Like many other sectors, aviation is having to deal with the challenges and opportunities that come with operating in an increasingly data-driven world. With the aid of sophisticated sensors and asset management tools, baggage handling systems and security screening machines now generate a huge amount of information about operational performance, throughput and stoppages. However, it can be a challenge to digest and interpret this data in a way that can be easily understood by decision-makers, who want to improve operations and create business value.
Senior management at one of our partner airports were in this position when they wanted to find a way of effectively assessing, analysing, describing and communicating the operational performance of their screening matrices.
A screening matrix is a systematic tool used to evaluate and prioritise the security screening of baggage, passengers and cargo. Given that the baggage handling system is a critical operational bottleneck, the screening matrix plays an essential role in streamlining processes and ensuring that global security standards are consistently met.
Several service providers were asked to recommend a way forward. However, even though all of them were using the same – if often incomplete – datasets, they generated different results when evaluating the performance of the screening matrices, particularly relating to availability.
Vanderlande’s extensive process engineering capabilities enabled the development of an alternative method for data analysis to address the challenge. Using hourly aggregated bag throughput data, its process engineers were able to generate temperature-based heatmaps to evaluate the availability of screening equipment.
A heatmap visualises data by using colour to represent the magnitude of values in a dataset. This allows for complex information to be displayed in cells with colours changing completely, or by hue and intensity. Heatmaps display complex information in a way which is easy to comprehend, and are now widely used in fields such as statistics, finance, web analytics and meteorology.
To build our heatmaps, we use three different data sources:
This data is harnessed to provide details about a system’s availability and how it is utilised. Availability refers to the probability of finding a system in an operable condition at a given time, and is calculated in part by using incident tickets generated by the control room operators and the security authorities.
Utilisation refers to the efficiency and effectiveness with which a system employs its assets to achieve specific objectives within a defined timeframe. Through our work, we developed and implemented a KPI for utilisation based on operational timeframes, which leverage hourly aggregated data and are enhanced with comprehensive heatmap visualisations.
The above is a heatmap showing the operation of a set of five screening machines over time. The Y-axis shows days of the month and the X-axis details hours of the day for each asset, going from zero to 23 hours. The colour-coded temperature threshold reveals activity from zero (dark blue) through to 350 bags per hour (strongest red). In addition, availability and utilisation are shown as percentages.
The information used to build the heatmap can also be displayed in different ways, for example in terms of comparing utilisation and availability, and the duration of events based on tickets (see illustration below).
One of the visually striking aspects of using heatmaps is their ability to provide an at-a-glance view of operational activity. For example, in the illustration below, “cold spots” for screening machine number four can be clearly seen in blue, showing when and for how long the asset is not available.
As every communication between the security authorities and the control room is recorded, it is possible to correlate every raised ticket to every anomaly in the screening machine. Such comprehensive information allows the airport to identify bottlenecks in screening activities that can affect flight punctuality.
In addition, since information relating to asset availability and utilisation is automatically recorded, there is no chance of human error. As the heatmap model was being established, some misreporting was revealed in the communications between the security authorities and the control room, as well as a lack of reporting about non-operational hours.
The airport is delighted with the heatmap model, which is now a fundamental component of its weekly, monthly, quarterly and yearly operational reviews.
Following the successful implementation of heatmap analysis with the screening matrices, the method was applied to two more areas of airport operations: contingency lines and sort piers.
The contingency line case study looked at the airport’s ticket counter operations. The heatmaps produced show how a number of counters were being used over time. The illustration below indicates how counter number 4 is used as a contingency when number 3 is out of use.
We have even found ways of using this data for a simulation tool. For example, bags can be added to the model and then an assessment made to show how ticket counters are affected by peak flows in the system. Furthermore, it improves tracking of disruptions and the management of stakeholder interdependencies during such events.
Contingency can also be seen in the illustration below, where L1 baggage transfer line shows three distinct cold spots. Across the same timeframe, L2 show darkest red as it handles bags from L1, as well as its own allocation.
A sort pier is a designated area where luggage is directed to the appropriate conveyor belt or transport system. Sort piers are typically equipped with advanced technology, such as barcode scanners and automated sorting systems, to efficiently manage and route the luggage.
As the airport team was pleased with the heatmaps provided for screening services, it asked for their use to be extended to show how sort piers and carousels were being utilised, especially during peak hours. These heatmaps were based on aggregated sort pier throughput to provide a visual representation of baggage flows.
The objective was to improve bag distribution and optimise the allocation of resources during busy periods. Using the results, the airport has been able to do just that by transferring bags from one sort pier to another and balance loads more accurately.
In addition, by digging more deeply into the data, it is possible to spot trends, such as the frequency of alarms triggered at the sort piers due to high throughputs. These details also help managers to allocate resources and personnel more efficiently to deal with upcoming peak volumes.
This heatmap model is being used in regular operational reviews by the airport.
The heatmap models provide the airport – and our local team – with a straightforward and visually intuitive representation of operational performance. The value of using real-time data means that the model can be updated and presented to the airport and other stakeholders on a weekly basis. It has been used to show operational performance to the senior management team, and can be exploited to help plan activities.
Such is the confidence in the model’s robustness that it has been presented to the relevant security authorities. They in turn are using it to improve their asset management activities and operational performance, for example by changing machine calibration schedules to avoid bottlenecks. The results can also be used to allocate resources more effectively, including personnel.
In addition, for the sort pier model, the airport is planning to discuss the findings with airlines with a view to relocating some operations to take advantage of underused assets in various areas of the airport.
There is potential to use heatmaps and related data to help build effective forecasting tools. By analysing historical data, seasonal trends, and external factors – such as holidays or events – predictive models will allow airports to:
• gauge and prepare for future baggage volumes
• adjust workforce schedules to cover peak times
• and ready contingency screening lanes for upcoming busy periods.
In the future, it will also be possible to use sophisticated machine-learning algorithms that can exploit data patterns to further improve resource allocation and operational performance. Airports that use predictive analytics can expect to improve efficiency, setting them apart from the competition.
The insights gained from using heatmaps, along with data about availability and utilisation, offer significant value to airports and stakeholders who want to optimise the performance of their screening and baggage handling operations.
Heatmaps provide a visual way to identify both low and high levels of activity. This information can then be used by an airport to change staffing levels and deploy resources more effectively to meet fluctuating demand for services. In addition, engineering teams can schedule maintenance for quieter periods, thereby minimising disruptions to operations.
Furthermore, understanding the distribution of baggage throughput across different times will allow airports to streamline processes, reduce bottlenecks and plan contingency routes to cover unexpected shutdowns.
By harnessing data from heatmaps, airports can also adjust how screening machines and baggage systems are used to balance their workloads. This ensures equipment is neither over nor underused.
There are commercial advantages to be gained from using and exploiting reliable sources of data. For example, by helping authorities deploy security staff more effectively, they can save on overtime costs.
Handler teams can also be moved to where they are needed as information about baggage volume trends is made available via the heatmap model. In addition, the sort pier heatmaps make it easier for baggage handling teams to identify times when bags accumulate, giving them opportunities to prevent pile-ups.
In general terms, the models we’ve produced demonstrate the value of embracing a data-driven culture in which decision-making is backed up by solid analysis. Embracing these innovative solutions is also an effective way to show investors that an airport operator is committed to exploiting advanced technologies to improve performance.
Contact us to find out more about our data-driven service tools and solutions