Automated wafer defect inspection system and a process of performing such inspection

• US 9,337,071 B2
• Filed: 05/28/2010
• Issued: 05/10/2016
• Est. Priority Date: 07/15/1998
• Status: Expired due to Term

• Current Assignee: Rudolph Technologies Incorporated (Onto Innovation Inc.)
• Original Assignee: Rudolph Technologies Incorporated (Onto Innovation Inc.)
• Inventors: O'Dell, Jeffrey L., Verburgt, Thomas, Harless, Mark, Watkins, Cory
• Primary Examiner(s): STREGE, JOHN B
• Application Number:
  US12/789,829
• Publication Number:
  US 20100239157A1
• Time in Patent Office: 2,174 Days
• Field of Search: 382/141, 382/145, 382/147, 382/148, 382/149, 382/181, 348/87, 348/126, 356/237.3, 356/237.4, 356/237.5, 438/16
• US Class Current: 1/1
• CPC Class Codes: G01N 2021/8838 Stroboscopic illumination; synchronised illumination
• CPC Class Codes: G01N 21/8803 Visual inspection measuring projectors G01B9/08
• CPC Class Codes: G01N 21/8806 Specially adapted optical and illumination features
• CPC Class Codes: G01N 21/9501 Semiconductor wafers manufacturing processes per se of semiconductor devices implementing a measuring step H01L22/10
• CPC Class Codes: G01N 2201/06113 Coherent sources; lasers
• CPC Class Codes: G01N 2201/0696 Pulsed
• CPC Class Codes: G01N 2201/0697 Pulsed lasers
• CPC Class Codes: G01N 2201/12 Circuits of general importance; Signal processing
• CPC Class Codes: G06T 2207/30148 Semiconductor; IC; Wafer
• CPC Class Codes: G06T 7/0004 Industrial image inspection
• CPC Class Codes: H01L 21/67242 Apparatus for monitoring, sorting or marking testing or measuring during manufacture H01L22/00, marks per se H01L23/544; testing individual semiconductor devices G01R31/26
• CPC Class Codes: H01L 21/67271 Sorting devices
• CPC Class Codes: H01L 21/67288 Monitoring of warpage, curvature, damage, defects or the like
• CPC Class Codes: H01L 22/12 for structural parameters, e.g. thickness, line width, refractive index, temperature, warp, bond strength, defects, optical inspection, electrical measurement of structural dimensions, metallurgic measurement of diffusions electrical measurement of diffusions H01L22/14
• CPC Class Codes: H01L 2924/00 Indexing scheme for arrangements or methods for connecting or disconnecting semiconductor or solid-state bodies as covered by H01L24/00
• CPC Class Codes: H01L 2924/0002 Not covered by any one of groups H01L24/00, H01L24/00 and H01L2224/00
• CPC Class Codes: H04N 23/56 provided with illuminating means

Abstract

An automated defect inspection system has been invented and is used on patterned wafers, whole wafers, broken wafers, partial wafers, sawn wafers such as on film frames, JEDEC trays, Auer boats, die in gel or waffle packs, MCMs, etc., and is specifically intended and designed for second optical wafer inspection for such defects as metalization defects (such as scratches, voids, corrosion, and bridging), diffusion defects, passivation layer defects, scribing defects, glassivation defects, chips and cracks from sawing, solder bump defects, and bond pad area defects.

Claims

1. An automated system for inspecting a substrate, the system comprising:

a test plate;

a substrate provider for providing a set of substrates to the test plate, wherein each substrate in the set of substrates is selected from a group consisting of a whole patterned wafer, a sawn patterned wafer, a broken patterned wafer, at least one portion of a patterned wafer, an individual patterned die, at least one portion of an individual patterned die, a plurality of individual patterned die, at least one portion of a plurality of individual patterned die, multiple patterned die in a waffle pak, a multi-chip module (MCM), a JEDEC tray, and an Auer boat;

a visual inspection device for visual inputting of a plurality of known good quality substrates from the set of substrates during training and for visual inspection of unknown quality substrates from the set of substrates during inspection, wherein the known good quality substrates have a use defined level of quality, and wherein the training forms a model, the model providing a single representation of the plurality of known good quality substrates;

an illuminator for providing short pulses of light to each of the unknown quality substrates during movement between the unknown quality substrate and the visual inspection device, wherein the illuminator is configured to provide the short pulses of light based on a velocity of the movement; and

a microprocessor having processing and memory capabilities for developing the model of a good quality substrate based upon the training and comparing the unknown quality substrates to the model.

