Last updated on 06/03/2024
Artificial intelligence (AI) is rapidly transforming all industries. Aviation is no different, except that it has been an early adopter. AI planning and scheduling being one of the most promising applications. AI can be used to automate tasks, optimize schedules, and improve efficiency in a variety of ways.
A Birds-eye View of AI in Flight
Current Uses
Planning and scheduling is an incredibly common application of AI. There are few industries as defined by plans and schedules as the commercial flight industry. Here are a few of the things they rely on AI for:
- Fleet planning: optimizing the size and composition of aircraft fleets is critical for airlines to reduce costs and improve efficiency.
- Route planning: planning the most efficient routes for aircraft to fly reduces both fuel consumption and emissions.
- Flight scheduling: flight schedules can be crafted to minimize delays and cancellations. Careful planning also considers staging planes for flights on subsequent days, evening overall fleet-wear and improving the customer experience.
- Maintenance scheduling: Knowing when an aircraft has parts that will soon need service allows us to minimize unexpected downtime, improving the customer experience. It also improves safety and reliability while reducing the overall cost of maintaining the fleet.
- Crew scheduling: AI schedules flight crews to minimize fatigue the risk of crews ‘timing out’, and downtime during a shift. This can help to improve safety and productivity.
Benefits of AI
AI benefits aviation in several ways:
- Improved efficiency: AI planning and scheduling improves efficiency in several ways. Scheduling engine maintenance tasks in a large job shop reduces downtime. It can schedule crew without human intervention. This saves manhours and reduces the likelihood of a crew timing out on their last leg. AI can even help in seating passengers efficiently.
- Reduced costs: AI can help to reduce the costs of aircraft planning and scheduling. For example, AI can optimize the size and composition of fleets. This can lead to savings on fuel and maintenance costs.
- Improved safety: Better planning can improve safety, for example by reducing crew fatigue. AI can identify potential problems with flight schedules or maintenance plans. Once identified, these issues can be corrected with an eye towards safety.
- Increased customer satisfaction: AI can minimizing delays and cancellations. This improves the customer experience.
Challenges
The challenges of using AI for aircraft planning and scheduling:
- Data availability: AI models need large amounts of data to be effective. This can be a challenge in the aircraft industry, where data is often siloed and difficult to access.
- Complexity: AI models can be complex and difficult to understand and manage. This challenge extends to making sure they’re accurate and reliable.
- Bias: AI models can be biased, which can lead to unfair decisions. This is a particular concern in the aircraft industry, where safety is paramount.
The future of AI in aircraft planning and scheduling:
The future of AI in aircraft planning and scheduling is bright. We can expect to see even more ways to use AI to improve efficiency, safety, and customer satisfaction.
For example, we should expect to see our predictive capabilities improve. This is also true for weather, engine health, and consumer demand. Improvement in predictions would lead to improved planning capabilities. If our predictions are better, we need less margin in our plans. Needing less margin for error in plans leads to more efficient use of resources.
Unlike humans, these systems can continuously observe real-time data. Continuous monitoring and planning lets airlines react to changing circumstances. Without continuous monitoring, airlines would lack insight into changing situations. Without automated planning, it would be too expensive to react to changes.
Maintenance Planning and Predictive Maintenance:
AI can predict maintenance needs from components instrumented with sensors. AI can identify early signs of faults, often before humans can. By identifying faults early, we can perform maintenance when it is cheaper. Identifying faults earlier also lets us schedule maintenance for when it is convenient. It lets us stage replacement parts and craft ahead of time to avoid unscheduled downtime.
Predicting required maintenance also helps in scheduling. We can pick the most convenient times to service the craft. Or, we can schedule maintenance to reduce disruption or operational cost. Finally, early intervention extends the useful life of components.
Crew Scheduling and Resource Allocation:
AI can optimize crew schedules based on many factors, including:
- demand
- crew qualifications
- labor regulations
- rest requirements
- time zone changes
- shift rotations
- staging requirements
- Potential weather disruptions
Human planners must develop ‘rules of thumb’ and best practices to cope with the size of the planning problem. AI doesn’t tire or get bored, so it can, comically, ‘think outside the box’ by considering plans humans wouldn’t. The trick is in capturing mathematically what makes a schedule high quality. Eliciting scheduling constraints scoring rules is the hard part. Once you have the rules, planners and schedulers are relatively simple pieces of software.
These AI-driven optimizations in planning and scheduling increase the efficiency of airline operations. Aviation companies adopting AI should see better resource usage and customer satisfaction.