Embracing automation not only allows airports and airlines to optimise their labour resources, but also enables them to increase their overall operational efficiency. This way, baggage handling operations can improve their capacity to deal with growing demand and deliver a seamless passenger experience.
This white paper serves as a guide for the aviation industry to navigate the current workforce challenges and paves the way for future-ready and efficient baggage handling operations.
The main takeaways of this white paper are as follows:
Airports and airlines are confronted with various challenges as they navigate through the post-COVID world, which has seen demand return to pre-pandemic levels. Environmental concerns, health, safety as well as the persistent cost pressure of minimising operational expenses are among the key challenges. The recent surge in mishandled bags1 further complicates efforts to meet passenger expectations for a seamless experience, especially with the anticipated growth in the number of bags2. Amidst these complexities, the shortage of personnel presents a significant challenge to the aviation sector.
In response to these pressing issues, Vanderlande presents Baggage 4.0. This is our vision for the next generation of baggage handling, aligning with the principles of Industry 4.0. By leveraging cutting-edge technologies and processes – such as the Internet of Things (IoT), cloud computing, robotics and artificial intelligence (AI) – Baggage 4.0 can deliver highly automated and predictable baggage handling operations. It‘s a holistic response to industry challenges, capable of carrying out complex tasks and enabling increasing interconnectivity and smart automation.
In our vision of Baggage 4.0, we foresee a paradigm shift in baggage handling, moving beyond a conventional system of conveyors and sorters. Instead, it transforms into an adaptive and smart entity that seamlessly integrates systems and processes. Through an optimal integration of digital solutions, services and smart automation, we can enhance the baggage flow, ensuring seamless collaboration among systems and processes, driven by data-centric decision-making.
Automation is no longer limited to the BHS itself: the vision is to achieve nearly autonomous baggage operations. Manual tasks will be significantly reduced by implementing advanced robotics and autonomous vehicles (AVs). Consequently, the role of the operator will transition from one that requires physical labour to a supervisory position, through which they will oversee and optimise the automated processes.
Baggage 4.0 introduces a new level of predictive capability in which machines are empowered to make real-time decisions based on comprehensive data. This transformative approach allows us to anticipate anomalies and proactively address them, ensuring smooth operations and minimising disruptions. The result is an advanced and highly automated operation that not only meets the demands of a rapidly evolving industry but also embraces sustainability as a guiding principle by improving working conditions and optimising the use of resources.
With incremental steps already being taken towards its realisation, this white paper explores the role of automation within Baggage 4.0 to address one of the industry‘s most pressing challenges: labour scarcity. With a focus on smart automation within the baggage hall, airports can improve working conditions by reducing the manual lifting of bags while achieving higher volumes with the same workforce for an increased overall operational efficiency. This will serve as a foundational step towards building the future of baggage handling.
It is important to note that regional disparities may require tailored approaches to implement handler automation solutions to suit unique contexts.
Emerging from the pandemic, the aviation industry is confronted with an extraordinary labour shortage3. This is not limited to the aviation sector but is part of a broader global trend across multiple industries4: 75% of companies in OECD countries reported shortages of talent in 2022, a notable increase from 54% in 20195. (The Organisation for Economic Cooperation and Development has 38 member countries, the majority of which have relatively wealthy economies and advanced infrastructures). The global trend of labour scarcity can be attributed to several factors, including demographic changes as well as shifting priorities and expectations in the workplace3,6.
While these factors have implications across various industries, a more detailed assessment is required to effectively understand the aviation sector‘s unique and complex situation in relation to this challenge.
Post-COVID (end of 2021), a total of 2.3 million fewer jobs were supported in the global aviation industry, a reduction of 21% compared to pre-COVID levels7. The pandemic-induced uncertainties and operational disruptions have not only resulted in job losses, but have also diminished the industry‘s image as an attractive and stable employer. As a result, many employees who left the aviation sector during the pandemic are hesitant to return3.
Additionally, lower-skilled workers often perceive airport jobs as demanding and stressful, with pay levels that may not adequately reflect the responsibilities they bear3. This is particularly true for ground handlers, whose daily tasks can be physically taxing.
