We developed a unique tool to aid effective planning and ensure capability sustainment across the Royal Navy’s Carrier Strike Group 21.
To maximise operational and cost efficiency, Army HQ needed to rationalise and exploit highly fragmented data resources within a complex and diverse supply chain.
We led on delivery, aligning stakeholders from the Strategic Alliance Board – Royal Navy, DE&S Ships, Babcock Marine and BAE Systems to deliver a powerful prediction and decision-support tool. The result – Techmodal: Prediction Engine, a revolutionary system that presents current and predicted future materiel state of the ships in the Strike Group.
Since the start of the project in March 2021, we have demonstrated our capability to develop a complex technological solution in a challenging environment using disparate datasets from across the Strategic Alliance Board. We are achieving an impressive accuracy in predictions within just 8 weeks of starting.
“The UK Carrier Strike Group is a great symbol of collaboration, both across the Armed Forces and our industry partners. Sailing together through a number of different environments, the partnership will uphold British values and international order. ”
– Rt Hon Ben Wallace, Defence Scretary of State
CSG21 is significant as the first operational deployment of a QE-class carrier but, at the strategic level, it symbolizes so much more. The most significant deployment of its kind for a quarter of a century, it is a visible demonstration of the Royal Navy’s resurgence after decades of contraction. As our nation redefines its place in the world post-Brexit, it is the natural embodiment of the Government’s ‘Global Britain’ agenda, against a backdrop of growing instability and competition, it reflects the United Kingdom’s continued commitment to global security.
The challenge
The Royal Navy is one of the most highly regarded and best equipped maritime forces in the world. In 2021 it deployed the UK Carrier Strike Group 21 (CSG21), led by HMS Queen Elizabeth and including ships from the UK’s allies and partners. The deployment is logistically complex and the Navy faces the difficult task of predicting critical failures to sustain operational capability across the fleet both now, and in future. There is currently no system, or consistent approach that enables prediction across all ships in the Carrier Strike Group. Our expertise in understanding the Royal Navy’s supply chain logistics and the intricate engineering and configuration data landscape means that we are positioned to achieve rapid results.
Techmodal: Prediction Engine improves the reporting process resulting in an automated simplified system
that reduces manual burden on SMEs.
Techmodal: Prediction Engine assessment of forward-held inventory, highlighting discrepancies in the consumption rates and allowing users to effectively manage stock-holdings and plan for shortfalls in stock. This combined with an accurate picture of future failure events significantly improves operational planning.
Enables the Royal Navy to gain deeper insight into risks to availability. By identifying likely
failures months in advance mitigations and other support measures can be put in place.
Provides DE&S Ships and Navy Command HQ with insights into operational status
across the task group, and informs decisions on how the capability of the CSG can be
sustained.
Techmodal: Prediction Engine disparate data sources from across the complex Royal Navy landscape. We apply machine learning-enabled artificial intelligence to ensure that decision-making is supported by accurate, consistent, and complete information. We are bringing together the most complete picture of a platform ever compiled and combining it with the latest in machine learning approaches to deliver a revolutionary new view on capability sustainment.
latest in machine learning approaches to deliver a revolutionary new view on capability
sustainment.
the solution
By seamlessly blending cutting-edge machine learning and user-centric design we have produced the authoritative capability assurance Techmodal: Prediction Engine. Data from industry, the Navy and open-sources was used to train an ensemble of machine learning models. These models can learn from the context around historic failures to predict which systems are likely to fail in the future. This capability, combined with data on maintenance and engineering defects, highlights where risk lies within a system and helps engineers and logisticians to make better decisions on planning mitigations, proactively getting ahead of issues before they occur.
Already, with limited sets of data, we are predicting with high accuracy levels. As we continue to refine our approach and add in additional data this accuracy level continues to rise. Using PowerBI, a front-end was built to sit on top of a huge amount of additional ship configuration and logistics data which is combined with the output from the predictive model. This gives a consolidated, trusted, view of current and future materiel state for platforms in CSG21. It can also be scaled to include the entire surface fleet and be applied to any future naval deployments.
The user can view the status of the Carrier Strike Group (current and predicted) across various levels of granularity: Task Group, Class, Platform, System, and Sub-System. The dashboard enables this drill-down through a hierarchy of systems. We provide an assessment of forward-held inventory and system criticality alongside a range of other data to support decisions. This solution has improved and automated existing manual reporting processes, resulting in a consistent and simplified process, and reduced manual burden on SMEs.
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