IP Library › Granted Patent US 12,654,315
Granted Patent B2
US 12,654,315 · App. 18/961,702 · Granted Jun 16, 2026

Substrate processing apparatus and substrate alignment method using the same

Inventors: Daejung Kim (Seoul, KR); Minyoung Kang (Seoul, KR); Sungsoo Kim (Yongin-si, KR); Sohee Kim (Sejong-si, KR); Yongsoo Yoo (Daegu, KR)
Assignee: SAMSUNG ELECTRONICS CO., LTD.
B25J9/163B25J9/1684B25J9/1697B25J11/0095B25J19/021
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,654,315
App. No.
18/961,702
Granted
Jun 16, 2026
Kind
B2
Abstract

A method includes performing a substrate processing process by carrying a substrate into a chamber, and disposing the substrate in a loading region of the chamber, capturing an image of a lower surface of the substrate to acquire a first image, identifying particle patterns formed on the lower surface of the substrate in the substrate processing process, and an edge of the substrate, from the first image, calculating a first alignment error value of a deviation between an approximate position value for the center of the loading region calculated from the particle patterns and an approximate position value for a center of the substrate calculated from the edge of the substrate, and determining a point in time for teaching a transfer robot that deposits the substrate into the chamber, based on the first alignment error value.

Claims (82)

1 . A substrate processing apparatus comprising:

a chamber having an internal space in which a substrate processing process for processing a substrate is performed;

an electrostatic chuck that is disposed in the internal space and that has a loading region in which a lower surface of the substrate is seated and an instrument is disposed;

an image capturing device that acquires a first image by capturing an image of the lower surface of the substrate on which the substrate processing process is performed;

a sensor module that is carried into the internal space, is seated in the loading region, and acquires a second image by capturing an image of the loading region;

a transfer robot that carries the sensor module and the substrate into and out of the internal space; and

a controller that is configured to:

identify particle patterns formed on the lower surface of the substrate by the instrument during the substrate processing process and an edge of the substrate, from the first image,

calculate a first alignment error value of a deviation between an approximate position value for a center of the loading region from the particle patterns and calculate a center of the substrate from the edge of the substrate,

determine a point in time for carrying the sensor module into the internal space, based on the first alignment error value,

detect an edge of the loading region from the second image,

calculate a precise position value for the center of the loading region from the edge of the loading region,

calculate a second alignment error value by comparing the precise position value with a reference position value, and

correct the second alignment error value by teaching the transfer robot.

2 . The substrate processing apparatus of claim 1 , wherein the loading region is an upper surface of the electrostatic chuck disposed in the chamber.

3 . The substrate processing apparatus of claim 1 , wherein the particle patterns are formed at a position corresponding to a position in which the instrument is disposed.

4 . The substrate processing apparatus of claim 1 ,

the electrostatic chuck further comprises:

a first ring arranged on the outer side of the instrument on the electrostatic chuck; and

a second ring surrounding the first ring.

5 . The substrate processing apparatus of claim 1 , wherein the sensor module comprises a plurality of image scanning modules,

wherein the plurality of image scanning modules capture images of portions of the edge of the loading region, respectively.

6 . The substrate processing apparatus of claim 1 , wherein the sensor module has a shape that is substantially identical to a shape of the substrate.

7 . The substrate processing apparatus of claim 6 , wherein a thickness of the sensor module is about 5 mm or less.

8 . The substrate processing apparatus of claim 1 , wherein the sensor module captures an image of an upper surface of the electrostatic chuck.

9 . The substrate processing apparatus of claim 1 , further comprising an upper electrode disposed at an upper portion within the chamber, and

the electrostatic chuck comprises:

a base body functioning as a lower electrode; and

a plate on the base body, the plate comprises an electrode therein and provides the loading region.

10 . The substrate processing apparatus of claim 1 ,

the controller is configured to:

acquire a first reference image by capturing an image of the lower surface of the substrate, before the substrate processing process is performed.

11 . The substrate processing apparatus of claim 10 ,

the controller is configured as follows to calculate the approximate position value:

identify a common pattern that is commonly disposed in the first reference image and the first image, among the particle patterns;

remove the common pattern from the particle patterns; and

calculate the approximate position value for the center of the loading region based on the first reference image and the first image from which the common pattern is removed.

