SGER GOALI - Collaborative Research: Forecasting and Proactive Management of Obsolescence for Sustainment-Dominated Systems

SGER GOALI - 协作研究：以维持为主导的系统的报废预测和主动管理

• 批准号: 0438522
• 负责人: Peter Sandborn
• 金额: --
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-10-01 至 2006-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0438522&HistoricalAwards=false
• 关键词: SGER; GOALI; Collaborative; Research; Forecasting

This GOALI SGER Collaborative project is to explore how industry and academia can collaborate to determine how multiple sources of resources can be combined to impact proactive obsolescence of electronic parts through forecasting and management. One of the most significant problems facing many "high-tech" sustainment-dominated systems is technology obsolescence, and no technology typifies the problem more clearly than electronic part obsolescence. It is expected that substantial savings in resources are possible if methods of forecasting through obsolescence-driven life cycle planning of products were developed and applied. This project will involve three high risk, high impact activities:1) Forecasting electronic part obsolescence by predicting the date of discontinuance under uncertainty of social, political, economic, and environmental factors.2) Determine the best mitigation approach upon obsolescence, and3) Manage the redesign of systems based upon the forecast.The broader impact is the expectation that longer term cost avoidance can be a more significant driver in economic decision-making if the forecasting lowers the uncertainty and risk. This is a high risk activity because of the inherent complexity is integrating across social and technological models for a sector such as the electronics sector.

这个GOALI SGER协作项目旨在探索工业界和学术界如何合作，以确定如何将多种资源结合起来，通过预测和管理来影响电子零件的主动淘汰。许多以“高技术”维持为主的系统所面临的最重要问题之一是技术陈旧过时，而没有任何技术比电子部件陈旧过时更能说明这一问题。如果制定和应用通过过时驱动的产品生命周期规划进行预测的方法，预计可以节省大量资源。该项目将涉及三个高风险、高影响的活动：1）在社会、政治、经济和环境因素的不确定性下，通过预测停产日期来预测电子部件的过时。2）确定过时后的最佳缓解方法，以及3）根据预测管理系统的重新设计。更广泛的影响是，如果预测降低了不确定性和风险，则预期长期成本避免可以成为经济决策中更重要的驱动因素。这是一项高风险活动，因为电子行业等行业的社会和技术模式具有内在的复杂性。