With a growing emphasis on health and safety in the workplace, there is a heightened awareness of the need to implement improved processes and practices within the baggage hall to safeguard the wellbeing of operators by minimising the manual lifting of bags. Amidst these concerns, multiple European national workplace regulators advocate for the adoption of mechanised loading methods to mitigate health risks for handlers8,9.
All these factors, along with the ageing population and the projected growth in passenger demand2, highlight the importance of developing strategies to address the labour shortage in the long term.
To navigate this challenging landscape, airports and other aviation stakeholders must explore new approaches as a response to the labour scarcity. This white paper aims to explore potential strategies and solutions to address the shortage of workers in the aviation industry, with a focus on the baggage hall. It will examine the role of automation and technological innovations in optimising the use of labour, enhance operational efficiency and ensure a sustainable workforce.
Starting with the essentials, this chapter focuses on the BHS, its evolution over time, and which technology can be implemented to increase automation and alleviate labour demands.
Let’s first have a look how BHS have evolved over time in relation to using manual labour. Initial systems included little automation. Simple conveyor belts were applied to collect bags at the check-in desks and transported them to a run-out or carousel in the baggage hall. Here, handlers manually lifted and sorted the bags based on the destination described by the baggage label, which was printed at check-in.
With the rise of PLCs, barcode scanners and sortation loops – such as tilt-tray sorters in the 1980s – it became possible to automatically sort bags to a chute, lateral or carousel based on the flight destination or class. This enabled handlers to work more efficiently and also reduced the chance of missorts. Also, bags from transfer passengers didn’t need to be handled manually anymore, but could instead be automatically sorted to the make-up positions.
From the 1990s onwards, early bag storage systems were gradually introduced. These systems collect early checked bags, or bags from passengers with long flight transfer connections, and store them on lanes or in racks before releasing them a few hours before departure. This increased efficiency as the handler was only needed a few hours before the flight departure to load the bags into containers or carts, instead of being present during the complete check-in opening time to receive bags. Working conditions at the BHS loading and unloading stations remain a concern, although they can be improved using lifting aids.
The more recent implementation of individual carrier systems (ICS) realised – along with many operational and maintenance benefits – a higher level of baggage conveyability. Fewer bags get trapped in machinery, thereby reducing the need for so-called “bag jammers”.
Without looking at the automation of adjacent handling processes, such as loading and unloading, does the current state-of-the-art BHS still offer opportunities to use labour more efficiently? We believe so, especially when we look at specific processes. A few examples follow.
Image: Individual Carrier System (ICS)
By increasing the level of self-service at the bag drop – for instance giving passengers the option to load their own bags directly into an ICS carrier – the same number of staff can oversee more check-in and bag-drop stations. With solutions such as the concept shown here, the passenger is now responsible for correctly loading the bag into the carrier as well as its proper identification. This not only alleviates the need for manual labour at the load correction and manual coding stations, but also uses all the advantages of ICS from the moment of bag induction. Benefits include full tracking and tracing, low jam rates, and best maintainability of equipment, which also helps airports deploy their handling staff as effectively as possible
Image: Concept of Self-Service Bag Drop solution DROP@EASE
An improved, more dynamic planning of make-up positions, which is based on the actual (expected) baggage demand rather than a fixed period of time, enables a reduction of time for make-up. This in turn means that the same handlers can effectively oversee a greater number of make-up positions.
Image: Lateral planning
Many (heavy) labour tasks can be reduced by handling exceptional flows, such as oversized or manual inspection bags, with AVs. The demand and characteristics of out-of-gauge (OOG) and odd-sized bags are typically such that an investment in a fixed conveyor system is not easily justified. With high flexibility and a low amount of fixed infrastructure, AV technology provides an ideal solution for dealing with these secondary and exceptional process flows.
Mobile infrastructure can free up space – typically occupied by large, fixed infrastructure – and offers operational resilience on a reduced footprint. AV technology is able to use existing driving routes for transport and can handle a group of bulky bags by using dedicated cages. Examples of use include transport from check-in counters to screening and buffering areas, and from the screening area to the make-up area.
