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1. 发明申请

WO2011008688A3 SCANNER PERFORMANCE COMPARISON AND MATCHING USING DESIGN AND DEFECT DATA 审中-公开
标题翻译：扫描仪性能比较和匹配使用设计和缺陷数据
公开(公告)号：WO2011008688A3
公开(公告)日：2011-05-05
申请号：PCT/US2010041697
申请日：2010-07-12
申请人： KLA TENCOR CORP , PARK ALLEN , CHANG ELLIS , AOKI MASAMI , YOUNG CHRIS CHIH-CHIEN , PLIHAL MARTIN , VAN RIET MICHAEL JOHN
发明人： PARK ALLEN , CHANG ELLIS , AOKI MASAMI , YOUNG CHRIS CHIH-CHIEN , PLIHAL MARTIN , VAN RIET MICHAEL JOHN
IPC分类号： H01L21/66
CPC分类号： H01L22/12 , G03F7/70516 , G03F7/70625 , G03F7/70641 , G03F7/7065
摘要： A system and method of matching multiple scanners using design and defect data are described. A golden wafer is processed using a golden tool. A second wafer is processed using a second tool. Both tools provide focus/exposure modulation. Wafer-level spatial signatures of critical structures for both wafers can be compared to evaluate the behavior of the scanners. Critical structures can be identified by binning defects on the golden wafer having similar patterns. In one embodiment, the signatures must match within a certain percentage or the second tool is characterized as a "no match". Reticles can be compared in a similar manner, wherein the golden and second wafers are processed using a golden reticle and a second reticle, respectively.
摘要翻译：描述使用设计和缺陷数据匹配多个扫描仪的系统和方法。使用金色工具处理金色晶圆。使用第二工具处理第二晶片。两种工具都提供对焦/曝光调制。可以比较两个晶片的关键结构的晶片级空间特征，以评估扫描仪的行为。关键结构可以通过在具有相似图案的金色晶片上合并缺陷来识别。在一个实施例中，签名必须在一定百分比内匹配，或者第二工具被表征为“不匹配”。可以以类似的方式比较网状物，其中分别使用金色掩模版和第二掩模版来处理金色和第二晶片。

2. 发明公开

KR20180043394A 적응성 자동 결함 분류 审中-公开
公开(公告)号：KR20180043394A
公开(公告)日：2018-04-27
申请号：KR20187010844
申请日：2016-09-16
申请人： KLA TENCOR CORP
发明人： HE LI , PLIHAL MARTIN , YING HUAJUN , BHATIA ANADI , DANDIANA AMITOZ S , RAMINI RAMAKANTH
IPC分类号： H01L21/66
CPC分类号： G01N21/9501 , G01N2201/06113 , G01N2201/12 , G06N99/005
摘要： 적응성자동결함분류기를사용하여시료상에서검출되는결함을분류하기위한방법및 시스템이제공된다. 하나의방법은, 제1 로트결과의결함의상이한그룹에대해유저로부터수신되는분류및 제1 로트결과의모든결함을포함하는결함의트레이닝세트에기초하여결함분류기를생성하는단계를포함한다. 제1 및추가적인로트결과는결합되어누적로트결과를생성한다. 누적로트결과의결함은생성된결함분류기를사용하여분류된다. 결함중 임의의것이임계치미만의신뢰도를가지고분류되는경우, 결함분류기는, 유저로부터수신되는이들결함에대한분류및 저신뢰도분류결함을포함하는수정된트레이닝세트에기초하여수정된다. 그다음, 수정된결함분류기는추가적인누적로트결과의결함을분류하기위해사용된다.

