Research Planning Grant: Analysis and Maximization of Large Complex Industrial Systems Through Distributed Simulation

这项研究计划拨款的中心是通过高级分布式仿真（ADS）研究大型复杂工业系统的分析和最大化。ADS技术为地理分布模拟提供了一个交互式的、时间一致的合成环境。它是实时、虚拟和建设性模拟的结合。本研究的重点是将ADS作为大型复杂制造系统分析和最大化的工具。ADS通过完全集成的单个仿真系统提供了企业范围的建模能力（在企业内部：设计和制造过程；在企业外部：供应商和小型支持制造商），其最终目标是使整个系统最大化。拟议研究的结果将(1)强调用于分析和最大化整个工业系统的完全集成系统的优势和潜在利益，(2)促进模拟聚合的进步，特别是解决与ADS相关的问题。规划拨款是必要的，以便：(1)可以获得对ADS的完整理解，(2)可以研究将ADS应用于目标本地制造商的机会，(3)可以使用至少一个神经网络聚合模型开发一个简单但具有代表性的原型，(4)可以编写一个全面的NSF提案。

Twomey 9622132 This research planning grant centers on investigation into the analysis and maximization of large complex industrial systems through Advanced Distributed Simulation (ADS). ADS technology provides an interactive, time-consistent synthetic environment for geographically distributed simulations. It is a combination of live, virtual and constructive simulation. This research focuses on ADS as a tool for the analysis and maximization of large complex manufacturing systems. ADS provides the capability for enterprise-wide modeling (within the enterprise: design and manufacturing processes; and outside the enterprise: vendors and small supporting manufacturers) through a fully integrated system of individual simulations, where the ultimate goal is the maximization of the entire system. The outcome of the proposed research will (1) highlight the advantages and potential benefits of fully integrated systems for the analysis and maximization of an entire industrial system, and (2) contribute to the advancement of simulation aggregation specifically addressing issues related to ADS. A planning grant is necessary so that: (1) a complete understanding of ADS may be gained, (2) opportunities for an ADS application to a targeted local manufacturer may be investigated, (3) a simple but representative prototype may be developed with at least one neural network aggregation model, and (4) a full-scale NSF proposal can be written.