Abstract:
A surface inspection system includes a beam source subsystem, a beam scanning subsystem, a workpiece movement subsystem, an optical collection and detection subsystem, and a processing subsystem. The processing subsystem has a channel formation capability for forming selected channels and developing channel output associated with each selected channel, with the channel output developed from collector output associated with at least one collection and detection module. Also, a spherical defect channel is described for detection of small spherical objects and defects with like geometries, using scattered light observed by the back collector output and P-polarized scattered light observed by wing collectors.
Abstract:
A surface inspection system, as well as related components and methods, are provided. The surface inspection system includes a beam source subsystem, a beam scanning subsystem, a workpiece movement subsystem, an optical collection and detection subsystem, and a processing subsystem. The signal processing subsystem comprises a series of data acquisition nodes, each dedicated to a collection detection module and a plurality of data reduction nodes, made available on a peer to peer basis to each data acquisition nodes. Improved methods for detecting signal in the presence of noise are also provided.
Abstract:
A population of data points each having three or more parameters associated therewith, such as multi-channel defect data from an optical scanner, are plotted in three dimensions, and grouping of data points are identified. Boundary surfaces are defined in the three-dimensional space for delineating groupings of data points. The different groupings correspond to different data classifications or types. Classification algorithms based on the boundary surfaces are defined. When applied to defect classification, the algorithms can be exported to an optical scanner for runtime classification of defects. An algorithm for identifying a particular grouping of data points can be defined as a Boolean combination of grouping rules from two or more different n-dimensional representations, where n can be either 2 or 3 for each representation.
Abstract:
A surface inspection system, as well as related components and methods, are provided. The surface inspection system includes a beam source subsystem, a beam scanning subsystem, a workpiece movement subsystem, an optical collection and detection subsystem, and a processing subsystem. Certain of these components, most notably the beam source subsystem, the beam scanning subsystem and the optical collection and detection subsystem are modular for ready field replacement and/or maintenance. The optical collection and detection system features wing collectors in the front quartersphere and back collectors in the back quartersphere for collected light scattered from the surface of the workpiece. This can greatly improve the measurement capabilities of the system. Also included is a method for detecting asymmetric defects using the wing collectors and back collectors.
Abstract:
A method for inspecting a surface of a workpiece comprises scanning an incident beam on the surface of the workpiece to impinge thereon to create reflected light and scattered light comprising light that is scattered from the surface upon impingement thereon by the incident beam; and determining an extent of a contribution to surface roughness from a component of the surface, with the component having a surface roughness spatial frequency range.
Abstract:
A surface inspection system, as well as related components and methods, are provided. The surface inspection system includes a beam source subsystem, a beam scanning subsystem, a workpiece movement subsystem, an optical collection and detection subsystem, and a processing subsystem. The signal processing subsystem comprises a series of data acquisition nodes, each dedicated to a collection detection module and a plurality of data reduction nodes, made available on a peer to peer basis to each data acquisition nodes. Improved methods for detecting signal in the presence of noise are also provided.
Abstract:
A population of data points each having three or more parameters associated therewith, such as multi-channel defect data from an optical scanner, are plotted in three dimensions, and groupings of data points are identified. Boundary surfaces are defined in the three-dimensional space for delineating groupings of data points. The different groupings correspond to different data classifications or types. Classification algorithms based on the boundary surfaces are defined. When applied to defect classification, the algorithms can be exported to an optical scanner for runtime classification of defects. An algorithm for identifying a particular grouping of data points can be defined as a Boolean combination of grouping rules from two or more different n-dimensional representations, where n can be either 2 or 3 for each representation.