12 . The substrate processing apparatus of claim 1 ,

the controller is configured as follows to calculate the approximate position value:

calculate a trace that connects centers of the particle patterns; and

calculate a center of the trace as the approximate position value for the center of the loading region.

13 . The substrate processing apparatus of claim 1 ,

the controller is further configured to:

store the second alignment error value in a database after determining to teach the transfer robot.

14 . The substrate processing apparatus of claim 1 , wherein the chamber comprises a plurality of chambers, and

the controller is further configured to:

predict a chamber that requires teaching of the transfer robot, among the plurality of chambers, by applying machine learning to information stored in a database, before determining the point in time for carrying the sensor module into the internal space.

15 . A substrate processing apparatus comprising:

a chamber having an internal space in which a substrate processing process for processing a substrate is performed;

an electrostatic chuck that is disposed in the internal space and that has a loading region in which a lower surface of the substrate is seated and an instrument is disposed;

an image capturing device that acquires a first image by capturing an image of the lower surface of the substrate on which the substrate processing process is performed;

a transfer robot that carries the substrate into and out of the internal space; and

a controller that is configured to:

identify particle patterns formed on the lower surface of the substrate by the instrument during the substrate processing process and an edge of the substrate, from the first image,

calculate a first alignment error value of a deviation between a first approximate position value for a center of the loading region from the particle patterns and calculate a center of the substrate from the edge of the substrate, and

determine a point in time for teaching the transfer robot, based on the first alignment error value.

16 . The substrate processing apparatus of claim 15 , further comprising a sensor module that is carried into the internal space, is seated in the loading region, and

wherein the controller is further configured to, before the point in time for teaching the transfer robot:

capture an image of the loading region using the sensor module to acquire a second image;

extract an edge of the loading region from the second image,

calculate a precise position value for the center of the loading region from the edge of the loading region, and

calculate a second alignment error value of a deviation between the precise position value and a pre-stored reference position value; and

wherein the point in time for teaching the transfer robot is based on the second alignment error value.

17 . The substrate processing apparatus of claim 16 , wherein the substrate is a wafer, and

the sensor module has a shape that is substantially identical to a shape of the substrate.

18 . A substrate processing apparatus comprising:

a chamber having an internal space in which a substrate processing process for processing a substrate is performed;

an electrostatic chuck that is disposed in the internal space and that has a loading region in which a lower surface of the substrate is seated and an instrument is disposed;

an image capturing device that acquires a first image by capturing an image of the lower surface of the substrate on which the substrate processing process is performed;

a transfer robot that carries the substrate into and out of the internal space; and

a controller that is configured to:

identify particle patterns formed on the lower surface of the substrate by the instrument during the substrate processing process and an edge of the substrate, from the first image,

calculate an approximate position value for a center of the loading region from the particle patterns and calculate a center of the substrate from the edge of the substrate,

calculate a first alignment error value of a deviation between the approximate position value for the center of the loading region and the center of the substrate,

determine whether to carry a sensor module into the chamber, based on the first alignment error value,

when it is determined to carry the sensor module into the chamber, the sensor module is carried into the chamber, the sensor module is disposed in the loading region, and a second image of the loading region is captured by the sensor module,

extract an edge of the loading region from the second image,

calculate a precise position value for the center of the loading region from the edge of the loading region,

calculate a second alignment error value of a deviation between the precise position value and a pre-stored reference position value, and

determine a point in time for teaching the transfer robot based on the second alignment error value.

19 . The substrate processing apparatus of claim 18 , when the first alignment error value is within a pre-stored error range, it is determined to carry the sensor module.

20 . The substrate processing apparatus of claim 18 , when the first alignment error value is not within of a pre-stored error range, it is determined to hold carrying of the sensor module.

