SBIR Phase II: Optimal Replenishment Algorithms for Service Parts Logistics Systems

SBIR 第二阶段：服务备件物流系统的最佳补货算法

• 批准号: 0239030
• 负责人: Vipul Agrawal
• 金额: $ 49.84万
• 依托单位: MCA SOLUTIONS INC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-02-01 至 2005-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0239030&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Optimal; Replenishment

This Small Business Innovation Research Phase II Project will develop prototype software to provide optimal real time purchase and repair replenishment, and allocation of service spare parts used to provide after-sales support to mission-critical products. It will design, develop and test advanced optimization algorithms to ensure that the right part is ordered from the right source in the right quantity at the right time and then allocated to the right location. In Phase III these engines will be incorporated in MCA Solutions planned commercial enterprise software product Replenishment and Allocation Optimizer (RAO) and complement MCA Solutions current product Service Parts Optimizer (SPO). The use of this tool will result in higher availability of service parts, increase products uptime and lower expense in service parts inventory. The target industries for this solution will be Defense, Aerospace, and manufacturers of Automotive, Computer, Telecommunications and Hi-Tech equipment. RAO will be the first commercial software product to support near real time optimization of inventory management in service supply chains. The requirement allocation optimizer software market is underdeveloped. The size of this opportunity is significant. Over 1,100 companies in the United States generate sales higher than $250 M/year in the original equipment manufacturer segment. Combined sales in this sector are $3.3 trillion with total inventory investment in service parts of about $250 Billion. Service parts inventory accounts for about 5 to 10% of product sales for an OEM. The technology has the potential to reduce these investments by 20% to 40 which in turn may pass some of the reductions to the customers.

该小型企业创新研究第二期项目将开发原型软件，以提供最佳的真实的时间购买和维修补给，以及用于为关键任务产品提供售后支持的服务备件分配。它将设计、开发和测试先进的优化算法，以确保在正确的时间从正确的来源以正确的数量订购正确的部件，然后分配到正确的位置。在第三阶段，这些引擎将被纳入MCA解决方案计划的商业企业软件产品补给和分配优化器（RAO），并补充MCA解决方案目前的产品服务零件优化器（SPO）。该工具的使用将提高备件的可用性，增加产品库存，降低备件库存费用。该解决方案的目标行业将是国防、航空航天以及汽车、计算机、电信和高科技设备制造商。RAO将是第一个支持服务供应链中库存管理接近真实的时间优化的商业软件产品。需求分配优化器软件市场不发达。这个机会的规模是巨大的。美国有超过1,100家公司在原始设备制造商领域的销售额超过2.5亿美元/年。该行业的总销售额为3.3万亿美元，服务零件的总库存投资约为2500亿美元。服务零件库存约占OEM产品销售额的5%至10%。该技术有可能将这些投资减少20%至40%，这反过来又可能将部分减少的投资转嫁给客户。