SBIR Phase I: Enterprise Decision making using Activity Interaction technology

SBIR 第一阶段：使用活动交互技术进行企业决策

• 批准号: 0945777
• 负责人: David Zhang
• 金额: --
• 依托单位: Bioproduction Group, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-01-01 至 2010-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0945777&HistoricalAwards=false
• 关键词: SBIR; Phase; Enterprise; Decision; making

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.

这个小型企业创新研究（SBIR）第一阶段项目旨在开发一种网络算法，用于有效地运行大规模网络模拟，以执行企业规划和风险分析。目前，供应链模型只包括简单的，低细节的节点，只近似的设施的参数，他们表示。因此，很难确定操作级别更改和关系对网络范围级别的影响。研究表明，运行由详细的操作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，将高度详细的操作级模型与其大型网络规模模型联系在一起。每个操作模拟都将通过网络关系（如供应和需求、产品流和库存控制中心）连接起来。然后可以创建一个矩阵，存储这些关系参数，最大限度地减少所需的计算时间投资。该项目更广泛的影响/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。工业灾难，如爱立信工厂火灾，摧毁了公司的库存水平，强调了需要了解公司之间以及公司内部的复杂相互关系。网络模拟器允许分析人员明确地看到设施是如何相互关联的，以及不良事件如何影响不仅仅是一个设施，而是整个网络。该技术有潜力在整个生物制药行业中使用，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。