Localized Decision-Making for Materials Transportation Systems Subject to Stochastic Uncertainty

Programming and installation of Materials Transportation Systems (MTS) in a manufacturing setting represent a significant portion of the investment in these systems. The costs are often so high that this alone presents a barrier to adoption amongst midsize manufacturers. Furthermore, the resulting systems are just as costly to reconfigure, limiting the flexibility of the resulting manufacturing facility to product changes. This research examines a localized decision-making scheme, in which individual manufacturing components are enhanced with an amount of intelligence and autonomy to enable the system to automatically self-program. Through an example, we study this paradigm versus fixed programming alternatives as the stochastic variability of the manufacturing setting increases. Localized Decision-Making enables a plug-n-play autonomy that can readily adapt to changes and deal with uncertainties in manufacturing.