2. The automated system of claim 1, wherein the visual inspection device is configured to capture still images of each of the unknown quality substrates during continuous movement between the unknown quality substrate and the visual inspection device.

3. The automated system of claim 2, wherein the short pulses of light are synchronized with the capturing of the still images.

4. The automated system of claim 1, wherein the illuminator is configured to provide the short pulses of light at a sequence correlating to a velocity of the movement.

5. The automated system of claim 1, wherein the illuminator comprises a brightfield illuminator positioned approximately above the test plate.

6. The automated system of claim 1, wherein the illuminator comprises a darkfield illuminator positioned approximately above the test plate.

7. The automated system of claim 1, wherein the illuminator comprises at least one darkfield laser positioned approximately about a periphery of the test plate for providing darkfield illumination at an angle of less than about six degrees to the test plate.

8. An automated method of inspecting a semiconductor substrate, the method comprising:

training a model as to parameters of a good substrate via optical viewing of multiple known good substrates;

forming the model as a single representation of the multiple known good substrates, wherein the model is formed of a plurality of pixels;

illuminating unknown quality substrates with an illuminator, the illuminator configured to provide flashes of light to each of the unknown quality substrates during movement of the unknown quality substrate, wherein the illuminator is configured to provide the flashes of light based on a velocity of the movement; and

inspecting the unknown quality substrates using the model, thereby identifying acceptable quality substrates, wherein each of the known good substrates and each of the unknown quality substrates is selected from a group consisting of a whole patterned wafer, a sawn patterned wafer, a broken patterned wafer, at least one portion of a patterned wafer, an individual patterned die, at least one portion of an individual patterned die, a plurality of individual patterned die, at least one portion of a plurality of individual patterned die, multiple patterned die in a waffle pak, a multi-chip module (MCM), a JEDEC tray, and an Auer boat.

9. The automated method of claim 8, wherein the inspecting step comprises capturing still views of each of the unknown quality substrates during continuous movement of the substrate.

10. The automated method of claim 9, wherein the flashes of light are synchronized with the capturing of the still views.

11. The automated method of claim 8, wherein the illuminator is configured to provide the flashes of light at a sequence correlating to a velocity of the movement.

12. An automated system for inspecting a substrate, the system comprising:

a test plate;

a substrate provider for providing a set of substrates to the test plate, wherein each substrate in the set of substrates is selected from a group consisting of a whole patterned wafer, a sawn patterned wafer, a broken patterned wafer, at least one portion of a patterned wafer, an individual patterned die, at least one portion of an individual patterned die, a plurality of individual patterned die, at least one portion of a plurality of individual patterned die, multiple patterned die in a waffle pak, a multi-chip module (MCM), a JEDEC tray, and an Auer boat;

a camera for capturing still images of a moving substrate from the set of substrates;

an illuminator for providing strobe illumination to the moving substrate, wherein the illuminator is configured to provide the strobe illumination based on a velocity of the moving substrate; and

a controller for comparing pixel data for unknown quality substrates in the set of substrates to a model of a good quality substrate wherein the model is a single representation of a plurality of known good quality substrates, wherein the model is formed of a plurality of pixels, with each pixel being a representation of corresponding pixels of the plurality of known good quality substrates.

13. The automated system of claim 12, wherein the strobe illumination comprises short pulses of light at a sequence correlating to a velocity of the moving substrate.

14. The automated system of claim 12, wherein the strobe illumination is synchronized with the capturing of the still images.

15. The automated system of claim 12, wherein the illuminator comprises a brightfield illuminator positioned approximately above the test plate.

16. The automated system of claim 12, wherein the illuminator comprises a darkfield illuminator positioned approximately above the test plate.

17. The automated system of claim 12, wherein the illuminator comprises a set of low angle darkfield lasers positioned approximately about a periphery of the test plate for providing darkfield illumination at an angle of less than about six degrees to the test plate.

