Surface Defect Classification in Silicon Wafer Manufacturing Using Linear-Based Channeling and Rule-Based Binning

Surface defect control is the serious science in semiconductor industry. Surface defects found at the end product of silicon wafer manufacturing are generated by human, fab facility, equipment and process. Generally, the surface defects found on a silicon wafer could be classified as grown-in Crystal Originated Particles (COPs), Surface-Adhered Foreign Particles (SFPs), and Process-Induced Defects (PIDs). Making the correct defect classification by the surface scanning instrument is of paramount because it provides the opportunity for finding defect root cause, which is part of yield enhancement process. This article reveals a novel defect classification approach by optimizing the linear-based channeling and rule-based binning algorithms applied in KLA surface scanning counter, a commercially available surface defect metrology tool.