Image: Concept of automated transport of oversize bags with AVs
OOG and odd-sized bags may be handled in cages that are either flight specific or managed per time window. Recently a total cost of ownership (TCO) calculation (see graph) was carried out comparing this concept with a manual operation for a large airport. Although the AV operation required investment in vehicles and software updates, an overall saving of 30% on (mainly) labour cost was achieved during a ten-year period, mainly because handlers did not need to spend time on transport tasks.
In essence, the incorporation of AV technology to automate secondary and exceptional flows, such as dealing with OOG or odd-sized bags, not only frees up handlers to do other tasks, but also improves working conditions. The handler‘s role involves less manual lifting and shifts to more supervision.
Graph: 10-Year TCO Comparison – Conventional vs. AV Handling for OOG and Odd-Sized Bags
During the last decade, the batching or pull process has attracted significant interest. This is because it efficiently optimises both the use of handler staff and precious make-up space, while improving predictability of the baggage handling process.
Batching refers to the process of sorting and storing items in groups or batches based on specific criteria. Bags are organised and prioritised according to departure times, flight schedules, segregation class and other relevant factors. Instead of individually handling each bag, they are consolidated into batches in storage before being loaded into containers or carts.
Unlike the conventional „push“ approach, where bags are continuously pushed forward (and for which the make-up open time can be slightly reduced with an early bag storage), batching operates on a „pull“ approach. Operators have the ability to decide when to initiate the process, allowing all the bags for a particular flight (or class) to be pulled from a bag store and prepared for make-up whenever handling resources are available. The utilisation of this approach enables a smoother and more efficient baggage flow. Note that we use ‘bagstore’ rather than ‘early bag storage’ (EBS) as in the pull process not only early bags but also bags with less time to departure are processed through the store.
With a batching process in place there is still a short period during which the last bags are loaded in a conventional way. This final part of the make-up process is called “compressed build”. However, the total loading time is much lower, as can be seen in the example image below. This shows that loading time is reduced from three hours per flight to approximately 1.5 hours through the use of batching. That way the same number of handlers are able to operate more make-up positions.
Additionally, with a batching process in place, the baggage flow into the batch-build area becomes more constant and predictable, which facilitates the automation of the loading process.
Batching can be achieved in different ways and with varied levels of infrastructure and complexity. It can be performed with simple lane-based storage, where luggage for different flights is sorted into separate lanes. These are then released to initiate the make-up process.
However, in order to fully harness the maximum benefits of batching, a storage with an individual bag retrieval system should be considered. This would grant the operator greater control over the process and achieve a higher filling level for container loading.
For example, with lane storage, it is not possible to retrieve bags in a specific order within the batch. With a rack-based bag store – that includes cranes or shuttles for the individual storage and retrieval of bags – it is feasible to strategically dispatch bags based on weight and sturdiness, prioritising heavy, hardcase bags first and placing soft, light bags at the end. To further enhance efficiency and ergonomic handling, automating the loading process through robotic solutions – or other methods that minimise physical tasks – can be implemented, leveraged by the strategic selection and retrieval of bags.
A limitation of the current batching logic is that it sends by default a batch of 30+ bags to load a full container or cart. With this threshold, many bags remain unbatched in the bag store as there will always be leftovers for flights/segregations that do not count up to 30+ and that will be sent to the traditional (manual) make-up process. The result is that today a maximum level of around 50-60% of the volume being batched is typical.
Based on lessons learnt from the current operational batch build processes, even more efficient use of labour can be achieved by “smart batching”. This includes a number of additional algorithms and configurations to increase the volume of batched bags.
The effectiveness of alternative batching algorithms was investigated using a simulation model in which flight schedules of two big international airports of different sizes and with different bag segregation levels were analysed.
The following three methods were investigated for their ability to increase the share of batched bags.
Hybrid storage
The figure below illustrates the flow of bags through storage with the current storage concept – all (early) bags are stored in rack storage. Batches are built out of the rack storage and sent to a lane buffer (often in line with a batching station “in-cache buffer”) for consolidation before the batch is built.
The next figure illustrates the flow of bags through the BHS with the hybrid storage concept. Early, not time-sensitive “cold” bags, are sent to rack storage and “warm”, more time-sensitive bags, are sent to lane storage. Green arrows indicate changes from the current storage concept. Batches are built out of both the rack and lane storage. Since the rack storage can be far from the batching output, batches in this concept are also consolidated closer to the batching output in the lane storage. Once consolidated, batches are sent for building at a batching output.
