Use of spatial models for simultaneous control of various non-uniformity metrics

• US 5,546,312 A
• Filed: 02/24/1994
• Issued: 08/13/1996
• Est. Priority Date: 09/20/1993
• Status: Expired due to Fees

• Current Assignee: Adventa Control Technologies, Inc. (Onto Innovation Inc.)
• Original Assignee: Texas Instruments, Inc.
• Inventors: Saxena, Sharad, Mozumder, Purnendu K.
• Primary Examiner(s): Trammell, James P.
• Application Number:
  US08/201,302
• Time in Patent Office: 901 Days
• Field of Search: 364/468, 364/488-491, 364/552, 364/554, 364/578, 364/579, 364/401, 364/402, 364/148-151, 437/7, 437/8, 437/51, 437/952, 437/958, 437/225
• US Class Current: 700/97
• CPC Class Codes: G05B 19/41875 characterised by quality surveillance of production
• CPC Class Codes: G05B 2219/42001 Statistical process control spc
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
• CPC Class Codes: Y02P 90/80 Management or planning

Abstract

A method and system have been described for simultaneously controlling one or multiple metrics of non-uniformity using a model form independent multi-variable controller. The method comprising: utilizing process models relating a plurality of product quality parameters to the plurality of process control variables; measuring a plurality of product quality parameters on a first plurality of products; exercising statistical quality control tests on the plurality of product quality parameters of the first plurality of products; continuing processing if statistical quality control tests do not indicate significant difference from model prediction and observables; otherwise measuring the plurality of product quality parameters on a second plurality of products; tuning the process models to create tuned process models using the plurality of product quality parameters from the first and the second plurality of products, wherein the tuning estimates a changed state of the processing with the use of process models; estimating new values for the plurality of process control variables from the tuned models; processing a third plurality of products at the new values of the plurality of process control variables; measuring the plurality of product quality parameters on the third plurality of products; repeating the tuning of the process models and the estimating new values for the plurality of process control variables if the quality control parameters from the third plurality of products are not acceptable; otherwise continuing processing products with the new values of the plurality of process control variables if the quality control parameters from the third plurality of products are acceptable. The process models may include site models, wherein the site models would model metrics of non-uniformity and asymmetry as functions of sites.

Claims

1. A method of simultaneously controlling a plurality of non-uniformity metrics in processing a discrete product, said method comprising:

utilizing process models of said discrete product relating a plurality of product quality parameters to a plurality of process control variables, wherein said process models include spatial models of said discrete product;

measuring said plurality of product quality parameters on a first plurality of products;

exercising statistical quality control tests on said plurality of product quality parameters of said first plurality of products;

continuing processing if statistical quality control tests do not indicate significant difference from model prediction and observables;

otherwise

measuring said plurality of product quality parameters on a second plurality of products;

tuning said process models to create tuned process models using said plurality of product quality parameters from said first and said second plurality of products, wherein said tuning estimates a changed state of said processing with the use of process models;

estimating new values for said plurality of process control variables from said tuned models;

processing a third plurality of products at said new values of said plurality of process control variables;

measuring said plurality of product quality parameters on said third plurality of products;

repeating said tuning of said process models and said estimating new values for said plurality of process control variables if said product quality parameters from said third plurality of products are not acceptable;

otherwise

continuing processing products with said new values of said plurality of process control variables if said product quality parameters from said third plurality of products are acceptable.

2. The method of claim 1, wherein said spatial models model metrics of non-uniformity and asymmetry as functions of sites.

3. The method of claim 1, wherein said plurality of product quality parameters is a function of a plurality of model outputs of said process models, thereby providing a separation of said plurality of model outputs from a predetermined set of goals.

4. The method of claim 1, wherein said tuning updates said process models based on inputs corresponding to local experiment design and measured values corresponding to process model outputs.

5. The method of claim 1, wherein said tuning optimizes said process models with respect to targets or constraints specified by a set of predetermined goals.

6. The method of claim 1, wherein said estimating new values includes optimization to achieve a set of predetermined goals.

7. A system for simultaneously controlling a plurality of non-uniformity metrics in processing a discrete product, said system comprising:

a processor for processing discrete products;

a means operable for utilizing process models of said discrete product relating a plurality of product quality parameters to a plurality of process control variables, wherein said process models include spatial models of said discrete products;

a means operable for measuring said plurality of product quality parameters on a plurality of products;

a means operable for exercising statistical quality control tests on said plurality of product quality parameters of said plurality of products;

a means operable for determining whether said statistical quality control tests are successful on reaching a predetermined set of goals;

a means operable for tuning said process models to create tuned process models using said plurality of product quality parameters, wherein said tuning estimates a changed state of said processing with the use of process models;

a means operable for estimating new values for said plurality of process control variables from said tuned models; and

a memory for storing said new values.

8. The system of claim 7, wherein said spatial models model metrics of non-uniformity and asymmetry as functions of sites.

9. The system of claim 7, wherein said plurality of product quality parameters is a function of a plurality of model outputs of said process models, thereby providing a separation of said plurality of model outputs from said predetermined set of goals.

10. The system of claim 7, wherein said means operable for tuning updates said process models based on inputs corresponding to local experiment design and measured values corresponding to process model outputs.

11. The system of claim 7, wherein said means operable for tuning optimizes said process models with respect to targets or constraints specified by a set of predetermined goals.

12. The system of claim 7, wherein said means operable for estimating new values optimizes to achieve a set of predetermined goals.

13. A device for simultaneously controlling a plurality of non-uniformity metrics in processing a discrete product, said system comprising:

a means operable for utilizing process models of said discrete product relating a plurality of product quality parameters to a plurality of process control variables, wherein said process models include spatial models of said discrete products;

a means operable for measuring a plurality of product quality parameters on a plurality of products;

a means operable for exercising statistical quality control tests on said plurality of product quality parameters of said plurality of products;

a means operable for determining whether said statistical quality control tests are successful on reaching a predetermined set of goals;

a means operable for tuning said process models to create tuned process models using said plurality of product quality parameters, wherein said tuning estimates a changed state of said processing with the use of process models;

a means operable for estimating new values for said plurality of process control variables from said tuned models; and

a memory for storing said new values.

14. The device of claim 13, wherein said spatial models model metrics of non-uniformity and asymmetry as functions of sites.

15. The system of claim 13, wherein said means operable for tuning updates said process models based on inputs corresponding to local experiment design and measured values corresponding to process model outputs.

16. The system of claim 13, wherein said means operable for tuning optimizes said process models with respect to targets or constraints specified by a set of predetermined goals.

17. The system of claim 13, wherein said means operable for estimating new values optimizes to achieve a set of predetermined goals.