Decision support model to evaluate complex overhead crane schedules

Boeing Commercial Airplanes produces four twin-aisle airplane models at its Everett, Washington production facility-the largest building by volume in the world. Efficient and effective material handling of large airplane substructures is critical to maintain production rates, and the Everett facility employs two interconnected systems of overhead cranes to move airplane sections through the factory. The crane scheduling team needed a tool to evaluate current and proposed crane schedules for feasibility, rate capability, and potential bottlenecks. Boeing Research and Technology partnered with Simio LLC to develop a simulation model of the crane network that would execute and evaluate a series of crane moves. The model employs both discrete event and agent-based paradigms to model the complex system and to allow for highly configurable initial states. This approach allows for rapid schedule evaluation, non-recurring planning, and real-time system modeling. In this paper we present the system, the model, and results.