DDDAS-SEP: Dynamically-Integrated Production Planning and Operational Control for the Distributed Enterprise

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Modern society depends upon many interacting large-scale dynamic systems (systems of systems), most of which are too complex for mathematical analysis. The behavior of such system networks depends on their linkages and the environment, i.e. scientific reductionism is incapable of fully defining behavior. These applications are typically characterized by hierarchical control and horizontally, interdependent components (federates), and in a dynamic environment require the whole or sub system(s) to respond adaptively to changes in an accurate and timely manner for improved performance.This project focuses on hierarchical production and logistics planning and control in highly capitalized discrete manufacturing system networks. The overall scheme envisioned is a multi-scale federation of interwoven simulation and decision models that support planning and control with dynamic updating through sensed and streamed data. Planning and control models are updated both directly from real-world sensed data and from simulations. While the real world may yield parameters such as current costs or inventory status, the simulation model, in synchronization with other federates representing the other entities in the supply network, will be used to compute more complex model parameters such as lead times and effective resource availabilities. In addition, the simulation model will be used off-line to test the performance of various proposed decision rules/models and guide the selection of model construction and selection at each re-planning instance. Re-planning will occur when a defined threshold of discordance between actual observation and model form used to construct the active plan is reached.To accomplish these goals the project will investigate methods for the development of an integrated architecture for distributed computing in networked sensor-driven, hierarchical decision and control systems of the distributed enterprise. This architecture, which is based on ubiquitous web service technology, will allow an integrated collection of multi-scale models that support the simulation, decision and control functions to interact with transducers. The proposed architecture will facilitate integration in several ways: developing a continuous sensor-driven approach to planning and control coordination; interoperability of different genres of models for distributed systems; integration of sensor/actuator interactions with a variety of models; integration of different genres of sensors/actuators that conform to different standards; integration of sensor measurements in the model validation process.