REAL-TIME MANAGEMENT SYSTEMS AND METHODS FOR MANUFACTURING MANAGEMENT AND YIELD RATE ANALYSIS INTEGRATION

• US 20060241802A1
• Filed: 09/19/2005
• Published: 10/26/2006
• Est. Priority Date: 04/26/2005
• Status: Active Grant

• Current Assignee: Powerchip Semiconductor Manufacturing Corp. (Powerchip Technology Corporation)
• Original Assignee: Powerchip Semiconductor Corporation (Powerchip Technology Corporation)
• Inventors: Wang, Sheng-Jen, Chen, Chien-Chung, Ho, Yu-Wen
• Granted Patent: US 7,260,444 B2
• Time in Patent Office: Days
• US Class Current: 700/121
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 2219/1112 Bit addressing, handling
• CPC Class Codes: G05B 2219/45031 Manufacturing semiconductor wafers
• CPC Class Codes: G05B 2223/02 Indirect monitoring, e.g. monitoring production to detect faults of a system
• CPC Class Codes: G05B 23/024 Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks
• CPC Class Codes: H01L 21/67276 Production flow monitoring, e.g. for increasing throughput program-control systems per se G05B19/00, e.g. total factory control G05B19/418

Abstract

A real-time management method for manufacturing management and yield rate analysis integration. A plurality of yield rates relating to wafer products are summed and averaged for a historical yield rate. Multiple representational inline QC parameters are selected. A statistical process is implemented and, if no extreme value and collinear parameter exists and if analysis results satisfy normal distribution, multiple optimum inline QC parameters are selected from the representational inline QC parameters. Weights of each optimum inline QC parameter are calculated. A predicted yield rate is calculated according to the historical yield rate, weights, and a plurality of measurement and target values relating to the wafer products.

Claims

1. A real-time management method for manufacturing management and yield rate analysis integration, comprising:

collecting a plurality of yield rates and inline QC parameters relating to wafer products in a predetermined period;

summing and averaging the yield rates for a historical yield rate;

selecting multiple representational inline QC parameters;

implementing a statistical process, comprising;

determining whether at least one extreme value exists in the representational inline QC parameters;

if no extreme value exists, determining whether at least one collinear parameter exists in the representational inline QC parameters; and

if no collinear parameter exists, determining whether residual analyses relating to the statistical process satisfy normal distribution;

if the analysis result satisfies normal distribution, selecting multiple optimum inline QC parameters from the representational inline QC parameters;

calculating weights of each optimum inline QC parameter; and

calculating a predicted yield rate according to the historical yield rate, weights, and a plurality of measurement and target values relating to the wafer products.

2. The method as claimed in claim 1, wherein if an extreme value exists in the representational inline QC parameters, parameter values sorted before 25% and after 75% are removed therefrom.

3. The method as claimed in claim 1, wherein if a collinear parameter exists in the representational inline QC parameters, one representational inline QC parameter is removed therefrom.

4. The method as claimed in claim 1, wherein if the analysis result satisfies abnormal distribution, it is converted to normal distribution using a Box-Cox conversion method.

5. The method as claimed in claim 1, wherein the determining operations are implemented using a stepwise linear regression (SLR) method.

6. A real-time management system for manufacturing management and yield rate analysis integration, comprising:

a collection unit, collecting a plurality of yield rates and inline QC parameters relating to wafer products in a predetermined period;

a statistical unit, summing and averaging the yield rates for a historical yield rate, selecting multiple representational inline QC parameters, implementing a statistical process, comprising determining whether at least one extreme value exists in the representational inline QC parameters, if no extreme value exists, determining whether at least one collinear parameter exists in the representational inline QC parameters, if no collinear parameter exists, determining whether residual analyses relating to the statistical process satisfy normal distribution, if the analysis result satisfies normal distribution, selecting multiple optimum inline QC parameters from the representational inline QC parameters, and calculating weights of each optimum inline QC parameter; and

a collection unit, calculating a predicted yield rate according to the historical yield rate, weights, and a plurality of measurement and target values relating to the wafer products.

7. The system as claimed in claim 6, wherein if an extreme value exists in the representational inline QC parameters, the statistical unit removes parameter values sorted before 25% and after 75% therefrom.

8. The system as claimed in claim 6, wherein if a collinear parameter exists in the representational inline QC parameters, the statistical unit removes one representational inline QC parameter therefrom.

9. The system as claimed in claim 6, wherein if the analysis result satisfies abnormal distribution, it is converted to normal distribution using a Box-Cox conversion method.

10. The system as claimed in claim 6, wherein the statistical unit implements the determining operations using a stepwise linear regression (SLR) method.