Priority Claims (1)
KR 10-2022-0024592 · Feb 24, 2022 · national
Continuity (2)
Continuation 17957967 · Sep 30, 2022
Related Publication 20250091203A1 · Mar 20, 2025
References Cited (225)
US 4326332A · Kenney · 1982 [cited by applicant]
US 4362486A · Davis et al. · 1982 [cited by applicant]
US 4364074A · Garnache et al. · 1982 [cited by applicant]
US 4399205A · Bergendahl · 1983 [cited by applicant]
US 4513203A · Bohlen et al. · 1985 [cited by applicant]
US 4668045A · Melman et al. · 1987 [cited by applicant]
US 4743953A · Toyokura et al. · 1988 [cited by applicant]
US 4835078A · Harvey et al. · 1989 [cited by applicant]
US 4904087A · Harvey et al. · 1990 [cited by applicant]
US 5042709A · Cina et al. · 1991 [cited by applicant]
US 5093740A · Dorschner et al. · 1992 [cited by applicant]
US 5138429A · Nagesh et al. · 1992 [cited by applicant]
US 5229331A · Doan et al. · 1993 [cited by applicant]
US 5257336A · Dautartas · 1993 [cited by applicant]
US 5274575A · Abe · 1993 [cited by applicant]
US 5275897A · Nagesh et al. · 1994 [cited by applicant]
US 5333166A · Seligson et al. · 1994 [cited by applicant]
US 5372973A · Doan et al. · 1994 [cited by applicant]
US 5413489A · Switky · 1995 [cited by applicant]
US 5436571A · Karasawa · 1995 [cited by applicant]
US 5469263A · Waldo, III et al. · 1995 [cited by applicant]
US 5552916A · O'Callaghan et al. · 1996 [cited by applicant]
US 5573963A · Sung · 1996 [cited by applicant]
US 5610930A · Macomber et al. · 1997 [cited by applicant]
US 5631987A · Lasky et al. · 1997 [cited by applicant]
US 5679125A · Hiraiwa et al. · 1997 [cited by applicant]
US 5723374A · Huang et al. · 1998 [cited by applicant]
US 5759867A · Armacost et al. · 1998 [cited by applicant]
US 5792680A · Sung et al. · 1998 [cited by applicant]
US 5808805A · Takahashi · 1998 [cited by applicant]
US 5835285A · Matsuzawa et al. · 1998 [cited by applicant]
US 5842300A · Cheshelski et al. · 1998 [cited by applicant]
US 5859947A · Kiryuscheva et al. · 1999 [cited by applicant]
US 5861997A · Takahashi · 1999 [cited by applicant]
US 5872042A · Hsu et al. · 1999 [cited by applicant]
US 5911108A · Yen · 1999 [cited by applicant]
US 5940564A · Jewell et al. · 1999 [cited by applicant]
US 5972753A · Lin et al. · 1999 [cited by applicant]
US 5995688A · Aksyuk et al. · 1999 [cited by applicant]
US 5998252A · Huang · 1999 [cited by applicant]
US 5999333A · Takahashi · 1999 [cited by applicant]
US 6013954A · Hamajima · 2000 [cited by applicant]
US 6045426A · Wang et al. · 2000 [cited by applicant]
US 6084723A · Matsuzawa et al. · 2000 [cited by applicant]
US 6087283A · Jinbo et al. · 2000 [cited by applicant]
US 6140220A · Lin · 2000 [cited by applicant]
US 6180977B1 · Lin et al. · 2001 [cited by applicant]
US 6184104B1 · Tan et al. · 2001 [cited by applicant]
US 6189339B1 · Hiraiwa · 2001 [cited by applicant]
US 6204134B1 · Shih · 2001 [cited by applicant]
US 6206272B1 · Waldron-Floyde et al. · 2001 [cited by applicant]
US 6207532B1 · Lin et al. · 2001 [cited by applicant]
US 6242318B1 · Mugibayashi et al. · 2001 [cited by applicant]
US 6243508B1 · Jewell et al. · 2001 [cited by applicant]
US 6266472B1 · Norwood et al. · 2001 [cited by applicant]
