Cost-Effective Reliability Screening, Binning, and In-Field Adaptation

经济高效的可靠性筛选、分级和现场适应

• 批准号: 1255818
• 负责人: Li-Chung Wang
• 金额: $ 18.9万
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-04-01 至 2017-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1255818&HistoricalAwards=false
• 关键词: Cost; Effective; Reliability; Screening; Binning

In the semiconductor industry, one way of measuring reliability is the expected lifetime of a product. As semiconductor manufacturing technologies continue to advance, ensuring reliability has become one of the major challenges in the industry. The ability to ensure reliability is essential for the success of a product line as well as the success of the industry. This project proposes to develop a first cost-effective solution for screening unreliable parts before product shipment to the customer. The project proposes to develop software tools and methodologies for predicting the expected life time of a part. Further, the project proposes to develop a second cost-effective solution for continuously monitoring and improving reliability while a part is being used in the field. Additional software tools and methodologies will be developed for building models for such continuous monitoring. These monitoring models are then used for extending the life time of a part by automatic adjusting the operational parameters such as speed and voltage of the part based on its current health condition. The research is integrated with educational activities to develop course and tutorial materials for broad impact, a state-of-the-art laboratory for education, and a research program to attract undergraduate and underrepresented students. The research strives to achieve a comprehensive understanding of state-of-the-art industrial practices and to accomplish multidisciplinary studies merging knowledge from reliability physics, semiconductor testing, and data mining. Knowledge discovered through this research will provide the industry with a clear direction on how to cope with the present and future reliability challenges.

在半导体行业，衡量可靠性的一种方法是产品的预期寿命。随着半导体制造技术的不断进步，确保可靠性已成为该行业的主要挑战之一。确保可靠性的能力对于产品线的成功以及行业的成功至关重要。该项目建议开发第一个具有成本效益的解决方案，用于在产品装运给客户之前筛选不可靠的部件。该项目提议开发预测零件预期寿命的软件工具和方法。此外，该项目还建议开发第二种具有成本效益的解决方案，以便在现场使用零件时持续监测和提高可靠性。将开发更多的软件工具和方法，为这种持续监测建立模型。这些监测模型然后用于通过基于其当前健康状况自动调整诸如部件的速度和电压的操作参数来延长部件的寿命。 该研究与教育活动相结合，以开发具有广泛影响力的课程和辅导材料，一个最先进的教育实验室，以及一个吸引本科生和代表性不足的学生的研究计划。该研究致力于全面了解最先进的工业实践，并完成多学科研究，融合可靠性物理，半导体测试和数据挖掘的知识。通过这项研究发现的知识将为行业提供一个明确的方向，如何科普当前和未来的可靠性挑战。