18. An automated system for inspection of a substrate for defects, the system comprising:

a platform arranged for moving the substrate during inspection, wherein the substrate is selected from a group consisting of a whole patterned wafer, a sawn patterned wafer, a broken patterned wafer, at least one portion of a patterned wafer, an individual patterned die, at least one portion of an individual patterned die, a plurality of individual patterned die, at least one portion of a plurality of individual patterned die, multiple patterned die in a waffle pak, a multi-chip module (MCM), a JEDEC tray, and an Auer boat;

a visual inspection device adapted to capture images associated with the substrate while the substrate is in motion relative to the visual inspection device;

a strobing illuminator configured to automatically illuminate at least a portion of the substrate while the substrate is in motion to aid in capture of the images by the visual inspection device; and

a processor configured to compare the captured images to a reference model during inspection to detect defects in the substrate.

19. The automated system of claim 18, wherein the strobing illuminator comprises at least one of a brightfield illuminator, a darkfield laser and a darkfield illuminator.

20. The automated system of claim 18, wherein the visual inspection device comprises a grey-scale camera.

21. The automated system of claim 18, wherein the strobing illuminator is configured to selectively illuminate the substrate at a variable rate, wherein the variable rate is automatically adjusted to a speed associated with movement of the substrate relative to the visual inspection device.

22. An automated system for training a reference model for inspection of an unknown quality substrate for defects, the system comprising:

a moveable stage configured to move known quality substrates, wherein each of the known quality substrates is selected from a group consisting of a whole patterned wafer, a sawn patterned wafer, a broken patterned wafer, at least one portion of a patterned wafer, an individual patterned die, at least one portion of an individual patterned die, a plurality of individual patterned die, at least one portion of a plurality of individual patterned die, multiple patterned die in a waffle pak, a multi-chip module (MCM), a JEDEC tray, and an Auer boat;

a visual inspection device adapted to capture for each of the known quality substrates at least one image associated with the known quality substrate while the known quality substrate is in motion relative to the visual inspection device;

a strobing illuminator operative to automatically illuminate at least a portion of each of the known quality substrates while the known quality substrate is in motion relative to the visual inspection device; and

a processor configured to create a reference model based on the images associated with at least two of the known quality substrates.

23. The automated system of claim 22, wherein the visual inspection device comprises a grey-scale camera.

24. An automated system for inspection of a substrate for defects, the system comprising:

a moveable stage configured to move a set of substrates, wherein each substrate in the set of substrates is selected from a group consisting of a whole patterned wafer, a sawn patterned wafer, a broken patterned wafer, at least one portion of a patterned wafer, an individual patterned die, at least one portion of an individual patterned die, a plurality of individual patterned die, at least one portion of a plurality of individual patterned die, multiple patterned die in a waffle pak, a multi-chip module (MCM), a JEDEC tray, and an Auer boat;

a visual inspection device adapted to capture images associated with each substrate in the set of substrates;

a strobing illuminator operative to automatically illuminate at least a portion of each substrate in the set of substrates while the substrate is in motion relative to the visual inspection device; and

a processor configured to generate a reference model from the captured images acquired from at least two known quality substrates in the set of substrates, and compare the captured images acquired from an unknown quality substrate in the set of substrates to the reference model to detect defects in the unknown quality substrate.

25. The automated system of claim 24, wherein the defects comprise a set of defects associated with bumps.

26. The automated system of claim 24, wherein the visual inspection device comprises a grey-scale camera.

27. An automated system for inspection of a substrate for defects, the system comprising:

a moveable platform adapted to move the substrate, wherein the substrate is selected from a group consisting of a whole patterned wafer, a sawn patterned wafer, a broken patterned wafer, at least one portion of a patterned wafer, an individual patterned die, at least one portion of an individual patterned die, a plurality of individual patterned die, at least one portion of a plurality of individual patterned die, multiple patterned die in a waffle pak, a multi-chip module (MCM), a JEDEC tray, and an Auer boat;

a robotic arm configured to provide the substrate to the moveable platform;

a brightfield illuminator configured to selectively strobe the substrate while the substrate is in motion;

a darkfield illuminator configured to selectively strobe the substrate while the substrate is in motion;

a focusing mechanism adapted to focus on a surface of the substrate;

a grey-scale camera adapted to capture images of the substrate while the substrate is in motion; and

a processor adapted to compare the images to a reference model to detect defects in the substrate.

28. The automated system of claim 27, wherein the processor is further adapted to virtually align the substrate.

29. The automated system of claim 27, wherein the reference model is based on a set of images from at least two known quality substrates.

