Crystal Ball

Fast-Time Simulation Helps Airlines Produce Various Scenarios To Solve Complex Problems

Fast-time simulation, a method for generating a variety of what-if scenarios to address specific business problems, can be completed in minimal time, enabling airlines to make quicker, smarter decisions. This sound method not only works in present time but also gives airlines a clear view of the future so they can make strategic adjustments across their business.

Wouldn’t it be great if every airline had a crystal ball that allowed it to see the future and avoid situations that deplete company resources? Having enough insight to make accurate forecasts is a challenge, but there are proven methods airlines can use to achieve optimal results without the crystal ball.

The airline business is complex with different feedback cycles (current activities that impact those in the future), dependencies and networks (planes, crews, passengers, etc.) interacting between and among each other.

One of the simplest examples of feedback in action is the routing of a single airplane, which has a set of routes to fly during a given day. The performance of the second flight depends on the first flight’s performance. And the third flight’s performance depends on those of the first two flights and so on.

Therefore, if an unexpected event disrupts one of the day’s earlier flights, the airline’s entire schedule may eventually be impacted. An airline needs tools to gain insight into these complex dynamics and interactions to minimize the effect of a single disruption on not only the remaining day’s flights scheduled for that particular aircraft but the network, as well.

Fast-time simulation is a decision-support tool that models, visualizes, quantifies and provides insights about extremely complex systems such as an airline’s network, aircraft boarding process, delay propagation, air traffic management, etc. The idea behind fast-time simulation is the creation of a model that represents the current state and then simulates how this model behaves when changes to the simulation model occur.

Simulation Of Airport Ramp Space And Runways

In as little as 25 minutes, fast-time simulation software can run an entire day of operations. Simulation of ramp space around airports, runways and airspace is the most common use of the practice.

To understand the impact associated with these changes, the variables of the model can be altered. Fast-time simulation typically takes a fraction of the time because it is performed in an accelerated way; hence the name.

For example, some simulation software can run an entire day of operations in 25 minutes. This permits airline managers and modelers to run different what-if scenarios to find the best solution for a problem, improve business processes, increase throughput or eliminate capacity constraints that produce waste. More importantly, users of the model and those expecting insights from the model can address tactical or strategic issues such as:

  • Tactical issues:
    • Analyzing a runway closure and the impact to an airline’s operation for a specific hub,
    • Exploring the impact of a new and longer security process at a particular airport.
  • Strategic issues:
    • Modeling terminal capacity (determining how many passengers can be handled at a specific airport in the future) using a five- to 10-year plan. As part of the modeling, an airline may discover that the terminal will not be able to manage the expected growth. This will drive discussions around either adding capacity or reducing growth.
    • The same concept can be applied when exploring the addition of a new runway or changing an air-traffic-control process.

Fast-time simulation is used in different areas within the aviation industry. One of the most common practices is the simulation of airspace, runways and ramp space around airports. Airlines and airports use these simulation models to visualize potential bottlenecks or delays, avoid trial and error when implementing initiatives, or unlock capacity constraints. This supports the decision-making process related to current situations or for planning purposes.

Other processes modeled by airlines include airport check-in, security checkpoint, aircraft boarding, passenger flow as well as congestion patterns in terminals and gates and tarmac movement involved with tugging airplanes versus taxiing them. Simulation can also replicate reservations call center operations to introduce new ways to enhance customer service, reduce costs or increase the throughput of the call center. The benefits translate into revenue increases and/or cost reductions.

Revenue gains are possible if the simulation model shows ways to increase throughput or productivity of current resources, such as gates, check-in facilities, runways, ground-support equipment, employees, etc.

The Power Of Simulation

Prior to building a new terminal, Sabre Airline Solutions® and TransSolutions ran a simulation model for an airline, which identified that the number of security lines planned for the new terminal were insufficient. This enabled the airline to correct the design, saving a significant amount of time and money.

For example, the simulation can highlight capacity constraints. If capacity constraints are solved by adding capacity or changing processes, the scheduling department can add to or adjust the schedule because now more flights can be processed, resulting in increased revenue.

On the cost-reduction side, the simulation provides insights into ways to reduce delays, such as taxi-out delays. By minimizing delays, the airline may experience a reduction in fuel burn.

The super-tug simulation model also provides a good example of a possible cost-reduction initiative resulting from the simulation. Airlines use super tugs (fast tug trucks typically without tow bars) to move airplanes from gate to gate, gate to maintenance stands or gate to remote stands instead of taxiing them with their own power. A simulation model can help airlines decide if purchasing the tugs is justified. Or if the super tugs are already included in the fleet, the model will help determine if it is possible to increase their productivity while quantifying the fuel-burn savings associated with towing the plane versus taxiing it.

Additionally, the simulation model can incorporate all the operational constrains and environmental features of an airport, providing better visibility and representation of the situation. This is all achieved without running expensive experiments or observations.

