Applied Materials Israel Limited

Moshe Amzaleg

Efrat Rozenman

Yehuda Cohen

Nir Ben-David Dodzin

Zvi Goren

Saar Shabtay

Eyal Neistein

Ariel Shkalim

Elad Cohen

Nir Ben-David Dodzen

Ofer Adan

Mark Geshel

Vered Gatt

Nir Ben David Dodzin

Yair Hanani

Limor Martin

Shlomo Tubul

Karen Pomeranz

Vivek Balasubramanian

Eyal Bassa

Inspection data that corresponds to potential defects of an object may be received. A first set of locations of first potential defects can be identified. The first set of locations of the first potential defects can be imaged with a review tool to obtain a first set of review images. The first potential defects can be classified based on the first set of review images to obtain first classification results of the first potential defects. An instruction can be determined for the review tool based on the first classification results, the instruction being associated with detecting potential defects. Using the instruction, a second set of locations of second potential defects of the plurality of potential defects to be imaged with the review tool can be identified.

System, method and computer program product for object examination

A system, computer program product and a method for detecting manufacturing process defects, the method may include: obtaining multiple edge measurements of one or more structural elements after a completion of each one of multiple manufacturing phases; generating spatial spectrums, based on the multiple edge measurements, for each one of the multiple manufacturing phases; determining relationships between bands of the spatial spectrums; and identifying at least one of the manufacturing process defects based on the relationships between the bands of the spatial spectrums.

Method, computer program product and system for detecting manufacturing process defects

Inspection data that corresponds to potential defects of an object may be received. A first set of locations of first potential defects can be identified. The first set of locations of the first potential defects can be imaged with a review tool to obtain a first set of review images. The first potential defects can be classified based on the first set of review images to obtain first classification results of the first potential defects. A determination can be made as to whether an examination stopping criteria has been satisfied. In response to determining that the examination stopping criteria has not been satisfied, a second set of locations of second potential defects can be identified to be imaged with the review tool to obtain a second set of review images. The second set of locations can be different than the first set of locations.

A computerized method for estimating a size of a nanometric part of an inspected article, the method including: (a) acquiring inspection results generated by processing an inspection image which was generated by collecting signals arriving from a portion of the article which includes the part by an inspection system; (b) fitting to the inspection results an approximation function from a group of functions which is related to a response pattern of the inspection system; and (c) determining an estimated size of the part, based on at least one parameter of the approximation function.

System, a method and a computer program product for size estimation

There are provided system and method of detecting defects on a specimen, the method comprising: capturing a first image from a first die and obtaining one or more second images; receiving: i) a first set of predefined first descriptors each representing a type of DOI, and ii) a second set of predefined second descriptors each representing a type of noise; generating at least one difference image based on difference between pixel values of the first image and pixel values derived from the second images; generating at least one third image, comprising: computing a value for each given pixel of at least part of the at least one difference image based on the first and second sets of predefined descriptors, and surrounding pixels centered around the given pixel; and determining presence of defect candidates based on the at least one third image and a predefined threshold.

Method of defect detection and system thereof

Examination system, method and computer-readable medium, the method comprising: processing by a processor using a first recipe at least one image comprised in images and metadata generated by an inspection tool and stored, to detect a first location set of first potential defects and attributes thereof; selecting and imaging part of the first location set with a review tool to obtain an image set; obtaining classification results of said first potential defects and determining a further recipe based thereon; processing the image using the further recipe for detecting a further location set of further defects; selecting part of the further location set; imaging the part with the review tool to obtain a further image set, and obtaining further classification results; and repeating determining the further recipe, processing the image, selecting and imaging part of the further location set, and obtaining further classification results, until a stopping criteria is met.

There are provided system and method of generating an examination recipe usable for examining a specimen, the method comprising: capturing images from dies and obtaining noise map indicative of noise distribution on the images; receiving design data representative of a plurality of design groups each having the same design pattern; calculating a group score for each given design group, the group score calculated based on the noise data associated with the given design group and a defect budget allocated for area of the given design group; providing segmentation related to the dies, comprising: associating design groups with segmentation labels indicative of different noise levels based on the group score, thereby obtaining a set of die segments each corresponding to one or more design groups associated with the same segmentation label and segmentation configuration data; and generating an examination recipe using the segmentation configuration data.

Method of generating an examination recipe and system thereof

A system configured to detect defects in an inspection image generated by collecting signals arriving from an article, the system comprising a tangible processor which includes: (i) a distribution acquisition module, configured to acquire a distribution of comparison values, each of the comparison values being indicative of a relationship between a value associated with a pixel of the inspection image and a corresponding reference value; (ii) a fitting module, configured to fit to the distribution an approximation function out of a predefined group of functions; and (iii) a defect detection module, configured to: (a) set a defect detection criterion based on a result of the fitting; and to (b) determine a presence of a defect in the inspection image, based on the defect detection criterion.

