International Business Machines Corporation

Justin Wai-chow Wong

Olivier Verscheure

Deepak Srinivas Turaga

Leping Li

Steven G Barbee

Lisa Amini

Eugene Henry Ratzlaff

Tony F Heinz

Yiping Hsiao

Naoki Abe

Srujana Merugu

Perry G Hartswick

Brian Christopher Barker

David L Jensen

Brian Douglas Pfeifer

June Cline

Ronald G Meunier

Edward Sumner Begle

Joseph P Walko

Kellie L Dutra

Gerett Raybourn Yocum

Michael J Balconi-Lamica

Robert A Calderoni

A technique for identifying a defect in an object produced by a controllable process. A first type of data generated as a result of production of the object by the controllable process is obtained. A second type of data generated as a result of production of the object by the controllable process is obtained. The first type of data and the second type of data are jointly analyzed. A defect is identified in the object based on the joint analysis of the first type of data and the second type of data. By way of example, the controllable process comprises a semiconductor manufacturing process such as a silicon wafer manufacturing process and the object produced by the semiconductor manufacturing process comprises a processed wafer. The first type of data comprises tool trace data and the second type of data comprises wafer image data. The tool trace data is generated by a photolithographic tool.

Multi-modal data analysis for defect identification

A technique for analyzing two or more data streams respectively generated from two or more components of a controllable process includes the following steps. In a first step, a statistical analysis is performed on each of the two or more data streams to generate first analysis results in the form of respective statistical results for the two or more data streams. In a second step, at least a portion of the statistical results from at least one of the two or more data streams is combined with at least a portion of the statistical results from at least another one of the two or more data streams to yield second analysis results. The controllable process is adjustable based on at least one of the first analysis results and the second analysis results.

Hierarchical and incremental multivariate analysis for process control

A method (and system) for causal modeling includes modeling a data set. The modeling includes estimating a reverse Bayesian forest for the data set and detecting outliers in a separate data set. Detecting the outliers includes applying the reverse Bayesian forest to the separate data set to obtain a probability value assigned to data points in the separate data set and identifying outliers in the separate data set by evaluating the probability value given by the reverse Bayesian forest.

Method and system for causal modeling and outlier detection

Disclosed is a method and system for detecting abnormal plasma discharge that is useful in, for example, detecting plasma leakage in a reactive ion etching (RIE) chamber. The system includes electrical contacts connected to the chamber that provide an input signal to the chamber. This input signal can be generated by a radio frequency (RF) generator that is connected to the electrical contacts. A variable power controller connected to the RF generator gradually increases (ramps) the power of the input signal being supplied to the chamber.

Measurement to determine plasma leakage

A contactless method and apparatus for real-time in-situ monitoring of a chemical etching process during etching of at least one wafer in a wet chemical etchant bath are disclosed. The method comprises the steps of providing two conductive electrodes in the wet chemical bath, wherein the two electrodes are proximate to but not in contact with a wafer; monitoring an electrical characteristic between the two electrodes as a function of time in the etchant bath of the at least one wafer, wherein a prescribed change in the electrical characteristic is indicative of a prescribed condition of the etching process; and recording a plurality of values of the electrical characteristic as a function of time during etching. From the plurality of recorded values and corresponding times, instantaneous etch rates, average etch rates, and etching end points may be determined. Such a method and the apparatus therefor are particularly useful in a wet chemical etch station.

Real time measurement of etch rate during a chemical etching process

A contactless method and apparatus for real-time in-situ monitoring of a chemical etching process for the etching of at least one wafer in a wet chemical etchant bath are disclosed. The method comprises the steps of providing at least two conductive electrodes in the wet chemical bath, wherein the at least two electrodes are proximate to but not in contact with the at least one wafer, and further wherein said two electrodes are positioned on the same side of the wafer; and monitoring an electrical characteristic between the at least two electrodes, wherein a prescribed change in the electrical characteristic is indicative of a prescribed condition of the etching process. Such a method and apparatus are particularly useful in a wet chemical etch station.

Contactless real-time in-situ monitoring of a chemical etching

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South Burlington, VT, United States of America

Justin Wai-chow Wong