Wafer fabrication yield learning and cost analysis based on in-line inspection
研究了晶圆制造中基于在线检测的良率提升模型，考虑学习效应，分析检测容量和检测率对良率及总成本的影响，为优化检测策略提供依据。
Wafer fabrication is characterised with advanced equipment, complex processes and high cost. Good production output, measured by yield given total throughput, should rapidly increase while considering the associated cost. Yield improvement models based on inspection usually consider the effect of excursion monitoring, while this work considers the effect of learning from experience as well. It assumes a production model where each machine’s output is inspected via wafers it processes, triggering repair if required. The yield improvement is modelled as a function of machine’s quality performance, accumulated inspections, inspection capacity and inspection rate. It exhibits a sigmoid shape curve with slow rise in startup, acceleration in ramp and almost a plateau in high volume manufacturing. Higher inspection rate enables more inspections over time, faster learning and higher yield. Yet, higher inspection rate at constant capacity prolongs the response time and can further drive lower yield. Clearly, higher inspection capacity enables faster yield improvement, but also increases equipment and operations costs. The cost analysis developed here illustrates the preferred inspection capacity and inspection rate, for minimising the overall cost combined of yield loss and inspection cost. It also shows preference to error with higher, rather than with lower, inspection capacity.