SBIR Phase II: Enterprise Decision Making Using Activity Interaction Technology

SBIR 第二阶段：利用活动交互技术进行企业决策

• 批准号: 1052566
• 负责人: David Zhang
• 金额: $ 50万
• 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: 2011
• 资助国家: 美国
• 起止时间: 2011-02-01 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1052566&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Enterprise; Decision

This Small Business Innovation Research (SBIR) Phase II project seeks to further research and implement a Network Algorithm for efficiently running large-scale network simulations and using those simulations to perform enterprise planning and risk analysis. The company's algorithms (and associated early-release software) have been shown to run supply chain models one order of magnitude faster, with one order of magnitude more complexity, than current simulation models commonly deployed. Bioproduction Group has created a simulation methodology that meaningfully links together highly-detailed operational level models with its large network-scale model. Each operations simulation is linked by network relationships such as supply and demand, product path flows, and inventory holding centers. Bioproduction Group has received contracts with several biotech firms to implement advanced prototypes of this research in biopharmaceutical manufacturing as they come online. The goal is to use this simulator to reduce biopharmaceutical inventory levels across the industry by 10% or more, while reducing risk across the manufacturing network. If successfully deployed in a large enterprise, it is believed that this inventory reduction would have a yearly return of more than $20mm per organization. The technology has the potential to be used across the biopharmaceutical industry to increase quality of care to the patient as well as reduce manufacturing costs. These goals have significant direct flow-on savings benefits to the hundreds of thousands of patients across the entire public and private healthcare sector.

这个小型企业创新研究（SBIR）第二阶段项目旨在进一步研究和实施网络算法，以有效地运行大规模网络模拟，并使用这些模拟来执行企业规划和风险分析。该公司的算法（以及相关的早期版本软件）已被证明比目前常用的仿真模型运行供应链模型的速度快一个数量级，复杂性高一个数量级。Bioproduction Group创建了一种模拟方法，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。每个操作模拟都通过网络关系（如供应和需求、产品路径流和库存保持中心）链接。生物生产集团已收到合同，与几个生物技术公司实施先进的原型，这项研究在生物制药制造，因为他们来在线。我们的目标是使用该模拟器将整个行业的生物制药库存水平降低10%或更多，同时降低整个制造网络的风险。如果在大型企业中成功部署，相信这种库存减少将为每个组织带来超过2000万美元的年回报。该技术有可能在整个生物制药行业中使用，以提高对患者的护理质量并降低制造成本。这些目标对整个公共和私人医疗保健部门的数十万患者具有显着的直接流动储蓄效益。