System for monitoring and analyzing manufacturing processes using statistical simulation with single step feedback

• US 5,719,796 A
• Filed: 12/04/1995
• Issued: 02/17/1998
• Est. Priority Date: 12/04/1995
• Status: Expired due to Term

• Current Assignee: GlobalFoundries, Inc.
• Original Assignee: Advanced Micro Devices, Inc.
• Inventors: Chen, Vincent Ming Chun
• Primary Examiner(s): LOUIS JACQUES, JACQUES H
• Application Number:
  US08/566,529
• Time in Patent Office: 806 Days
• Field of Search: 364/578, 364/488, 364/490, 364/468.03, 364/468.15, 364/474.03, 364/474.22, 364/474.29, 364/474.37, 364/474.17, 364/474.24, 364/474.26 , 364/560, 364/551.02, 364/468.16, 364/552, 364/554, 364/148, 364/468-28, 364/491, 364/551.01, 364/188, 364/468.02, 364/468.04, 364/468.01 , 364/468.21, 364/468.24, 364/468.28, 364/474.16, 364/550, 364/570, 364/571.01, 395/500, 395/22, 395/27, 395/800, 395/10
• US Class Current: 703/13
• CPC Class Codes: H01L 22/20 Sequence of activities consisting of a plurality of measurements, corrections, marking or sorting steps
• 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

Abstract

A statistical simulation of a semiconductor fabrication process is performed in parallel with the actual process. Input parameters derived from a probability density function are applied to the simulator which, in turn, simulates an actual fabrication process which is modeled as a probability density function. Each simulation step is repeated with a random seed value using a Monte Carlo technique, a trial-and-error method using repeated calculations to determine a best solution to a problem. The simulator generates an output in the form of a probability distribution. The statistical simulation uses single-step feedback in which a simulation run uses input parameters that are supplied or derived from actual in-line measured data. Output data generated by the simulator, both intermediate output structure data and WET data, are matched to actual in-line measured data in circumstances for which measured data is available. The probability density structure of the simulator is adjusted after each simulation step so that simulated data more closely matches in-line measured data.

Claims

1. A manufacturing monitoring system comprising:

a fabrication equipment for performing a fabrication process step applied to a workpiece;

a test equipment for acquiring a sample of a process test parameter sensed from the workpiece;

a computer coupled to the test equipment to receive the process test parameter sample;

a software program operable upon the computer system, the software program having a plurality of routines including;

a routine for receiving the process test parameter sample;

a routine for simulating a simulated fabrication process step which corresponds to the fabrication process step to generate a plurality of simulated fabrication process results, routine for simulating being a statistical simulation of a semiconductor fabrication process further including;

a simulation loop routine using single-step feedback in which a simulation step of a plurality of simulation steps uses input parameters that are supplied from actual in-line measured data and generates output data;

a subroutine for matching output data generated by the simulation step against actual in-line measured data; and

a subroutine for adjusting a probability density structure of the simulator after each simulator step so that the simulated data more closely matches the actual in-line measured data; and

a routine for generating a simulated profile indicative of the simulated fabrication process results.

2. A system according to claim 1, wherein the software program further includes:

a Monte Carlo simulation routine for iteratively updating simulation results using a random seed value.

3. A system according to claim 1, wherein the software program further includes:

a routine for formatting a plurality of process test parameter samples into a process data profile; and

a routine for matching the process data profile to the simulated profile.

4. A system according to claim 1, wherein the software program simulating routine is a statistical simulation of a semiconductor fabrication process further comprising:

a subroutine for deriving an input parameter to the simulation from an actual fabrication process parameter, the input parameter being derived from a probability density function; and

a subroutine for simulating an actual fabrication process, the actual fabrication process being modeled as a probability density function.

5. A system according to claim 4, wherein the software program simulating routine is performed in parallel with the fabrication process step.

6. A system according to claim 4, wherein the software program simulating routine is a statistical simulation of a semiconductor fabrication process further comprising:

a subroutine for repeating a plurality of simulation steps, the repeated steps applying a varying random seed value that is varied using a Monte Carlo technique.