US 6348733B1 · Lin · 2002 [cited by applicant]
US 6350680B1 · Shih et al. · 2002 [cited by applicant]
US 6352904B2 · Tan et al. · 2002 [cited by applicant]
US 6365059B1 · Pechenik · 2002 [cited by applicant]
US 6400038B2 · Mugibayashi et al. · 2002 [cited by applicant]
US 6406994B1 · Ang et al. · 2002 [cited by applicant]
US 6421474B2 · Jewell et al. · 2002 [cited by applicant]
US RE37846E · Matsuzawa et al. · 2002 [cited by applicant]
US 6492269B1 · Liu et al. · 2002 [cited by applicant]
US 6503770B1 · Ho et al. · 2003 [cited by applicant]
US 6509264B1 · Li et al. · 2003 [cited by applicant]
US 6518210B1 · Jinbo et al. · 2003 [cited by applicant]
US 6521530B2 · Peters et al. · 2003 [cited by applicant]
US 6541346B2 · Malik · 2003 [cited by applicant]
US 6542672B2 · Jewell et al. · 2003 [cited by applicant]
US 6579407B1 · Boyd et al. · 2003 [cited by applicant]
US 6623911B1 · Jong et al. · 2003 [cited by applicant]
US 6648204B2 · Waldron-Floyde et al. · 2003 [cited by applicant]
US RE38421E · Takahashi · 2004 [cited by applicant]
US RE38438E · Takahashi · 2004 [cited by applicant]
US 6690185B1 · Khandros et al. · 2004 [cited by applicant]
US 6735492B2 · Conrad et al. · 2004 [cited by applicant]
US 6741777B2 · Jewell et al. · 2004 [cited by applicant]
US 6742980B2 · Sasaki · 2004 [cited by applicant]
US 6819426B2 · Sezginer et al. · 2004 [cited by applicant]
US 6894362B2 · Malik · 2005 [cited by applicant]
US 6907178B2 · Lerner et al. · 2005 [cited by applicant]
US 6931181B2 · Jewell et al. · 2005 [cited by applicant]
US 6933523B2 · Sheck · 2005 [cited by applicant]
US 6955984B2 · Wan et al. · 2005 [cited by applicant]
US 6959024B2 · Paldus et al. · 2005 [cited by applicant]
US RE39024E · Takahashi · 2006 [cited by applicant]
US 7025854B2 · Boyd et al. · 2006 [cited by applicant]
US 7034854B2 · Cruchon-Dupeyrat et al. · 2006 [cited by applicant]
US 7042569B2 · Sezginer et al. · 2006 [cited by applicant]
US 7298496B2 · Hill · 2007 [cited by applicant]
US 7324216B2 · Hill · 2008 [cited by applicant]
US 7359043B2 · Tsuchiya et al. · 2008 [cited by applicant]
US 7375809B2 · Seipp · 2008 [cited by applicant]
US 7431705B2 · Wilkins · 2008 [cited by applicant]
US 7486878B2 · Chen et al. · 2009 [cited by applicant]
US 7508034B2 · Takafuji et al. · 2009 [cited by applicant]
US 7522267B2 · Hofsmeister et al. · 2009 [cited by applicant]
US 7545497B2 · Seipp · 2009 [cited by applicant]
US 7623698B2 · Soenksen et al. · 2009 [cited by applicant]
US 7644489B2 · Arora et al. · 2010 [cited by applicant]
US 7650029B2 · Picciotto et al. · 2010 [cited by applicant]
US 7762638B2 · Cruchon-Dupeyrat et al. · 2010 [cited by applicant]
US 7942622B2 · Kondoh et al. · 2011 [cited by applicant]
US 8053894B2 · Wan et al. · 2011 [cited by applicant]
US 8106349B2 · Ding et al. · 2012 [cited by applicant]
US 8207058B1 · Fedorov et al. · 2012 [cited by applicant]
US 8260461B2 · Krishnasamy et al. · 2012 [cited by applicant]
US 8289388B2 · Cheng et al. · 2012 [cited by applicant]
US 8378414B2 · Miller et al. · 2013 [cited by applicant]
US 8421161B2 · Iwamoto · 2013 [cited by applicant]
US 8459922B2 · Hosek · 2013 [cited by applicant]
