based environment for designing, monitoring and improving CBM capabilities.
Diagnostic requirements assessment
Define what monitoring capability is required, where sensors should be located, and how they support failure detection.
Cost comparison of alternatives
Compare alternate diagnostic approaches to understand availability, reliability, cost and supportability implications.
Lifecycle flexibility
Apply CBM design and improvement methods to both new systems and legacy assets throughout the asset lifecycle.
Automated dependency mapping
Use model-based failure propagation to understand system-level effects and maximise consistency of CBM design.
Engineering process integration
Configure the analysis to integrate with organisational engineering processes and existing diagnostic infrastructure.
Diagnostic Optimisation
Optimise the monitoring approach before investing in sensors and systems.
Coverage, reliability, cost and performance trade-offs
MADE PHM supports what-if analysis and trade studies of different sensor combinations, helping teams select diagnostic strategies based on measurable performance rather than assumptions.
How MADE improves the CBM business case
MADE helps justify CBM capability by linking diagnostic performance to reliability, availability, cost and risk outcomes.
Optimise availability and reliability
Model how improved detection, isolation and maintenance timing affect operational availability across the expected asset life.
Mitigate unscheduled outage risk
Identify critical failure paths and diagnostic gaps before they create safety, operational or economic consequences.
Leverage existing diagnostic infrastructure
Assess how BIT, control sensors and existing monitoring systems can support CBM without unnecessary additional hardware.
Support lifecycle decisions
Use model-based analysis to design, improve and justify CBM at concept, design, upgrade and sustainment stages.
Outcomes for CBM programs
MADE helps teams move from assumed maintenance logic to evidence-based diagnostic and sustainment decisions.
Reduce maintenance waste
Avoid unnecessary servicing and premature removal of healthy equipment.
Improve fault detection
Validate probability of detection and diagnostic coverage for specific failure modes.
Improve availability
Schedule intervention based on condition and incipient failure rather than time alone.
Justify investment
Show whether CBM delivers measurable operational and economic benefit.
Reduce risk
Mitigate technical and economic risk from unscheduled outages and critical failures.
Capture knowledge
Use standardised taxonomies and model-based reasoners to preserve diagnostic logic.
Recommended Resource
Download the MADE for CBM brochure.
See how MADE PHM supports Condition-Based Maintenance capability design, sensor selection, diagnostic rule generation, trade studies and lifecycle justification.
Design CBM capability that is technically valid and commercially justified.
MADE PHM helps teams design, improve and justify CBM capability by connecting failure behaviour, diagnostic coverage, sensor selection, maintenance strategy and lifecycle performance in one model-based framework.
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