7. A software program encoded on a computer-usable medium having computable readable code embodied therein controlling a manufacturing monitoring system, the manufacturing monitoring system including a fabrication equipment for performing a fabrication process step applied to a workpiece, a test equipment for acquiring a sample of a process test parameter sensed from the workpiece, a computer coupled to the test equipment to receive the process test parameter sample and having a memory, and the software program loadable into the memory and executable on the computer, the software program having a plurality of routines including:

a routine for receiving the process test parameter sample;

a routine for simulating a simulated fabrication process step which corresponds to the fabrication process step to generate a plurality of simulated fabrication process results;

a routine for generating a simulated profile indicative of the simulated fabrication process results; and

a routine for controlling the manufacturing monitoring system in response to the generated simulated profile.

8. A software program according to claim 7 further comprising:

a Monte Carlo simulation routine for iteratively updating simulation results using a random seed value.

9. A software program according to claim 7 further comprising:

a routine for formatting a plurality of process test parameter samples into a process data profile; and

a routine for matching the process data profile to the simulated profile.

10. A software program according to claim 7 wherein the software program simulating routine is a statistical simulation of a semiconductor fabrication process further comprising:

a subroutine for deriving an input parameter to the simulation from an actual fabrication process parameter, the input parameter being derived from a probability density function; and

a subroutine for simulating an actual fabrication process, the actual fabrication process being modeled as a probability density function.

11. A software program according to claim 10, wherein the software program simulating routine is performed in parallel with the fabrication process step.

12. A software program according to claim 10, wherein the software program simulating routine is a statistical simulation of a semiconductor fabrication process further comprising:

a subroutine for repeating a plurality of simulation steps, the repeated steps applying a varying random seed value that is varied using a Monte Carlo technique.

13. A software program according to claim 10, wherein the software program simulating routine is a statistical simulation of a semiconductor fabrication process further comprising:

a simulation loop routine using single-step feedback in which a simulation step of a plurality of simulation steps uses input parameters that are supplied from actual in-line measured data and generates output data;

a subroutine for matching output data generated by the simulation step against actual in-line measured data; and

a subroutine for adjusting a probability density structure of the simulator after each simulator step so that the simulated data more closely matches the actual in-line measured data.

14. An executable program code encoded on a computer-usable medium having computable readable code embodied therein controlling a manufacturing monitoring system, the manufacturing monitoring system including a fabrication equipment for performing a fabrication process step applied to a workpiece, a test equipment for acquiring a sample of a process test parameter sensed from the workpiece, a computer coupled to the test equipment to receive the process test parameter sample and having a memory, and the software program loadable into the memory and executable on the computer, the software program having a plurality of routines including:

a routine for receiving the process test parameter sample;

a routine for simulating a simulated fabrication process step which corresponds to the fabrication process step to generate a plurality of simulated fabrication process results;

a routine for generating a simulated profile indicative of the simulated fabrication process results; and

a routine for controlling the manufacturing monitoring system in response to the generated simulated profile.

15. An executable program code according to claim 14 further comprising:

a Monte Carlo simulation routine for iteratively updating simulation results using a random seed value.

16. An executable program code according to claim 14 further comprising:

a routine for formatting a plurality of process test parameter samples into a process data profile; and

a routine for matching the process data profile to the simulated profile.

17. An executable program code according to claim 14 wherein the software program simulating routine is a statistical simulation of a semiconductor fabrication process further comprising:

a subroutine for deriving an input parameter to the simulation from an actual fabrication process parameter, the input parameter being derived from a probability density function; and

a subroutine for simulating an actual fabrication process, the actual fabrication process being modeled as a probability density function.

18. An executable program code according to claim 17 wherein the software program simulating routine is performed in parallel with the fabrication process step.

19. An executable program code according to claim 17 wherein the software program simulating routine is a statistical simulation of a semiconductor fabrication process further comprising:

a subroutine for repeating a plurality of simulation steps, the repeated steps applying a varying random seed value that is varied using a Monte Carlo technique.

20. An executable program code according to claim 17 wherein the software program simulating routine is a statistical simulation of a semiconductor fabrication process further comprising:

a simulation loop routine using single-step feedback in which a simulation step of a plurality of simulation steps uses input parameters that are supplied from actual in-line measured data and generates output data;

a subroutine for matching output data generated by the simulation step against actual in-line measured data; and

a subroutine for adjusting a probability density structure of the simulator after each simulator step so that the simulated data more closely matches the actual in-line measured data.