US 8515294B2 · Britz et al. · 2013 [cited by applicant]
US 8531029B2 · Fedorov et al. · 2013 [cited by applicant]
US 8546717B2 · Stecker · 2013 [cited by applicant]
US 8632295B2 · Onishi et al. · 2014 [cited by applicant]
US 8740535B2 · Kondoh et al. · 2014 [cited by applicant]
US 8755316B2 · Aschan et al. · 2014 [cited by applicant]
US 8767199B2 · Dozor et al. · 2014 [cited by applicant]
US 8892248B2 · Hosek · 2014 [cited by applicant]
US 8967935B2 · Goodman et al. · 2015 [cited by applicant]
US 9024456B2 · Yang et al. · 2015 [cited by applicant]
US 9035267B2 · Maxwell et al. · 2015 [cited by applicant]
US 9106344B2 · Britz et al. · 2015 [cited by applicant]
US 9228270B2 · Feng et al. · 2016 [cited by applicant]
US 9338788B2 · Britz et al. · 2016 [cited by applicant]
US 9399264B2 · Stecker · 2016 [cited by applicant]
US 9422651B2 · Roberts et al. · 2016 [cited by applicant]
US 9424646B2 · Ikeda et al. · 2016 [cited by applicant]
US 9543178B2 · Lee et al. · 2017 [cited by applicant]
US 9543223B2 · Habets · 2017 [cited by applicant]
US 9547143B2 · Frederick et al. · 2017 [cited by applicant]
US 9568826B2 · Fujiwara · 2017 [cited by applicant]
US 9574290B2 · Roberts et al. · 2017 [cited by applicant]
US 9728168B2 · Mitani et al. · 2017 [cited by applicant]
US 9911701B2 · Fujiwara · 2018 [cited by applicant]
US 9915520B2 · Cable et al. · 2018 [cited by applicant]
US 9941217B2 · Shiba et al. · 2018 [cited by applicant]
US 9988734B2 · Feng et al. · 2018 [cited by applicant]
US 10065340B2 · Moyal · 2018 [cited by applicant]
US 10066311B2 · Ostrowski et al. · 2018 [cited by applicant]
US 10124367B2 · Roberts et al. · 2018 [cited by applicant]
US 10145026B2 · D'Evelyn et al. · 2018 [cited by applicant]
US 10189114B2 · Stecker · 2019 [cited by applicant]
US 10234267B2 · Cable et al. · 2019 [cited by applicant]
US 10236259B2 · Shiba et al. · 2019 [cited by applicant]
US 10295914B2 · Habets · 2019 [cited by applicant]
US 10338472B2 · Fujiwara · 2019 [cited by applicant]
US 10435807B2 · Feng et al. · 2019 [cited by applicant]
US 10461039B2 · Shiba et al. · 2019 [cited by applicant]
US 10585362B2 · Kuwahara · 2020 [cited by applicant]
US 10604865B2 · D'Evelyn et al. · 2020 [cited by applicant]
US 10661304B2 · Roberts et al. · 2020 [cited by applicant]
US 10739688B2 · Habets · 2020 [cited by applicant]
US 10847393B2 · Potter et al. · 2020 [cited by applicant]
US 10902350B2 · Banerjee et al. · 2021 [cited by applicant]
US 10908045B2 · Coulter et al. · 2021 [cited by applicant]
US 10926756B2 · Dastous et al. · 2021 [cited by applicant]
US 10935957B2 · Kashiwagi et al. · 2021 [cited by applicant]
US 10978330B2 · Yin et al. · 2021 [cited by applicant]
US 11094569B2 · Sato · 2021 [cited by applicant]
US 11165514B2 · Balteanu et al. · 2021 [cited by applicant]
US 20010035400A1 · Gartner et al. · 2001 [cited by applicant]
US 20030119649A1 · Jinbo et al. · 2003 [cited by applicant]
US 20030124844A1 · Li et al. · 2003 [cited by applicant]
US 20030235226A1 · Ueki · 2003 [cited by applicant]
US 20050074047A1 · Boggy et al. · 2005 [cited by applicant]
US 20050243884A1 · Paldus et al. · 2005 [cited by applicant]
US 20060174753A1 · Aisenbrey · 2006 [cited by applicant]
