With the help of artificial intelligence, KLM employees can get more accurate forecasts of the type of food consumption expected on each flight. The first results are encouraging: the amount of food waste can be significantly reduced.

Using an algorithm developed specifically for catering, the airline attempts to make accurate estimates of how much food should be prepared and brought on board for each flight. It depends on the number of passengers, so the self-learning algorithm makes estimates from this data. Not all passengers who have reservations for the flight arrive, depending on the class of travel. The percentage of those who do not show up for check-in for some reason ranges between 3 and 5 percent.

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The system called “In-Flight Meal System” provides the expected number of passengers for each flight, broken down by class of travel, and the data is updated continuously up to 20 minutes before departure, so a very accurate estimate can be given of how many passengers can be expected and how many food ingredients will need to be purchased. To be served, then prepared from these dishes and transported on board the ship.

According to data from the first three months, food waste was reduced by 63 percent during catering activities. The most noticeable change can be seen on intercontinental flights, where 2.5 servings less food waste is produced on each flight.

This may not seem like a lot at first, but on an annual basis and for the entire airline network, that would mean 111 tons, so a lot of food preparation and waste could be saved.

KLM also announced that it is already working on applying AI more broadly in flight operations and machinery maintenance as well as catering.

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