In both storage concepts, bags that enter the system once their flight’s make-up opens are sent directly to a make-up output. Bags that are in storage when their flight’s make-up opens are also sent directly to the same place.
The table below summarises the functionalities of the rack and lane storage in the two storage concepts.
By introducing a hybrid storage concept, we can make the batching process more dynamic and more efficient. This is mainly beneficial for the warm bags that are now buffered closer to make-up, and of which more can now also be batch loaded.
Make-up open time reduction
In a conventional process, make-up (MU) opens between two and three hours before a flight’s scheduled time of departure (STD). With batching, the remaining make-up open time can be shortened to, for instance, 90 minutes before the STD (compressed build). We examined moving the make-up open time from STD-90 minutes to STD-20 minutes. These two scenarios are summarised in the timeline below. By shortening the make-up opening time, we increase the time and therefore the volume of bags being consolidated in batches before the make-up position opens.
Variable batch sizing
In a conventional batching process bags are only sent when a “full” batch can be built. With the variable batch sizing algorithm, partial batches (< 30 bags) are also sent for loading approximately 10 minutes before make-up opens. This timing is indicated by the blue boxes on the timelines below. Building a partial batch can leave a halffilled container. These containers can be filled with checked-in bags while make-up is open, which means these half-empty containers may be moved to the make-up output. With variable batch sizing, more bags are handled through the batching process.
From the results of this analysis – with the combination of all three proposed measures – it was revealed that a significant increase in batched bags was possible to approximately 70-90%, for both airports. For airport 2, the increase was slightly greater than for airport 1, because of the bag arrival pattern (the bag dwell profile) and the fact that there are fewer segregations per flight.
With the new algorithms, relatively more bags will become part of a batch for the smaller airport 2, which also sees more bags batched by passing via the lane storage only.
The increase in batching volume means that a larger part of the flight can be loaded at a constant, predictable level, which means that the total loading time per flight is lower. In the analysis above, the average number of batches per flight for airport 2 increased from two to five batches on average. If we consider 15 minutes (manual) loading time per batch, we can see in the table below that the extra time for batch loading is offset by the larger reduction in compressed build time.
In conclusion, the proposed methods for smart batching can increase the volume of batch building to 88% and therefore reduce the handling time by around 20-30%, allowing for a more efficient use of the handler staff.
Further methods to increase the share of batching include: batch from anywhere (bags not passing through a cold or warm bag store); predictive batching (e.g. building smaller batches if no more bags are expected based on all bag data available or historical patterns); and combining smaller segregations into one batch just before make-up open time.
In the next chapter we will further examine ways to automate the handler processes.
The next step in solving labour scarcity can be found in automating handler processes, such as loading, unloading, transport, buffering and management of (empty) load units within the baggage hall. A load unit can be a container or a cart. The scope of these processes is mapped in the image below on the end-to-end process for baggage. The result is a facility that processes bags in a highly automated way – what we refer to as part of our Baggage 4.0 approach.
Due to the variable arrival patterns of aircraft and local passengers, baggage demand often varies significantly during the day. As described in the previous chapter, by applying the automated buffering of batches in a bag store, the (smart) batching process leads to a more consistent and predictable flow. Such a constant flow enables further automation and can justify an investment in a semi- or fully automated loading process.
The urgent need to mechanise the loading process became for example apparent during a European Labour Inspectorate’s recent assessment of the baggage handling processes at a European transfer hub airport. While current regulations indicate that one person should handle a maximum of 216 bags per day, it appears that during busy days a handler may need to lift up to this amount of bags per hour.
Several make-up devices are available for mechanising the loading process, ranging from simple lifting aids to fully automated robotic solutions. With a higher level of automation, a person’s role changes from a pure handling to a supervisory position, which would only involve lifting bags in exceptional circumstances. Some technologies are suitable for a batching (pull) process, while other devices are best applied in a push process, for instance during the normal (compressed) make-up process. The figure shows how the loading devices are plotted in relation to these two views.
