Lam Research Corporation

Hossein Sadeghi

Richard Alan Gottscho

Richard M Blank

Peter S Thaulad

Mark E Emerson

Scott Baldwin

Arulselvam Simon Jeyapalan

Marco Piccigallo

At least one laser sensor and a controller are embedded into a substrate processing system communicating with a remote big data and machine learning server receiving/sending data from/to a fleet of substrate processing systems for autonomous process control and optimization. The laser sensor is arranged proximate to a region of the substrate processing system and is configured to capture first data from at least one of an edge coupling ring and a semiconductor substrate transported from/to the processing chamber to/from the region. The controller is configured to receive the first data from the laser sensor, process the first data to generate second data, transmit the second data to a remote server via a network, receive third data from the remote server via the network in response to sending the second data to the remote server, and operate the substrate processing system based on the third data for process optimization.

Systems and methods for autonomous process control and optimization of semiconductor equipment using light interferometry and reflectometry

Systems and techniques for determining and using multiple types of offsets for providing wafers to a wafer support of a wafer station of a semiconductor processing tool are disclosed; such techniques and systems may use an autocalibration wafer that may include a plurality of sensors, including a plurality of edge-located imaging sensors that may be used to image fiducials associated with two different structures located in a selected wafer station.

Integrated adaptive positioning systems and routines for automated wafer-handling robot teach and health check

A sorption structure used in a plasma process chamber includes an inner layer having one or more heating elements to heat the sorption structure, a middle section having a lattice structure and a coolant flow delivery network through which a coolant circulates to cool the sorption structure, and a vacuum flow network that is connected to a vacuum line to create low pressure vacuum. The lattice structure includes network of openings defined in a plurality of layers. The inner layer is disposed adjacent to the middle section and an outer layer of the lattice structure faces an interior region of the chamber. The openings in the layers of the lattice structure progressively increase in size from the inner layer to the outer layer. The lattice structure is used to adsorb by-products released in the process chamber and the vacuum flow network is used to remove the by-products.

Sorption chamber walls for semiconductor equipment

A measurement system to measure at least one of a height and a thickness of an edge ring in a plasma processing chamber includes an ultrasound transducer configured to output an ultrasound signal into the edge ring and to receive a reflected signal from the edge ring. A controller is configured to cause the ultrasound transducer to generate the ultrasound signal and to determine a thickness of the edge ring based on timing of the ultrasound signal and the reflected signal.

Measurement system to measure a thickness of an adjustable edge ring for a substrate processing system

Systems and methods for real time semiconductor manufacturing cluster tool health monitoring are provided via an in-situ sensor. In a method embodiment, an operation procedure for pumping/venting load lock (LL), and LL doors facing vacuum transfer module (VTM) and equipment front end module (EFEM), sensor installation location and operation procedure, and data flow and analysis process are provided. The sensor provides real-time data and monitors airborne particle contamination on EFEM, load lock (LL), and VTM, and plurality of process modules (PMs) simultaneously by correlating door open/close time and vent/pump timing in the loadlock to the particle measurement data. The method further provides an operation for determining that a maintenance procedure is recommended on one of the EFEM, the LL, the VTM, or the plurality of PMs based on the real time measurement data, door state data, and using machine learning algorithms.

Growing community of inventors

Glendale, CA, United States of America

Hossein Sadeghi