30. The automated system of claim 27, wherein the defects comprise a set of defects associated with bumps.

31. The automated system of claim 27, wherein the brightfield illuminator and darkfield illuminator are configured to selectively illuminate the substrate at a variable rate, wherein the variable rate is automatically adjusted to a speed associated with movement of the substrate relative to the camera.

32. An automated system for inspection of a substrate on a film frame for defects, the system comprising:

a platform arranged for moving the substrate during inspection, wherein the substrate is selected from a group consisting of a whole patterned wafer, a sawn patterned wafer, a broken patterned wafer, at least one portion of a patterned wafer, an individual patterned die, at least one portion of an individual patterned die, a plurality of individual patterned die, at least one portion of a plurality of individual patterned die, multiple patterned die in a waffle pak, a multi-chip module (MCM), a JEDEC tray, and an Auer boat;

a visual inspection device adapted to capture images associated with the substrate while the substrate is in motion relative to the visual inspection device;

a strobing illuminator configured to automatically illuminate at least a portion of the substrate while the substrate is in motion to aid in capture of the images by the visual inspection device; and

a processor configured to compare the captured images to a reference model during inspection to detect defects in the substrate.

33. An automated method of inspecting an unknown quality substrate comprising:

moving the unknown quality substrate, wherein the unknown quality substrate comprises at least a portion of a patterned wafer mounted on a film frame;

automatically strobing the unknown quality substrate while the unknown quality substrate is in motion;

capturing images of the unknown quality substrate while the unknown quality substrate is in motion; and

comparing the images to a reference model to detect defects in the unknown quality substrate and make the unknown quality substrate a known quality substrate.

34. The automated method of claim 33, wherein the defects comprise at least one of metallization defects, diffusion defects, passivation layer defects, scribing defects, glassivation defects, sawing-related chips, sawing-related cracks, bump defects, bond pad area defects and probe area defects.

35. The automated method of claim 33, wherein the defects consist essentially of a set of defects generally at a 1+ micron level.

36. The automated method of claim 33, wherein the at least a portion of a wafer comprises a plurality of irregularly spaced die.

37. The automated method of claim 36, wherein the plurality of irregularly spaced die are sawn.

38. The automated method of claim 36, wherein the plurality of irregularly spaced die are selected from all of the die on the at least a portion of a patterned wafer.

39. The automated method of claim 33, wherein a rate at which the unknown quality substrate is strobed varies with respect to a velocity of the unknown quality substrate.

40. The automated method of claim 33, wherein a rate at which the unknown quality substrate is strobed varies during the inspection of the unknown quality substrate.

41. The automated method of claim 33, wherein a rate at which the unknown quality substrate is strobed varies discontinuously.

42. The automated method of claim 36, wherein a rate at which the unknown quality substrate is strobed varies in a manner that correlates to both a velocity of the unknown quality substrate and a position of the irregularly spaced die.

43. An automated method of inspecting an unknown quality substrate comprising:

moving the unknown quality substrate, wherein the substrate is selected from a group consisting of a whole patterned wafer, a sawn patterned wafer, a broken patterned wafer, at least one portion of a patterned wafer, an individual patterned die, at least one portion of an individual patterned die, a plurality of individual patterned die, at least one portion of a plurality of individual patterned die, multiple patterned die in a waffle pak, a multi-chip module (MCM), a JEDEC tray, and an Auer boat;

automatically strobing the unknown quality substrate while the unknown quality substrate is in motion;

varying a rate at which the unknown quality substrate is strobed during inspection, the rate at which the unknown quality substrate is strobed being at least partially correlated to both a rate at which the unknown quality substrate is moved and relative positions of a plurality of regions of interest on the unknown quality substrate;

capturing images of at least one of the regions of interest on the unknown quality substrate while the unknown quality substrate is in motion; and

comparing the images to a reference model to detect defects in the unknown quality substrate and make the unknown quality substrate a known quality substrate.

44. An integrated circuit chip generated by a process comprising the steps of:

moving an unknown quality substrate, wherein the unknown quality substrate comprises at least a portion of a patterned wafer, and wherein the at least a portion of a patterned wafer comprises a semiconductor die of the integrated circuit chip;

automatically strobing the unknown quality substrate while the unknown quality substrate is in motion;

capturing images of the unknown quality substrate while the unknown quality substrate is in motion; and

comparing the images to a reference model to detect defects in the unknown quality substrate and make the unknown quality substrate a known quality substrate.