The highest automation level is achieved with robotic loading that, for instance, has been operational for many years at Amsterdam Schiphol and London Heathrow. Based on evolutionary developments in technology, robotic loading is now ready for a significant upgrade. This new generation of robots will likely double operational capacity, with one supervisor overseeing multiple robots.
The four new technologies being incorporated into next generation robotics are highlighted below.
The high productivity of the robotic build cell (which integrates the robot with the baggage feed lines, controls and a supervisor workstation) also requires the rapid replenishment of empty load units (LUs) and takeaway of full load units to and from the cell. In general, the airport will need an operational plan for the management, movement, storage and retrieval of LUs. This is where the automated handling of LUs comes into play, which can be realised either by conveyors (originating from the air cargo industry) or AVs. The latter can store the load units in a decentralised way, which uses space more efficiently.
When considering AVs for the container handling process, the same benefits regarding flexibility apply that are applicable to individual bag AVs (compared to belt conveyor systems). AVs can be rapidly deployed, and it is easier to carry out upgrades in the future. A system based on AVs offers higher flexibility and better scalability.
Image: Automated transport and storage of LU‘s using AV technology (FLEET Batch)
It can also be tailored to actual demand without the unnecessary installation of extra capacity for redundancy, unbalanced flows, and temporary or unpredictable future demand. Greater efficiency in the use of space can be achieved if the AV is capable of storing LUs at height, which is possible with the automated forklift technology commonly applied in warehouse automation.
The LU processes for bulk (non-containerised) aircraft can also be automated by introducing an airport container (or airport load device – ALD). In this way, all manual driving can be removed from the baggage hall for increased safety and the avoidance of any potential building damage. An interface with apron vehicles is foreseen, through which containers are (automatically) transferred between the baggage hall and the dolly transport to and from the aircraft stands.
Image: Airport Load Device (ALD)
A key element in our Baggage 4.0 concept is the automated buffering of LUs for empty and outbound baggage. Buffering LUs also enables peak shaving of inbound baggage unloading. For instance, by storing inbound LUs with cold transfer bags (those with connection times of multiple hours, which are segregated at the originating airport in a separate container), the unloading capacity can be better utilised and an investment in automated unloading (container “tippers”) may be justified. In addition, by automating the unloading of containers, the work of handlers shifts from continuous heavy and awkward lifting and pulling bags to a mainly supervisory role at the automatic unloading stations.
By integrating handler processes with the BHS, the power of an end-to-end system is harnessed, contributing to a more reliable baggage handling process. For instance, by taking the flows in the BHS into account, the correct unloader station may be selected for inbound baggage. This balances the baggage flows over the available capacity and minimises waiting times for time-critical, “hot” transfer baggage.
With all the measures mentioned above, both in the core BHS and handler processes, manual staff will still be needed in the Baggage 4.0 concept for tasks such as:
Overall, within the baggage 4.0 concept, the manual lifting of baggage is tremendously reduced. The process will be more automated, creating a healthier and safer work environment. The handler‘s role shifts from physical baggage handling to more supervisory and coordinating tasks.
In a case study, we determined how many people are needed to operate the automated baggage hall, compared to a conventional approach. In this example, full automation includes all solutions described earlier, from improvements in the core BHS and smart batching principles, to the automation of handler processes within the baggage hall.
With the fully automated solution, we eliminate heavy manual lifting and instead introduce people who operate a mechanised solution. In the table below we show the number of operators needed per mechanisation process. We chose to calculate the number of operators required per eight full-time hours of work. In total we need 12 operators per eight full-time hours of work for the automated solution. Considering typical operational working hours and peak patterns throughout a seven-day working week, we need a total of 30 operators on average per day to operate the fully automated solution.
The solution eliminates all heavy manual labour and reduces the number of people needed by ± 60% compared to a conventional solution, and by ± 35-50% compared to a semi-automated solution that uses speedloaders rather than robotic loading. This implies that with the same workforce, around 150% of the volume can be handled compared to a conventional operation. People required for maintenance are not included in our analysis as we expect that number will be similar for all three scenarios. However, the automated solutions may require maintenance personnel to adopt a different skillset.
What are the main attention points to be taken into account when considering the automation of handler processes? Can the Baggage 4.0 concept work for every size of airport, how does it impact operations and what are the infrastructure requirements?