US 20070108638A1 · Lane et al. · 2007 [cited by applicant]
US 20070228425A1 · Miller et al. · 2007 [cited by applicant]
US 20080203536A1 · Furukawa et al. · 2008 [cited by applicant]
US 20090078562A1 · Johnson et al. · 2009 [cited by applicant]
US 20090095956A1 · Takafuji et al. · 2009 [cited by applicant]
US 20100242765A1 · Cruchon-Dupeyrat et al. · 2010 [cited by applicant]
US 20110019876A1 · Galoppo · 2011 [cited by examiner]
US 20110075123A1 · Nagamori · 2011 [cited by applicant]
US 20110190927A1 · Douki · 2011 [cited by applicant]
US 20110245964A1 · Sullivan et al. · 2011 [cited by applicant]
US 20110249025A1 · Mitani et al. · 2011 [cited by applicant]
US 20110282484A1 · Amano · 2011 [cited by examiner]
US 20110297141A1 · Correia et al. · 2011 [cited by applicant]
US 20110311722A1 · Faris · 2011 [cited by applicant]
US 20120012972A1 · Takafuji et al. · 2012 [cited by applicant]
US 20120034591A1 · Morse, III et al. · 2012 [cited by applicant]
US 20130119106A1 · Moyal · 2013 [cited by applicant]
US 20130176519A1 · Hayama et al. · 2013 [cited by applicant]
US 20130179236A1 · Hicyilmaz et al. · 2013 [cited by applicant]
US 20130181339A1 · Fan et al. · 2013 [cited by applicant]
US 20150212377A1 · Imaoku et al. · 2015 [cited by applicant]
US 20150219560A1 · Maxwell et al. · 2015 [cited by applicant]
US 20160148366A1 · Amano · 2016 [cited by applicant]
US 20160370797A1 · Azarya et al. · 2016 [cited by applicant]
US 20180345316A1 · Roberts et al. · 2018 [cited by applicant]
US 20180347065A1 · Feng et al. · 2018 [cited by applicant]
US 20180363162A1 · Ostrowski et al. · 2018 [cited by applicant]
US 20190046373A1 · Coulter et al. · 2019 [cited by applicant]
US 20190143445A1 · Stecker · 2019 [cited by applicant]
US 20190172742A1 · Mohcizuki · 2019 [cited by applicant]
US 20190184480A1 · Auyeung et al. · 2019 [cited by applicant]
US 20200246939A1 · Kashiwagi et al. · 2020 [cited by applicant]
US 20200254625A1 · Rogers · 2020 [cited by applicant]
US 20200292766A1 · Vermeulen et al. · 2020 [cited by applicant]
US 20200350258A1 · Lee et al. · 2020 [cited by applicant]
US 20210008591A1 · Lindefjeld et al. · 2021 [cited by applicant]
US 20210028800A1 · Balteanu et al. · 2021 [cited by applicant]
US 20210131874A1 · Xu · 2021 [cited by applicant]
US 20210145665A1 · Coulter et al. · 2021 [cited by applicant]
US 20210170584A1 · Kopec · 2021 [cited by examiner]
US 20210186454A1 · Behzadi et al. · 2021 [cited by applicant]
US 20210275129A1 · Behzadi et al. · 2021 [cited by applicant]
US 20210276540A1 · Dastous et al. · 2021 [cited by applicant]
US 20210384058A1 · Harada et al. · 2021 [cited by applicant]
US 20220020575A1 · Kwon · 2022 [cited by examiner]
US 20220148857A1 · Amikura · 2022 [cited by examiner]
CN 111640694B · 2021 [cited by applicant]
KR 100246850B1 · 2000 [cited by applicant]
KR 101977755B1 · 2019 [cited by applicant]
KR 102125839A · 2020 [cited by applicant]
KR 1020210027647A · 2021 [cited by applicant]
KR 1020210150283A · 2021 [cited by applicant]
KR 1020210155192A · 2021 [cited by applicant]
KR 1020220021897A · 2022 [cited by applicant]
KR 102721980B1 · 2024 [cited by applicant]
US 9,871,003 B2, 01/2018, Fujiwara (withdrawn) [cited by applicant]