Abstract: Aspects of the present disclosure provide a method and a system for providing a selection of golden tools for better defect density and product yield. A golden tool selection and dispatching system is provided to integrate different components for robust golden tool selection and dispatching. The golden tool selection system selects a set of golden tools based on performance of a set of manufacturing tools and provides a fully automated operational environment to produce a product using the set of golden tools.

Abstract: Provided are a method and a system for virtual metrology in semiconductor manufacturing. Process data and metrology data are received. Prediction data is generated based on the process data and metrology data using a learning control model. The system for virtual metrology in a fabrication facility comprises a fault detection and classification system operable to receive process data, a statistical process control system operable to perform statistical process control on a history of physical metrology data to form metrology data, and a virtual metrology application operable to generate prediction data based on the process data and the metrology data using a learning control model.

Abstract: Aspects of the present disclosure provide a method and a system for providing a selection of golden tools for better defect density and product yield. A golden tool selection and dispatching system is provided to integrate different components for robust golden tool selection and dispatching. The golden tool selection system selects a set of golden tools based on performance of a set of manufacturing tools and provides a fully automated operational environment to produce a product using the set of golden tools.

Abstract: A method and system are disclosed for configuring manufacturing tools in a semiconductor manufacturing flow. After collecting information with regard to one or more product performance features associated with a processing step performed in a process tool, one or more undesired process tool performance excursion patterns may be determined based on the collected information. On the other hand, operational and processing parameters of the process tool are monitored while conducting the processing step. Non-conformance faults of the monitored operational and processing conditions are detected and classified. A correlation between the classified non-conformance faults with the determined excursion patterns is made for adjusting one or more processing parameters of the processing tool.

Abstract: A method and system are disclosed for configuring manufacturing tools in a semiconductor manufacturing flow. After collecting information with regard to one or more product performance features associated with a processing step performed in a process tool, one or more undesired process tool performance excursion patterns may be determined based on the collected information. On the other hand, operational and processing parameters of the process tool are monitored while conducting the processing step. Non-conformance faults of the monitored operational and processing conditions are detected and classified. A correlation between the classified non-conformance faults with the determined excursion patterns is made for adjusting one or more processing parameters of the processing tool.