In one instance, the operations consulting team for Sabre Airline Solutions® used fast-time simulation to help an airline determine if a planned facility was adequate to handle passenger volumes now and five years in the future. A baseline model was built and validated, which was crucial because the model had to replicate the current reality.

This specific model required different parameters and data sets, which were input into a special simulation tool for building and testing the model. These sophisticated tools can track key performance indicators (KPIs) that allow the modeler to compare and place values on the various scenarios.

The airline, in this case, was able to identify and gain insight about several problems before implementing the new facility, which allowed it to address these issues during the planning phase prior to implementation. By identifying these problems in advance, the carrier avoided the impact to a subsequent process down line such as transporting the crew to the plane, which, in turn, might affect the on-time departure of its flights.

Simulation Reduces Costs

Rather than taxiing aircraft using their own power, airlines use super tugs to move aircraft, reducing taxi-out delays and saving fuel. Using a fast-time simulation model, airlines can better determine if they should buy tugs or, if they already have them, increase the productivity of the current fleet.

From a strategic point of view, fast-time simulation can help identify where and when additional capacity is needed. For instance, airports are fundamental components of an airline’s production chain; however, airlines do not control airports. Therefore, airports might affect how airlines deliver their products to their passengers. Airports often have a set of objectives that are completely different from those pursued by airlines.

Therefore, airlines surrender half of their production processes (at least the flight portion) to government and quasi-governmental agencies and city or private organizations around the world, such as Heathrow Airport Holdings (formerly British Airport Authority). Airlines can benefit from fast-time simulation because the results from various scenarios can help influence airport owners and authorities to take any number of actions such as adding capacity in the check-in processes or baggage handling systems. Based on simulations results, airlines and airports can work together to find a solution that satisfies all parties.

Fast-time simulation can also be used in a less-strategic, but no less relevant, fashion. During the planning phase, for example, an airline may run a new preliminary schedule in a simulation tool to identify potential problems before they actually impact its operation. The resulting feedback is given to the scheduling department to make the necessary adjustments to the schedule to avoid service disruptions.

This is particularly valuable in a hub-and-spoke operation because it provides visibility about the embedded inefficiencies associated with this type of operation. This is a better approach to understanding the future operational environment than simply using historical data to forecast the future. The historical data is based on statistical analysis, so it does not have the same level of granularity offered by the simulation.

Delay Avoidance

Turn performance can affect departure performance; therefore, delays can be propagated for subsequent flights. Fast-time simulation can identify routings or flights prone to causing delays before they operate, giving airlines an opportunity to make necessary adjustments and avoid down-line delays.

For example, having an average taxi out time is good, but understanding what is driving the taxi out time is more meaningful.

Building a viable simulation model requires the construction of a solid framework, which includes several steps:

  1. Data collection and variables definitions — To understand which data is needed, the modeler needs to understand the type of model that will be simulated. Therefore, the variables included in the model should also be defined in this step. In addition, the modeler must consider which KPIs are important for the business, such as fuel burn, passenger waiting time, resource utilization and costs. Relevant data may be collected from a variety of sources and will generally include flight schedules, resource or passenger behaviors (processing times, arrival curves, etc.); as well as the physical layout of the involved facilities (airport or terminal layout, check-in area, etc.). Sometimes the data is not available, and time and motion studies are necessary to collect it.
  2. Model construction — Once the data is collected, the simulation model can be built. Different applications are available in the market place based on the processes to be simulated. Software, such as Arena Simulation Software by Rockwell Automation, simulates general business processes specific to aviation.
  3. Model Validation — Once the model is built, it should be validated against reality. This step is necessary to establish a baseline for comparison purposes. An incorrect or inaccurate baseline will drive negative, unusable results.
  4. Scenario runs — Scenarios are run based on the alternatives an airline is assessing. Typically, the creation of different scenarios results from changing variables in the model and running multiple simulations to understand the impact of these changes. Scenarios can be defined prior to building the simulation model. Typically, simulation models are built to answer questions to certain scenarios.
  5. Reports — When the simulation is complete, reports are generated detailing the respective impact on tracked KPIs, enabling managers to understand the impact of each alternative. In many cases, results can be displayed visually, which is generally more powerful than plain text and allows issues to be highlighted at different levels. Visual displays enable managers to see how resources or passengers congregate or behave in a process.

There are risks associated with fast-time simulations. For example, a simulation model will be as good as the methodology used to build the model. The largest risk is that the baseline model does not reflect the current state. Therefore, wrong conclusions can be drawn when the model is used to analyze different scenarios. Therefore, solid data collection, sound modeling and expert analysis can overcome these risks.

When an airline is uncertain about the impact of a proposed new program on its operation, or if it wants to identify ways to optimize its operation and increase revenue or reduce costs, fast-time simulation is a powerful tool. In fact, it may be as good as a crystal ball after all.

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