MADE | Maritime Case Study

Optimizing Maintenance Strategy for Legacy Maritime Assets |

Enabling a data-driven transformation of legacy fleet sustainment by optimising maintenance strategy, improving operational availability, and reducing life cycle cost using MADE.

Operational Availability
Increased Platform
Availability
Reduced Sustainment
Cost Risk
Validated Maintenance
Strategy
1
Digital Risk
Twin
The Challenge

Restoring Availability and Affordability Across Legacy Naval Platforms

The Contractor held a long-term contract to provide maintenance and logistics support for a class of navy ships at an agreed level of operational availability. But the platform was not meeting the contracted readiness target, creating sustained operational pressure and commercial risk.

The challenge was not simply to do more maintenance. The Contractor needed to determine which maintenance actions were delivering value, which systems were underperforming, and how maintenance approach and periodicity could be changed to improve availability in the context of real mission profiles and operating environments.

Just as importantly, the Contractor needed a defensible way to validate recommendations, quantify cost and readiness impacts, and communicate the analysis clearly to the customer. That required a model-based approach capable of linking operational usage, failure behaviour, maintenance strategy, and life cycle cost with confidence.

Readiness Shortfalls
The platform was not achieving the contracted operational availability target, demanding a measurable improvement in readiness without inflating sustainment effort.
Legacy Maintenance Mismatch
OEM maintenance recommendations were not fully aligned to real operating conditions, mission profiles, or the failure behaviour emerging across ageing maritime systems.
Need for Customer Validation
Any change to maintenance strategy or design needed to be validated technically and economically, then communicated in a way the customer could trust.
The Approach

Model-Based Maintenance Optimisation and Validation Using MADE

Analyse Maintenance Data and Identify Poor Performers

The Contractor analysed maintenance records and used MADE to identify poor-performing components and systems that were failing more frequently than expected. This established where sustainment effort and availability loss were being driven across the fleet.

01
Optimise Maintenance Approach and Periodicity

Using MADE, the Contractor identified potential changes to maintenance approach and periodicity for poor-performing components. This enabled alternative sustainment strategies to be assessed against real operational usage and operating environment assumptions.

02
Conduct Trade Studies Across Availability and Cost

Trade studies were performed to increase operational availability, model the impact of mission profile and operating environment on maintenance cost, and calculate the potential reduction in sustainment costs for the platform.

03
Validate Improvements and Build Reusable Knowledge

MADE was used to technically and economically validate design improvement recommendations, create a reusable knowledge base of failures and maintenance actions, and provide a clear means of communicating defensible analysis to the customer.

04

“MADE gave the Contractor a rigorous way to optimise sustainment strategy—linking maintenance decisions, mission profile, availability, and cost in one defensible model.”

Outcomes

Measurable Results. A Sustainment Strategy Built to Perform.

Improved Operational Availability

Alternative maintenance strategies were identified and assessed to increase platform readiness and close the gap to contracted availability targets.

Reduced Sustainment Cost Risk

Mission-aware cost modelling and maintenance optimisation identified how sustainment costs could be reduced without compromising operational outcomes.

Validated Sustainment Knowledge Base

Failures and maintenance actions were captured in a reusable knowledge base to support future decision-making across the life of the platform and contract.

Challenges Overcome
Validate OEM maintenance recommendations against real operational data and usage patterns
Identify poor performers and recommend changes to maintenance approach and periodicity
Build a clear, defensible case for improving availability while reducing sustainment cost
Keys to Success
Use maintenance data analysis to identify poor-performing components and systems driving readiness loss
Model the impact of mission profile and operating environment on maintenance cost and platform availability
Validate maintenance and design improvement recommendations technically, economically, and operationally
Outputs
MADE delivered the analytical outputs required to validate maintenance strategy, identify poor performers, quantify availability and cost improvements, assess design changes, and support customer-facing sustainment decisions with confidence.
MADE - Outputs

Digital Risk Twin Analysis Outputs

Functional Block Diagram
Functional block diagram of the selected systems.
Reliability Block Diagrams
Reliability Block Diagrams of the systems (to identify PP components).
Failure Diagrams
Failure diagrams of PP components (to capture associated physics of failure).
FMEA / FMECA
Automatically generated from the MADE model to identify critical failure modes.
Back-fit RCM
Back-fit RCM analysis conducted on PP.
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Increased capability readiness
Reduced sustainment costs
Validation and recommendation of new designs
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