Applied Materials, Inc.

Garrett H Sin

Ganesh Balasubramanian

Sidharth Bhatia

Chidambara A Ramalingam

Heng-Cheng Pai

Irfan Jamil

Pramod Nambiar

John S Lewis

Michael Biese

Balaji Chandrasekaran

Tak Fan (Kerry) Ling

Boguslaw A Swedek

Lakshmanan Karuppiah

Sidney P Huey

Terry Kin-Ting Ko

Sanjeev Jain

A method includes identifying sets of sensor data associated with wafers processed via wafer processing equipment and identifying sets of metrology data associated with the wafers processed via the wafer processing equipment. The method further includes generating sets of aggregated sensor-metrology data, each of the sets of aggregated sensor-metrology data including a respective set of sensor data and a respective set of metrology data. The method further includes causing, based on the sets of aggregated sensor-metrology data, performance of a corrective action associated with the wafer processing equipment.

Sensor metrology data integration

Methods, systems, and non-transitory computer readable medium are described for sensor metrology data integration. A method includes receiving sets of sensor data and sets of metrology data. Each set of sensor data includes corresponding sensor values associated with producing corresponding product by manufacturing equipment and a corresponding sensor data identifier. Each set of metrology data includes corresponding metrology values associated with the corresponding product manufactured by the manufacturing equipment and a corresponding metrology data identifier. The method further includes determining common portions between each corresponding sensor data identifier and each corresponding metrology data identifier. The method further includes, for each of the sensor-metrology matches, generating a corresponding set of aggregated sensor-metrology data and storing the sets of aggregated sensor-metrology data to train a machine learning model. The trained machine learning model is capable of generating one or more outputs for performing a corrective action associated with the manufacturing equipment.

A method of forming bare silicon substrates is described. A bare silicon substrate is measured, wherein measuring is performed by a non-contact capacitance measurement device to obtain a signal at a point on the substrate. The signal or a thickness indicated by the signal is communicated to a controller. An adjusted polishing parameter according to the signal or thickness indicated by the signal is determined. After determining an adjusted polishing parameter, the bare silicon substrate is polished on a polisher using the adjusted polishing parameter.

In-line wafer thickness sensing

A cleaning method is provided for brush cleaning a surface of a substrate. The method comprises scrubbing a first surface of the substrate with a brush having a first surface geometry; and then scrubbing the first surface of the substrate with a brush having a second surface geometry, wherein the first and the second surface geometries are different. Numerous other aspects are provided.

Post CMP scrubbing of substrates

Embodiments of the present invention generally relate to an apparatus and methods for rinsing and drying substrates. One embodiment provides an end effector comprising a body having a contact tip for contacting an edge area of a substrate, wherein the end effector is configured to support the substrate while the substrate is in a rinsing bath and while the substrate is being dried from the rinsing bath, and the contact tip comprises a hydrophilic material.

Vapor dryer having hydrophilic end effector

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San Jose, CA, United States of America

Garrett H Sin