Fault detection apparatuses and methods for fault detection of semiconductor processing tools

• US 8,791,714 B2
• Filed: 01/23/2012
• Issued: 07/29/2014
• Est. Priority Date: 12/12/2007
• Status: Active Grant

• Current Assignee: Novellus Systems Incorporated (Lam Research Corporation)
• Original Assignee: Novellus Systems Incorporated (Lam Research Corporation)
• Inventors: Hansen, Keith John
• Primary Examiner(s): NGUYEN, HOAI AN D
• Application Number:
  US13/356,509
• Publication Number:
  US 20120123737A1
• Time in Patent Office: 918 Days
• Field of Search: 324/511, 324/555, 324/500, 324/762.01
• US Class Current: 324/762.01
• CPC Class Codes: G01R 31/00 Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere measuring superconductive properties G01R33/1238; testing or measuring semiconductors or solid state devices during manufacture H01L22/00; testing line transmission systems H04B3/46
• CPC Class Codes: G05B 2219/31356 Automatic fault detection and isolation
• CPC Class Codes: G05B 2219/37224 Inspect wafer
• CPC Class Codes: G05B 23/0229 knowledge based, e.g. expert systems; genetic algorithms
• 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 22/14 for electrical parameters, e.g. resistance, deep-levels, CV, diffusions by electrical means
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

Fault detection apparatuses and methods for detecting a processing or hardware performance fault of a semiconductor production tool have been provided. In an exemplary embodiment, a method for detecting a fault of a semiconductor production tool includes sensing a signal associated with a test component of the production tool during operation of the production tool and converting the signal to an electronic test signal. A prerecorded signature signal corresponding to the test component is provided and the test signal and the prerecorded signature signal are compared.

Claims

1. A fault detection apparatus comprising:

a signature signal database configured to store a signature signal corresponding to operation of a test component of a semiconductor fabrication tool in a known state; and

a comparator configured to compare a test signal received from a detection device and a signature signal received from the signature signal database, the test signal corresponding to a signal sensed from the test component of the semiconductor fabrication tool, the comparator further configured to perform a task based on a result of the comparison.

2. The apparatus of claim 1, wherein the known state comprises a properly functioning state.

3. The apparatus of claim 2, wherein the task comprises providing a fault detection signal if the result of the comparison is that the test signal is substantially different from the signature signal.

4. The apparatus of claim 1, wherein the known state comprises a malfunctioning state.

5. The apparatus of claim 4, wherein the task comprises providing a fault detection signal if the result of the comparison is that the test signal substantially matches the signature signal.

6. The apparatus of claim 1, wherein the comparator comprises voice recognition software.

7. The apparatus of claim 1, wherein the task comprises sending a signal to a controller configured to terminate operation of the semiconductor fabrication tool.

8. The apparatus of claim 1, further comprising sending a signal to a controller configured to vary at least one operational parameter of the semiconductor fabrication tool.

9. The apparatus of claim 1, wherein the task comprises performing a diagnostic test or analyzing process parameters.

10. The apparatus of claim 1, wherein the task comprises producing a visible or audible signal.

11. The apparatus of claim 1, wherein the signature signal comprises at least one of a frequency measured over time, an intensity measured over distance, an intensity measured over an x-y grid, and audio waveform data.

12. The apparatus of claim 1, wherein the signature signal has a sampling rate in the range of 60 Hz to 600 kHz.

13. The apparatus of claim 1, wherein the signature signal database contains a plurality of prerecorded signature signals recorded prior to installation of the semiconductor fabrication tool.

14. A method for detecting a fault in a semiconductor production tool, the method comprising:

comparing a test signal associated with a test component during operation of the semiconductor production tool to a prerecorded signature signal of the test component operating in a known state; and

providing a fault detection signal if the test signal substantially differs from the prerecorded signature signal or if the test signal substantially matches the prerecorded signature signal.

15. The method of claim 14, wherein the known state comprises a properly functioning state.

16. The method of claim 15, wherein providing the fault detection signal is if the test signal substantially differs from the prerecorded signature signal.

17. The method of claim 14, wherein the known state comprises a malfunctioning state.

18. The method of claim 17, wherein providing the fault detection signal is if the test signal substantially matches from the prerecorded signature signal.

19. The method of claim 14, wherein the known state comprises the test component operating in isolation.

20. The method of claim 14, wherein the known state comprises the test component operating in the semiconductor production tool.

21. The method of claim 14, wherein comparing comprises using voice recognition software.