Inventor

CHERIAN BENJAMIN

US52 patents

⚠️ This page may combine multiple inventors who share the name “CHERIAN BENJAMIN”. Patents are grouped by organization below to help distinguish them — per-person disambiguation is on the roadmap.

CHERIAN BENJAMIN

APPLIED MATERIALS INC

Acoustic emission monitoring and endpoint for chemical mechanical polishing

Detecting an excursion of a CMP component using time-based sequence of images and machine learning

Polishing apparatus using neural network for monitoring

Reducing noise in spectral data from polishing substrates

Limiting adjustment of polishing rates during substrate polishing

Adjustment of polishing rates during substrate polishing with predictive filters

Dynamic residue clearing control with in-situ profile control (ISPC)

Weighted regression of thickness maps from spectral data

Machine learning systems for monitoring of semiconductor processing

Control of processing parameters during substrate polishing using expected future parameter changes

Control of processing parameters during substrate polishing using constrained cost function

Determination of substrate layer thickness with polishing pad wear compensation

Control of processing parameters for substrate polishing with angularly distributed zones using cost function

Monitoring of polishing pad texture in chemical mechanical polishing

Spectrographic monitoring using a neural network

Applying dimensional reduction to spectral data from polishing substrates

Applying dimensional reduction to spectral data from polishing substrates

Multi-platen multi-head polishing architecture

Profile control with multiple instances of contol algorithm during polishing

Switching control algorithms on detection of exposure of underlying layer during polishing

Using a trained neural network for use in in-situ monitoring during polishing and polishing system

Machine vision as input to a CMP process control algorithm

Training spectrum generation for machine learning system for spectrographic monitoring

Path for probe of spectrographic metrology system

Profile control during polishing of a stack of adjacent conductive layers

Detecting an excursion of a CMP component using time-based sequence of images

Control substrate polishing using constrained cost function

Polishing apparatus using neural network for monitoring

Pressure signals with different frequencies during friction monitoring to provide spatial resolution

Control of processing parameters during substrate polishing using cost function

Control of processing parameters for substrate polishing with substrate precession

Pressure signals during motor torque monitoring to provide spatial resolution

Machine vision as input to a CMP process control algorithm

Training a machine learning system to detect an excursion of a CMP component using time-based sequence of images

Technique for training neural network for use in in-situ monitoring during polishing and polishing system

Determination of substrate layer thickness with polishing pad wear compensation

Detecting an excursion of a CMP component using time-based sequence of images

Trained neural network in in-situ monitoring during polishing and polishing system

Spectrographic monitoring using a neural network

Temperature-based in-situ edge assymetry correction during CMP

Technique for training neural network for use in in-situ monitoring during polishing and polishing system

Determining substrate orientation with acoustic signals

Determining substrate precession with acoustic signals

Training spectrum generation for machine learning system for spectrographic monitoring

Training spectrum generation for machine learning system for spectrographic monitoring

Machine learning systems for monitoring of semiconductor processing

Temperature-based assymetry correction during CMP and nozzle for media dispensing

In-situ monitoring to label training spectra for machine learning system for spectrographic monitoring

YENNIE GRAHAM

Machine learning systems for monitoring of semiconductor processing

QIAN JUN

Endpointing with selective spectral monitoring