SBIR Phase I: Enterprise Decision making using Activity Interaction technology

该小型企业创新研究(SBIR)第一阶段项目旨在开发一种网络算法，用于高效运行大规模网络模拟，以执行企业规划和风险分析。目前，供应链模型只由简单的、低细节的节点组成，这些节点只近似于它们所代表的设施的参数。因此，很难确定运营级别的变化和关系在整个网络级别上的影响。研究表明，运行由详细运营模型组成的大规模供应链模型将运行得太慢，无法及时执行任何有意义的分析。该项目旨在开发一种模拟方法，将高度详细的运行级模型与其大型网络规模模型有效地联系在一起。每个运营模拟都将通过供需、产品流动和库存保存中心等网络关系联系在一起。然后，可以创建存储这些关系参数的矩阵，从而将所需的计算时间投资降至最低。该项目的广泛影响/商业潜力将使组织更好地了解他们在内部和整个生产网络中面临的风险。工业事故，如爱立信工厂火灾，使该公司的库存水平大幅下降，突显了理解公司之间以及公司内部复杂内部关系的必要性。通过网络模拟器，分析人员可以明确了解设施之间的相互关系，以及不良事件不仅会影响一个设施，还会影响整个网络。这项技术有可能应用于整个生物制药行业，既提高了对患者的护理质量，又降低了类似数量的制造成本。

This Small Business Innovation Research (SBIR) Phase I Project seeks to develop a Network Algorithm for efficiently running large-scale network simulations to perform enterprise planning and risk analysis. Currently, supply-chain models consist of only simplistic, low-detail nodes which only approximate the facility's parameters that they represent. Because of this, it is difficult to determine the effect of operational level changes and relationships on a network-wide level. Research has shown that running a large-scale, supply chain model consisting of detailed operational models will run too slowly to perform any meaningful analysis in a timely manner. This project aims to develop a simulation methodology that meaningfully links together highly-detailed operational level models with its large network-scale model. Each operations simulation will be linked by network relationships such as supply and demand, product flows, and inventory holding centers. It is then possible to create a matrix which stores these relational parameters that minimize the computing time investment required. The broader impact/commercial potential of this project will provide organizations with a better understand of the risks they face both internally and across the entire production network. Industrial mishaps, such as the Ericsson facility fire which decimated the firm's inventory levels, have underlined the need to understand the complex inter-relationships between, as well as within, companies. A network simulator allows analysts to explicitly see how facilities are interrelated and how adverse events affect not just one facility, but the entire network. The technology has to potential to be used across the biopharmaceutical industry and both increase quality of care to the patient as well as reduce manufacturing costs by a similar amount.