The Impact of Yield Variation on Cost of Ownership

摘要

Increasingly, Cost Of Ownership (COO) is being used not only for equipment purchase decisions, but also as a metric for continuous improvement of machine operations. There are many things to consider for COO; reliability, consumables, gases and liquids, maintenance cost, cleanroom floor space, etc. Though product yield is one of the largest leverage points for COO, and is one of the least understood inputs, understanding the impact that product yield has on COO is an important part of continuous improvement. Using machine particle counts for predictive yield modeling has been discussed before and is part an on-going effort supporting the International Technical Roadmap for Semiconductors (ITRS). Utilizing the modeling methods previously published and validated in the SEMATECH effort, the yield impacts of machine to machine particle variation on product yield and excursions can be studied. This paper looks at the impact of particle variation on product yield and the resulting impact on COO. Trending these on a real-time basis provides an overall operational success metric for driving continuous improvement in semiconductor manufacturing.