A Review Study on ML-based Methods for Defect-Pattern Recognition in Wafer Maps
T.C. Theodosiou, Andriana Rapti, K. Papageorgiou, Theodoros Tziolas, Elpiniki I. Papageorgiou, Nikolaos Dimitriou, George Margetis, Dimitrios Tzovaras
Abstract
The identification of defects plays a key role in the semiconductor industry as it can reduce production risks, minimize the effects of unexpected downtimes and optimize the production process. A literature review protocol is implemented and latest advances are reported in defect detection considering wafer maps towards quality control. In particular, the most recent works are outlined to demonstrate the use of AI-technologies in wafer maps defect detection. The popularity of these technologies is then presented in the form of visualizing graphs. This enables the identification of the most popular and most prominent ML-methods that can be exploited for the purposes of Industry 4.0.