# US 10,503,078 B2 · Criticality analysis augmented process window qualification sampling

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 10,503,078 B2
- Document ID: US10503078B2
- Status: Granted
- Kind: B2
- Application number: 15/903,841
- Filed: 2018-02-23
- Published: 2019-03-07
- Granted: 2019-12-10
- Earliest claimed: 2017-09-01
- Assignees: KLA-Tencor Corporation
- Applicants: Kla-Tencor Corporation
- Inventors: Jagdish Chandra Saraswatula; Saibal Banerjee; Ashok Kulkarni
- Web page: https://patentgrep.com/patent/US10503078B2

## CPC

- G03F 7/7065: {Defects, e.g. optical inspection of patterned layer for defects}
- G03F 1/84: Inspecting
- G01N 21/95607: {using a comparative method}
- G03F 7/70666: {Aerial image, i.e. measuring the image of the patterned exposure light at the image plane of the projection system}
- H10P 74/203: {Structural properties, e.g. testing or measuring thicknesses, line widths, warpage, bond strengths or physical defects}
- G03F: PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR; (phototypographic composing devices B41B; photosensitive materials or processes for photographic purposes G03C; electrophotography, sensitive layers or processes therefor G03G)
- G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q)
- H10P: GENERIC PROCESSES OR APPARATUS FOR THE MANUFACTURE OR TREATMENT OF DEVICES COVERED BY CLASS H10

## Abstract

Techniques are provided that can select defects based on criticality of design pattern as well as defect attributes for process window qualification (PWQ). Defects are sorted into categories based on process conditions and similarity of design. Shape based grouping can be performed on the random defects. Highest design based grouping scores can be assigned to the bins, which are then sorted. Particular defects can be selected from the bins. These defects may be reviewed.

## Claims

### Claim 1

A method comprising:
sorting, using a processor, defects from a plurality of design based grouping bins into a plurality of categories based on a plurality of process conditions;
sorting, using the processor, the defects based on similarity of design into a plurality of bins, wherein each of the bins includes at least one of the design based grouping bins;
selecting, using the processor, a random defect from the defects in each of the design based grouping bins;
performing, using the processor, shape based grouping on each of the random defects;
for each of the bins, selecting, using the processor, one of the design based grouping bins with a score on an end of a range of scores after the shape based grouping, wherein the score is a highest score or a lowest score;
assigning, using the processor, the respective score that was selected to each of the bins;
sorting, using the processor, the bins in order by the respective scores; and
selecting, using the processor, one of the defects with a highest defect attribute value from each of the bins for each of the plurality of process conditions.

### Claim 2 (depends on 1)

The method of claim 1, further comprising performing a review of a wafer using a scanning electron microscope after selecting the defects with the highest defect attribute value.

### Claim 3 (depends on 1)

The method of claim 1, further comprising:
re-ordering, using the processor, the defects, the bins, and the design based grouping bins; and
repeating assigning the respective score, sorting of the bins in order starting with the score, and selecting one of the defects with the highest defect attribute value.

### Claim 4 (depends on 3)

The method of claim 3, further comprising performing a review of a wafer using a scanning electron microscope after selecting the defects with the highest defect attribute value.

### Claim 5 (depends on 1)

The method of claim 1, wherein the plurality of categories includes four of the categories.

### Claim 6 (depends on 1)

The method of claim 1, wherein the plurality of process conditions include focus and exposure.

### Claim 7 (depends on 1)

The method of claim 1, wherein sorting the defects based on similarity of the design uses a bin merge algorithm.

### Claim 8 (depends on 1)

The method of claim 1, wherein prior to sorting the defects from the plurality of design based grouping bins the method further comprises:
grouping, using the processor, the defects into the design based grouping bins;
consolidating, using the processor, the design based grouping bins into the bins;
grouping, using the processor, the bins based on the plurality of process conditions; and
determining, using the processor, dies that indicate an inflection in defect count.

### Claim 9

A system comprising:
a processor in electronic communication with an electronic data storage unit and a wafer inspection tool, wherein the processor is configured to:
sort defects from a plurality of design based grouping bins into a plurality of categories based on a plurality of process conditions;
sort the defects based on similarity of design into a plurality of bins, wherein each of the bins includes at least one of the design based grouping bins;
select a random defect from the defects in each of the design based grouping bins;
perform shape based grouping on each of the random defects;
for each of the bins, select one of the design based grouping bins with a score on an end of a range of scores after the shape based grouping, wherein the score is a highest score or a lowest score;
assign the respective score that was selected to each of the bins;
sort the bins in order by the respective scores; and
select one of the defects with a highest defect attribute value from each of the bins for each of the plurality of process conditions.

### Claim 10 (depends on 9)

The system of claim 9, wherein the wafer inspection tool is a scanning electron microscope.

### Claim 11 (depends on 9)

The system of claim 9, wherein the processor is further configured to:
re-order the defects, the bins, and the design based grouping bins; and
repeat assigning the respective score, sorting of the bins in order starting with the score, and selecting one of the defects with the highest defect attribute value.

### Claim 12 (depends on 9)

The system of claim 9, wherein prior to sorting the defects from the plurality of design based grouping bins the processor is further configured to:
group the defects into the design based grouping bins;
consolidate the design based grouping bins into the bins;
group the bins based on the plurality of process conditions; and
determine dies that indicate an inflection in defect count.

### Claim 13

A non-transitory computer-readable storage medium, comprising one or more programs for executing the following steps on one or more computing devices:
sorting defects from a plurality of design based grouping bins into a plurality of categories based on a plurality of process conditions;
sorting the defects based on similarity of design into a plurality of bins using a bin merge algorithm, wherein each of the bins includes at least one of the design based grouping bins;
selecting a random defect from the defects in each of the design based grouping bins;
performing shape based grouping on each of the random defects;
for each of the bins, selecting one of the design based grouping bins with a score on an end of a range of scores after the shape based grouping, wherein the score is a highest score or a lowest score;
assigning the respective score that was selected to each of the bins;
sorting the bins in order by the respective scores; and
selecting one of the defects with a highest defect attribute value from each of the bins for each of the plurality of process conditions.

### Claim 14 (depends on 13)

The non-transitory computer-readable storage medium of claim 13, wherein the steps further include:
re-ordering the defects, the bins, and the design based grouping bins; and
repeating assigning the respective score, sorting of the bins in order starting with the score, and selecting one of the defects with the highest defect attribute value.

### Claim 15 (depends on 13)

The non-transitory computer-readable storage medium of claim 13, wherein the plurality of categories includes four of the categories.

### Claim 16 (depends on 13)

The non-transitory computer-readable storage medium of claim 13, wherein the plurality of process conditions include focus and exposure.

### Claim 17 (depends on 13)

The non-transitory computer-readable storage medium of claim 13, wherein sorting the defects based on similarity of the design uses a bin merge algorithm.

### Claim 18 (depends on 13)

The non-transitory computer-readable storage medium of claim 13, wherein prior to sorting the defects from the plurality of design based grouping bins the steps further include:
grouping the defects into the design based grouping bins;
consolidating the design based grouping bins into the bins;
grouping the bins based on the plurality of process conditions; and
determining dies that indicate an inflection in defect count.