Traditionally, a batching process is mainly of interest to the large hub airports that have a high level of transfer baggage with long dwell profiles and early checked-in bags for long-haul flights. This would generate sufficient bags to create a significant amount of early batch build load units. However, what we also see at the big airports is a high level of segregations per flight, which has a limiting effect on batch build.
As we have seen, with extended batch build time and sending bags directly from input to the batch build station, we can significantly increase batching and therefore enable automated loading. This is not only the case for large hub airports, but also for slightly smaller (international) airports that already have the benefit of seeing less segregations per flight.
These airports have a higher share of loose-loaded (bulk) flights or hardly handle ULDs at all. With the introduction of an airport container or ALD, it becomes also interesting to automate the processes for these loose-loaded flights in the baggage hall in the same way as we intend to do for containerised flights.
A project for the full-scale automation of baggage operations cannot be introduced overnight. It should be implemented step by step, starting with proof of concepts and simple use cases, involving all stakeholders from the airport, airline and handler community. While gradually increasing the level of automation, there will always be part of the volume that needs to be handled in a specialised way with some manual effort. This could involve flows, such as time-critical bags, exceptional handling, and oversized/live-animals/odd-sized bags, typically accounting for less than 10% of the bag volume and that can be supported with lifting tools to reduce the impact on labour.
For the majority of the volume, how do we combine flexibility with a high level of automation – two requirements that traditionally seem to be in contradiction? Buffers play a role here, because they can create a more consistent flow that is suitable for automation. In addition, AV technology delivers benefits by creating smaller pieces of capacity to reduce the impact of a failure, while approaching the resilience, flexibility and scalability of a manual operation. Certain AVs also allow for manual operation as a contingency measure.
By applying buffers in the system we create peak shaving, which means that infrastructure does not need to be designed for a few single peaks during the day or year. We also see a shift in a smarter use of buffers. Where traditionally bags are stored in (racking-based) EBS systems, we see value in an additional (lane) buffer for warm bags that only need storage for minutes rather than hours. Bypassing the centralised bag store not only saves space, but also lowers the pressure on bag store throughput capacity and reduces energy consumption, because there is less travel distance in the system.
Automated LU handling also makes more efficient use of space by enabling the buffering of bags in containers. For instance, if ten bags for the same flight are available, we can load them into a container and temporarily store it – this is more efficient in terms of space than storing the ten bags individually in a bag store. The automated LU handling system, tailored for an efficient indoor operation, requires an interface with the outdoor transport (tug and dolly) vehicles. The additional space requirement is offset by the storage of LUs at multiple levels within the baggage hall, enabled by the use of automated forklift-based technology.
For the inbound journey, cold transfer bags may be buffered in segregated containers to better utilise the existing unloading quays instead of investing in spacious additional input points. The connectivity between systems (in the end-to-end process) and reliability of data sources (for instance, which bags are loaded into which inbound containers) are key in the transition from an ad hoc reactive process to a proactive, predictable data-driven operation that optimises the utilisation of the required infrastructure.
In conclusion, this white paper explores the transformative potential of automation, particularly embodied in the Baggage 4.0 concept, as a pivotal remedy to the labour scarcity challenge faced by the aviation industry.
It emphasises the interplay of automation, smart batching and automated handler processes. These components work in tandem to construct a strong operational framework. Our findings reveal untapped opportunities for enhanced automation in the current BHS. Smart batching methods have the potential to increase the volume of automated batch loading beyond 80%, enabling reduced handling effort. Furthermore, the solutions and processes discussed to automate handler processes offer a path to achieving up to 150% higher productivity with the same workforce.
This approach not only addresses labour scarcity, but also aligns with sustainability objectives, providing a safeguard against unforeseen disruptions. The handler‘s role evolves from physical handling to a more supervisory and coordinating position. Baggage 4.0 envisions a scenario in which automation takes centre stage, and human roles shift from being reactive to proactive, leveraging data insights.
In essence, this paper is a stepping stone to future exploration. It‘s core insights lay a foundation for forthcoming investigations. Our upcoming research will delve deeper into the convergence of digital solutions and sustainability, further revealing how innovation can shape the course of baggage handling operations and exploring the remaining facets of our Baggage 4.0 vision.
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