Optimizing large-volume scheduling for cost avoidance

Abstract

This dissertation presents the results of developing optimization algorithms for use in operational scheduling of airplane stalls and paint hangars at the Boeing Company's Everett Delivery Center. With the increasing number of orders, more airplanes are coming out of the Everett Factory and into the flightline for painting, fueling, and other pre-delivery testing activities. While Boeing's existing infrastructure is still well able to support this increasing scale of operations, some of the existing manual scheduling processes become more time consuming and sprout inefficiencies. This existing scheduling process was mapped and analyzed, and an Excel VBA tool was developed in collaboration with Boeing's Applied Math group to provide visibility into cost avoidance opportunities for the Everett Delivery Center. As a result of this work, up to 35% of paint hangar costs have been identified as potentially avoidable.