3. 发明专利

SG11201902745RA OPTIMIZING TRAINING SETS USED FOR SETTING UP INSPECTION-RELATED ALGORITHMS 未知
公开(公告)号：SG11201902745RA
公开(公告)日：2019-05-30
申请号：SG11201902745R
申请日：2017-10-17
申请人： KLA TENCOR CORP
发明人： PLIHAL MARTIN , SOLTANMOHAMMADI ERFAN , PARAMASIVAM SARAVANAN , RAVU SAIRAM , JAIN ANKIT , SHEKKIZHAR SARATH , UPPALURI PRASANTI
IPC分类号： H01L21/66
摘要： INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property :::` , 111111101111 0 1110101011111 011101 0 011111H11 1111110011111111111111011110111111 Organization International Bureau (10) International Publication Number i (43) International Publication Date .....•\"\"- WO 2018/075547 Al 26 April 2018 (26.04.2018) WIP0 I PCT (51) International Patent Classification: (71) Applicant: KLA-TENCOR CORPORATION [US/US]; HO1L 21/66 (2006.01) Legal Department, One Technology Drive, Milpitas, Cali- fornia 95035 (US). (21) International Application Number: PCT/US2017/057029 (72) Inventors: PLIHAL, Martin; 2728 Alpina Ct., Pleasanton, (22) International Filing Date: California 94588 (US). SOLTANMOHAMMADI, Erfan; 17 October 2017 (17.10.2017) 215 Union Avenue, Apt. 455, Campbell, California 95008 (US). PARAMASIVAM, Saravanan; Plot No 13, Shah (25) Filing Language: English Avenue, Rajakilpakkam, Chennai 600073 (IN). RAVU, (26) Publication Language: English Sairam; KG2, Trinity Garden, Mettukuppam, Chennai 600096 (IN). JAIN, Ankit; 41 Skylark Drive, Ballston Spa, (30) Priority Data: New York 12020 (US). SHEKKIZHAR, Sarath; 2045 201641035490 17 October 2016 (17.10.2016) IN Latham Street, Apt. 3, Mountain View, California 94040 62/477,248 27 March 2017 (27.03.2017) US (US). UPPALURI, Prasanti; 13425 Kodiac Place, Sarato- 15/782,820 12 October 2017 (12.10.2017) US ga, California 95070 (US). (54) Title: OPTIMIZING TRAINING SETS USED FOR SETTING UP INSPECTION-RELATED ALGORITHMS = = _ = Computer subsystem(s) 102 1 = 1 = 1 = — = Computer subsystem 36 __ = = _ _ = — = 28 _ 26 20 24 \" 411 n 0 • 6 18 21 ss 34 / -10 = 1 A og I T EL VA 3 2 = 14 JO — 22 = = Fig. 1 1-1 (57) : Methods and systems for training an inspection-related algorithm are provided. One system includes one or more IN computer subsystems configured for performing an initial training of an inspection-related algorithm with a labeled set of defects thereby I generating an initial version of the inspection-related algorithm and applying the initial version of the inspection-related algorithm to c e ; an unlabeled set of defects. The computer subsystem(s) are also configured for altering the labeled set of defects based on results of the IN applying. The computer subsystem(s) may then iteratively re-train the inspection-related algorithm and alter the labeled set of defects --.., © until one or more differences between results produced by a most recent version and a previous version of the algorithm meet one GC or more criteria. When the one or more differences meet the one or more criteria, the most recent version of the inspection-related 1-1 C algorithm is outputted as the trained algorithm. ei C [Continued on next page] WO 2018/075547 Al MIDEDIMOMMIDIREEMOMMIIMIMMIIIIIIIIIIII11111111 (74) Agent: MCANDREWS, Kevin et al.; KLA-Tencor Corp., Legal Department, One Technology Drive, Milpitas, Cali- fornia 95035 (US). (81) Designated States (unless otherwise indicated, for every kind of national protection available): AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, KM, ML, MR, NE, SN, TD, TG). Published: — with international search report (Art. 21(3))

4. 发明专利

SG11201702921XA DYNAMIC BINNING FOR DIVERSIFICATION AND DEFECT DISCOVERY 未知
公开(公告)号：SG11201702921XA
公开(公告)日：2017-07-28
申请号：SG11201702921X
申请日：2015-10-19
申请人： KLA TENCOR CORP
发明人： PLIHAL MARTIN , ANANTHA VIDYASAGAR
IPC分类号： H01L21/66
摘要： Methods and systems for generating a defect sample for a wafer are provided. One method includes separating defects detected on a wafer into bins having diversity in values of a first set of one or more first attributes of the defects. The method also includes selecting, independently from one or more of the bins, defects within the bins based on diversity in a second set of one or more second attributes of the defects. The selected defects are then used to create a defect sample for the wafer. In this manner, defects having diverse values of multiple attributes can be easily selected.

5. 发明专利

SG11201703560VA WAFER DEFECT DISCOVERY 未知
公开(公告)号：SG11201703560VA
公开(公告)日：2017-05-30
申请号：SG11201703560V
申请日：2015-11-04
申请人： KLA TENCOR CORP
发明人： CHEN HONG , WU KENONG , PLIHAL MARTIN , PANDITA VIDUR , SANAPALA RAVIKUMAR , BHAGAT VIVEK , LAKHAWAT RAHUL , BARIS OKSEN , RAMACHANDRAN RAJESH , HAQUE NOASHIN
IPC分类号： H01L21/66
摘要： Systems and methods for discovering defects on a wafer are provided. One method includes detecting defects on a wafer by applying a threshold to output generated by a detector in a first scan of the wafer and determining values for features of the detected defects. The method also includes automatically ranking the features, identifying feature cut-lines to group the defect into bins, and, for each of the bins, determining one or more parameters that if applied to the values for the features of the defects in each of the bins will result in a predetermined number of the defects in each of the bins. The method also includes applying the one or more determined parameters to the output generated by the detector in a second scan of the wafer to generate a defect population that has a predetermined defect count and is diversified in the values for the features.

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