Scenario for a Yield Model Based on Reliable Defect Density Data and Linked to Advanced Process Control

Abstract

Currently, yield enhancement and APC (advanced process control) systems operate independently within the manufacturing process. Yield enhancement has several requirements such as the root cause analysis of yield loss, the reliability of defect density data, and the demand for a link between yield models and APC. For root cause studies chemical analysis uses different preparation techniques to describe the nature and location of contamination or defect densities, e.g. copper bulk contamination or wafer edge effects. The reliability of defect density data and the matching of defect inspection tools improve by the reduction of noise. In combination with a process model this is the prerequisite to set up a random defect-based yield scenario which describes single processes. The combination of this scenario with methods for data acquisition and tracking from APC enhances the prediction of yield.

Process Optimization by Means of Integrated Monitoring Tools in the Semiconductor Industry

“…APC requires the conversion of today's polishing processes to intelligent selfadjusting processes (13). This conversion requires optical metrology in integrated solutions for in-line flatness control which has to meet the following requirements: a) compact sensors, b) the accurate measurement of local wafer geometry c) a high throughput for the inspection of surface.…”

“…Between radii of 110 mm to 150 mm the wafer thickness decreases by several 100 nm. This effect was explained with a simple model concerning the consumables and polishing process parameters (15). Such models are the base for reliable process control implemented in polishing equipment.…”