Skip to content

Autonomous semi-supervised machine learning application to detect the quality of electronic wafers

Notifications You must be signed in to change notification settings

Ahmed-0357/wafer_fault_detection

Repository files navigation

◍ Wafer Fault Detection ◍

  • This is an autonomous semi-supervised machine learning application to detect the quality of electronic wafers based on the inputs from various sensors.
  • A wafer is a thin slice of semiconductor used for the fabrication of integrated circuits and, in photovoltaics, to manufacture solar cells.

electronic wafer with built in circuits


The project architecture is made up of two main pipelines (training and prediction). The training pipeline contains three stages namely data ingestion, data preprocessing, and model development, while the prediction pipeline contains data ingestion, data preprocessing, and prediction.


project architecture


animated

training page


animated

prediction page


  • Click here to try the application

  • Click here to access the docker image animated


Authors