Case Study: Commercial Airline Cargo Business
The Problem: In the belly of all commercial airline flights are a combination of passenger luggage and air freight, or cargo. The airline carrier would like to utilize all space in the belly of the airplane (Figure 1) but the challenge is being able to plan for freight that is coming when there is a quick turn-around between customer drop-off and needing to have the plane loaded. We were asked to evaluate the current process and look for opportunities where our technology could be applied to gain efficiencies.
Research Findings: There are four steps to get the freight from shipper to destination. At each stage there is a different user/stakeholder for the process to ensure success, written in italics:
1. Prepare cargo for plane loading at the cargo warehouse = Warehouse worker
2. Plan the location of the cargo load on the plane to maintain weight and balance = NOC load planner
3. Bring cargo planeside and load into the belly of the plane = Ramp crew
4. Deliver cargo to destination warehouse for customer pick-up = Warehouse worker
The value proposition for a Cargo customer is that they can get their freight quickly to its destination. They are required to drop off any freight five hours before the scheduled flight time. The cargo team needs to have it processed and planeside two hours before the scheduled flight time so that it can be loaded before the passenger luggage. This leaves only three hours for processing the freight through the warehouse. This may seem like ample time, but the warehouse has a peak time of 12–4pm where most of the freight is coming in all at once. Additionally, the freight is not going directly from the customer to the plane but packages and pallets need to be consolidated on “super-pallets” that combine items going to the same destination (Figure 2). These take anywhere from 20 minutes to one hour to build up, depending on the size of the items being moved and the level of expertise of the worker.
The next step in the process is to plan the plane loading, performed at the Network Operations Center (NOC). The load planner needs to make sure the plane as a whole is balanced; above and below, front-to-back, and left-to-right for safe take-off, flying, and landing. They also need to insure the plane has adequate fuel given the distance and overall weight. As they determine the load locations their priorities are to accommodate all passengers first, then their luggage, and finally the cargo. If anything is going to be compromised, it will be delaying cargo rather than a passenger or luggage. In order to make these decisions they get information from various sources at different times. Four hours before flight time, they get information from the dispatch about the route, gas, and runway location. From the passenger data they can calculate weight above the wing and load distribution based on seat assignment. Two hours before the flight, the NOC receives data from Cargo. Ideally, they would want the dimensions of the cargo to best plan but currently they only have visibility to weight and it is not available in real-time (when it was captured). The NOC planner then needs to provide the load plan to the ramp crew approximately 70 minutes before the scheduled flight.
The ramp crew need information from the NOC planner about the number of pallets and what assigned location they are to be loaded at. However, as the planner only knows weight there are times that the freight cannot fit in the assigned spot. The example shared with us by the customer is a shipment from a table tennis manufacturer. The shipment may say 200 lbs, but if that could either be flat boxes of tables or large pallets of ping-pong balls. The same weight could be drastically different dimensions. In the case where the cargo cannot go in the assigned spot, the ramp crew must make decisions about how to rearrange the freight. This change then is communicated back to the NOC and needs to be approved by the planner before it can be executed. Again, all of this is happening within strict time bounds to leave adequate time to load luggage and get the plane out on time after boarding passengers.
Solution Exploration: We evaluated the end-to-end process and looked at the needs across the cargo workers, NOC planner, and ramp crew. We concluded that the greatest opportunities are to provide dimensions of the cargo in real-time and a means of improved communication of information across the different locations/users. Working with engineers from our chief technology office (CTO) we identified two means of capturing real-time dimensions using machine-vision technology. This data is valuable to all users as it can be passed to the customer application for use 1) by the cargo worker to provided guided pallet building, 2) the NOC planner to know which location the freight will fit into, and 3) give greater confidence to the ramp crew of the plan. One of the two dimension solutions is able to be accessed by a mobile device, which the ramp crew already uses for load confirmation. If they could also measure the dimension, then they could provide information back to the NOC if a plan needed to change based on erroneous warehouse data. These solutions are being evaluated by the customer. Doing this type of generative research helps our team not only understand the need of a specific customer but also broadens our understanding of challenges in the transportation and logistics industry as a whole, so that we can proactively design solutions.
