Redefining Contested Logistics: How AI Can Optimize the Navy’s Refueling Operations

Leveraging artificial intelligence (AI) in military logistics has become an increasingly important strategic priority in recent years. For example, the US Navy has been exploring how AI can improve the efficiency and effectiveness of its logistics operations, especially regarding refueling operations. 

Why is this critical? The Navy rightly understands that the future fight is one in which its ability to operate effectively in a maritime and littoral environment will face challenges by emergent threats emanating from all domains and across our supply chain. A growing ecosystem of variables and inputs from diverse data sources and types makes for a more complex planning and decision-making environment. This creates the need to introduce advanced analytics and AI to impact operational planning and decision-making. In this blog post, I’d like to spotlight five ways AI can address the challenges of contested logistics in the US Navy, particularly in the context of ship refueling.

Navy operational logistics is a subject I am very familiar with, as I have almost three decades of experience as a Surface Warfare Naval Officer. In my career, I commanded four Navy ships and an Amphibious Task Force. I also have ten years of shipboard engineering management and operations experience. I have deployed extensively across the globe, both within Carrier Strike Groups and as an independent deployer. Today, as an Executive for SparkCognition Government Systems (SGS), I’m working on solving complex national security challenges with SGS’ best-of-breed, full-spectrum AI technology. 

Contested logistics refers to the challenges that inevitably arise when moving supplies and personnel in a contested environment, such as during military operations in a hostile region. One of the primary challenges of contested logistics is the need to move supplies quickly and efficiently while keeping our personnel and vessels safe from enemy attacks. In the case of ship fuel, this challenge is particularly acute. Navy ships require large quantities of fuel to operate—especially capital assets such as nuclear and amphibious aircraft carriers for sustaining flight and carrier strike group operations and amphibious and expeditionary basing, respectively. In a contested environment, fuel delivery is an even higher-risk operation because enemy forces will target the supply lines in all domains transporting the fuel, making it difficult and dangerous to move fuel to the ships.

 To address these challenges, the US Navy should be aggressively exploring the use of AI to improve its logistics operations to maintain the effectiveness of joint forces, particularly when deploying more ships at higher operational tempo across vast operating areas. AI can optimize the movement of fuel and other supplies, making the process faster and more efficient. Here are some specific ways that AI can be used in the context of ship fuel:

1. Route Optimization: By analyzing data on fuel consumption, weather patterns, threat domain awareness, and other factors, AI algorithms can determine the most efficient route for transporting fuel to ships. This can reduce the time and cost of delivering fuel while minimizing the risk of attacks on supply lines.

2. Predictive Maintenance: As the Navy transitions to a more “digital” fleet, AI can be leveraged to improve the efficiency of ship fuel logistics and operations through predictive maintenance, especially as the Navy continues integrating ashore and afloat maintenance solutions with AI at the edge. By analyzing current and previous years of historical data from the ships’ engineering plant and shipboard replenishment equipment, AI algorithms can predict when maintenance is required on fuel service and support systems, allowing the Navy to optimize fuel usage and schedule maintenance operations in advance. This reduces fuel consumption rates and the risk of breakdowns that can delay fuel delivery.

3. Risk Assessment: By analyzing data on enemy forces, weather patterns, and other factors, AI algorithms can determine the likelihood of an attack on the supply lines. This will help the Navy make informed decisions about when and how to transport fuel, reducing the risk to personnel and equipment.

4. Inventory Management: By analyzing data on fuel consumption while also considering tactical requirements, AI algorithms can predict when supplies will run low, allowing the Navy to schedule resupply operations in advance. This helps ensure ships have enough fuel to operate, reducing the risk of delays or other issues.

5. Autonomous or Unmanned Refueling: By using autonomous or unmanned refueling vessels, much like the Navy’s MQ-25 Stingray, sensors, robotics, and other technologies, AI algorithms would allow ships to refuel with limited requirements for human intervention. This can reduce the risk to personnel during refueling operations while also improving the efficiency of the overall logistics process.

 The use of AI in military logistics, particularly in the context of ship fuel, can and will revolutionize how the US Navy operates. By optimizing routes, predicting maintenance needs, assessing risk, managing inventory, and enabling autonomous or unmanned refueling, AI can help make logistics operations faster, more efficient, and safer. 

As the Navy continues to explore using AI in its operations, we should expect to see continued improvements in logistics efficiency and effectiveness, making it more effective for the Navy to operate in contested environments.