Optimizing Material Shortages in Flight Catering with Machine Learning

Material shortage in-flight catering involves delays in the supply of alcohol, food, beverages, and carts to scheduled flights, leading to operational inefficiencies. We will try to find the root cause using Machine Learning techniques, such as vendor unavailability, transportation delays, raw material shortage, and other factors that may lead to the problem. Sample data will be used to simulate real-world situations and develop predictive solutions for shortage optimization. The findings point out the possible benefits of data-driven decision-making to accelerate production and delivery processes within in-flight catering.