System, a method and a computer program product for fitting based defect detection

There are provided system and method of detecting repeating defects on a specimen, the specimen obtained by printing two or more mask fields thereon, each of mask field comprising multiple dies, the method comprising: scanning the specimen to capture a plurality of first images from first dies located at the same position in the mask fields, and, for each first image, capture two or more second images from dies located in different positions from the first dies; generating a plurality of third images corresponding to the plurality of first images; generating, an average third image constituted by pixels with values computed as accumulated pixel values of corresponding pixels in the plurality of third images divided by the number of the two or more mask fields; and determining presence of repeating defects on the specimen based on the average third image and a predefined defect threshold.

Method of detecting repeating defects and system thereof

A system including an interface for receiving inspection image data of an inspection image of an inspection object. The inspection image data includes information of an analyzed pixel of the inspected image and of reference pixels of the inspected image. The system further includes a memory and a processor device operatively coupled to the interface and the memory to obtain an inspected value representative of the analyzed pixel of the inspected image, and a reference value for each of the reference pixels of the inspected image. For each reference pixel, the processor devices calculates a difference between the reference value of a respective reference pixel and the inspected value of the analyzed pixel, computes a representative difference value based on the differences and determines a presence of a defect in the analyzed pixel based on the representative difference value.

System, method and computer program product for defect detection based on multiple references

Methods, systems, and computer program products for signature detection. One example of a method includes: acquiring an article defect density map comprising a plurality of sections corresponding to a first resolution level which is indicative of defect numbers for the sections, and determining a distribution representative of the defect numbers or function thereof; determining a threshold in accordance with said distribution, and identifying sections, out of said plurality of sections in the article defect density map, with defect numbers or function thereof above the threshold; and clustering at least part of adjoining identified sections, into one or more signatures, thus detecting said one or more signatures.

Systems, methods and computer program products for signature detection

A system includes a memory and a processor device operatively coupled to the memory to obtain an inspected noise-indicative value representative of an analyzed pixel of an inspected image of an inspected object, and a reference noise-indicative value representative for each of multiple reference pixels of the inspected image. The processor device computes a representative noise-indicative value based on the inspected noise-indicative value and multiple reference noise-indicative values, calculates a defect-indicative value based on an inspected value representative of the analyzed pixel and determines a presence of a defect in the analyzed pixel based on the representative noise-indicative value and the defect-indicative value.

Method, system, and computer program product for detection of defects based on multiple references

A system capable of inspecting an article for defects, the system including: a patch comparator, configured to determine with respect to each of a plurality of reference patches in a reference image a similarity level, based on a predefined patch-similarity criterion and on a source patch defined in the reference image; an evaluation module, configured to rate each inspected pixel out of multiple inspected pixels of the inspection image with a representative score which is based on the similarity level of a reference patch associated with a reference pixel corresponding to the inspected pixel; a selection module, configured to select multiple selected inspected pixels based on the representative scores of the multiple inspected pixels; and a defect detection module, configured to determine a presence of a defect in the candidate pixel based on an inspected value of the candidate pixel and inspected values of the selected inspected pixels.

System, a method and a computer program product for patch-based defect detection

A defect detection system for computerized detection of defects in an inspected object based on processing of an inspection image generated by collecting signals arriving from the inspected object, the system including: an interface for obtaining an inspected noise-indicative value and multiple reference noise-indicative values, the inspected noise-indicative value representative of an analyzed pixel and each of the reference noise-indicative values representative of a reference pixel among a plurality of reference pixels; and a processor, including: a noise analysis module, configured to compute a representative noise-indicative value based on a plurality of noise-indicative values which includes the inspected noise-indicative value and the multiple reference noise-indicative values; and a defect analysis module, configured to calculate a defect-indicative value based on an inspected value representative of the analyzed pixel, and to determine a presence of a defect in the analyzed pixel based on the representative noise-indicative value and the defect-indicative value.

A defect detection system for computerized detection of defects, the system including: an interface for receiving inspection image data including information of an analyzed pixel and of a plurality of reference pixels; and a processor, including: a differences analysis module, configured to: (a) calculate differences based on an inspected value representative of the analyzed pixel and on multiple reference values, each of which is representative of a reference pixel among the plurality of reference pixels; wherein the differences analysis module is configured to calculate for each of the reference pixels a difference between the reference value of the reference pixel and the inspected value; and (b) compute a representative difference value based on a plurality of the differences; and a defect analysis module, configured to determine a presence of a defect in the analyzed pixel based on the representative difference value.

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Beer Sheva, Israel

Moshe Amzaleg