Digitalise baggage handling to improve airport efficiency

By Moritz Bender

 

The typical approach to efficiency in airports has been based on the idea that airport operations are steady states to which operators could apply efficiency initiatives to reduce waste over time. But we know that airport operations are anything but linear and in reality involve a lot of irregularities.

It’s not surprising, then, that we are starting to see a new phase of efficiency management evolving whereby what is needed to improve airport efficiency is actually the ability to predict irregularities and remove them before they even occur. With new technologies, such as AI and ML, airports are now able to predict those irregularities and tackle inefficiency from a new perspective. As such, data driven technologies are now essential to airport operations.

Predictive efficiency, however, does mean that airports, or for our purposes, BHS operators, have to have comprehensive knowledge of every aspect of the airport operation and this is where the concept of the digital twin becomes so important.

Digital twin: The airport’s new best friend

A digital twin is a digital replica or a digital overlay of the airport’s physical operation which many airports are already developing and using. Airports are using sensor technology and intelligent camera technology, for example, to build information repositories in order to gain better understanding of what’s going on in real time.

What does this mean for BHS operators? With a digital twin, BHS professionals can gain a full overview and understanding of how their actual system and processes look and function in the physical world and how different options and scenarios will likely impact OPEX costs.

Replicating operations in a digital environment means that BHS operators are able to plan BHS changes and broader transformations more effectively. It also means they are able to course correct operations, both in real time and for predictive purposes.

Leveraging airport big data to improve airport efficiency

Using digital twins to help drive airport operational efficiency is only possible by leveraging airport big data and using airport data analytics. In fact, a recent cost benefit analysis of three aspects of airport operations – data processing, automation and off-airport functions – showed that improved data processing is the key driver expected to deliver the most long-term economic value for airports.

Improved data processing is the key driver expected to deliver the most long-term economic value from so-called New Experience Travel Technologies, yielding approximately 71 percent of the overall benefits. Source: ACI / IATA.

For BHS professionals, leveraging the huge amount of airport data can provide valuable insights to help their organisational units make improvements that can reduce costs, reduce risks and increase capacity:

• Maintenance level: Data can be sourced from the equipment in real-time through sensors and devices and processed for the purposes of predictive maintenance, reducing cost and increasing efficiency.
• Operational level: Decision science improves the operation through the use of data driven recommendations for operational decisions – or even letting the system carry out decisions automatically.
• Management level: Dashboards can be customised and reports built on real-time data that management can rely on to forecast and plan, based on the historical data in combination with passenger forecasts (for example, are we able to cope with the summer peak this year, based on last year’s statistics and this summer’s forecast? – or how should we plan the staffing?).

More particularly, airport big data can be used to reduce BHS OPEX in these kind of ways:

• Data analytics can improve the efficiency of bag storage systems (EBS) – in one case, the analysis of data from the EBS delivered an 80 percent reduction of recirculations, while optimising the slot release time;
• The up-time and flow of Hold Baggage Screening (HBS) is constantly monitored on dashboards to continually improve and ensure optimal use of the area; and
• Data-driven asset management enables a leaner O&M staffing – in one case, data analytics led to a 50 percent decrease in time used on O&M, just by supporting the team with the right tools.

And as an added bonus, the digitisation of airports enables collaboration across entire airport operational systems.

Integratable, collaborative analytics platforms

Traditionally, airport operational systems were siloed and discretely working on their own efficiency measures. But by harnessing airport big data and using data-driven technologies, airports are increasingly able to work from a more holistic approach.

For example, the use of open software architectures in the BHS suite supports integration and allows for future integration of new software. With open integration, systems and data from multiple sources can be coordinated and integrated in a single user interface that enables virtual control rooms, collaboration from different locations and real-time operations. Integration and collaborative platforms also facilitate decision making, as the relevant people can participate with anything, from anywhere, at any time, optimising ground resources and improving efficiency.

 

Conclusion

There are a number of ways in which airports can improve their operational efficiency and reduce OPEX but digitalisation and use of data is undoubtedly the key driver expected to deliver the most long-term economic value. Through the development and use of digital twins, the use of data and especially data analytics and single BHS platforms that enable integration and collaboration across the entire system, airports have much to gain in enhancing efficiency.