M. D. Mills Harris, C. Saygin, A. Soylemezoglu, University of Missouri-Rolla, Rolla, MO; K. M. Etzkorn, P. Freeman, The Boeing Company, St. Louis, MO
Summary: Planning, scheduling, and control of manufacturing operations in large-scale systems,
such as aerospace manufacturing facilities, are inherently complicated due to the complexity of
products. The research shows that hierarchical modeling of such systems leads to rigid system
architectures such that it simply becomes incapable of responding to changing circumstances in a
timely and cost-effective fashion. Distributed systems architectures facilitate agility,
responsiveness, and reconfigurability, which are the key for survival in today’s market since the
focus is on high product variety, low volumes, low cost, high quality, and on-time delivery. In
this work, a manufacturing environment that possesses such features is called a network-centric
manufacturing environment, which incorporates a dynamic network of self-organizing,
autonomous units that operate, collaborate, cooperate, and compete upon basic principles of
decentralization, participation, and coordination in order to accomplish the goals set at system
level.
In this study, an adaptive inventory management model founded on Auto-ID-based state
and event data for tracking and dispatching of time and temperature sensitive materials in an
aerospace manufacturing facility is presented. The impact of integrating Auto-ID technologies
with inventory control on the shop floor is discussed. This study compares various traditional
inventory models with the adaptive inventory management model proposed in this work on the
basis of cost savings, inventory and waste reduction, inventory turns, and decision making
complexity. The validity of the proposed model is demonstrated in a simulation environment,
which also demonstrates the overall benefits and effectiveness of Auto-ID technologies in
providing low cost manufacturing solutions, reducing inventory levels, and preventing excessive
waste for typical aerospace manufacturing environments.
