Method and system of confidence scoring

• US 6,353,767 B1
• Filed: 08/25/2000
• Issued: 03/05/2002
• Est. Priority Date: 08/25/2000
• Status: Expired due to Fees

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Hauer, Thomas Anthony, Wakeman, Thomas George, Arvidson, Alan Luis
• Primary Examiner(s): Cheng, Joe H.
• Assistant Examiner(s): Nguyen, Kim T.
• Application Number:
  US09/617,940
• Time in Patent Office: 557 Days
• Field of Search: 700/91, 700/92, 700/95, 700/97, 700/109, 700/110, 702/81, 702/84, 702/179
• US Class Current: 700/91
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A method of developing a confidence level in reliability or producibility prediction scores that includes generating data for a set of factors, inserting the data into scorecards and dashboards, and calculating an overall Z score and Z confidence range. The scorecards and dashboards are used to calculate the confidence level in reliability scores. Each reliability or producibility factor may be weighted as to its importance to the overall confidence level. Factors included in the method include accuracy of the critical to quality flowdown; completeness of the critical to quality flowdown; percentage of the design analyzed; comprehensiveness of the design analysis; risk assessment analysis; percentage of component. subassembly or product reuse from other projects; percentage of the design complete; verification of the process capability; plant integration; order to remittance process integration; extent of pilot run; and effectiveness of a test plan.

Claims

1. A method of developing, a confidence level using six sigma prediction scoring comprising:

determining a customer expectation value;

determining a Z factor comprising a set of factors;

selecting said set of factors;

generating respective data sets for said set of factors;

collecting said respective data sets in at least one scorecard;

calculating at least one Z score for said at least one scorecard;

generating a total Z score as a function of the respective scorecard Z scores scorecards;

comparing said total Z score for said scorecards with a selected Zst value;

calculating a Z confidence range;

scoring a confidence level based upon said Z confidence range and said total Z value; and

reporting said confidence level.

2. The method of claim 1, wherein the step of determining said customer expectation value further comprises generating at least one critical-to-quality requirement based upon a customer expectation.

3. The method of claim 1, wherein the step of selecting said factors further comprises selecting at least one category containing a set of factors.

4. The method of claim 1, further comprising the step of determining an availability value.

5. The method of claim 1, further comprising the step of determining a life calculation prediction value.

6. The method of claim 1, wherein the step of selecting factors further comprises selecting said factors based upon a customer expectation, wherein said customer expectation comprises at least one critical-to-quality requirement.

7. The method of claim 1, wherein the step of generating data sets further comprises:

generating data for a product design process; and

generating data for said product design process in a product structure, wherein said product structure further comprises a service network, wherein said service network further comprises a plants and major systems level;

a subsystems level;

a components level; and

a features and materials level.

8. The method of claim 7, wherein the step of generating data for said product design process comprises conducting at least one test in at least one category containing a respective set of factors.

9. The method of claim 1, further comprising the step of quantifying a capability described on said scorecard using a transfer function.

10. A method of claim 1, further comprising the step of generating a transfer function to quantify said data at said scorecards.

11. The method of claim 1, wherein the step of selecting said factors further comprises assigning at least one numerical score for each said factor.

12. The method of claim 11, wherein the step of assigning said numerical score further comprises assigning a qualitative description to said score.

13. The method of claim 12, further comprising redefining said descriptions to accurately define the meaning of said score.

14. The method of claim 1, wherein the step of generating said total Z score further comprises combining respective Z scores from respective.

15. The method of claim 1, wherein the step of calculating said Z confidence range further comprises subtracting said total Z score from said Z factor to create a Z Upper Range.

16. The method of claim 1, wherein the step of reporting said confidence level further comprises reporting a confidence level for a reliability prediction.

17. The method of claim 1, wherein the step of reporting said confidence level further comprises reporting a confidence level for a producibility prediction.

18. A storage medium encoded with machine-readable computer program for developing a confidence level in six sigma prediction scoring, the storage medium including instructions for causing a computer to implement a method comprising:

determining a customer expectation value;

determining an availability value;

determining a life calculation prediction value;

determining a Z factor comprising a set of factors;

selecting said set of factors for at least one category;

generating a plurality of respective data sets for said set of factors;

collecting said data sets in at least one scorecard;

generating a transfer function to quantify said data sets in said at least one scorecard;

calculating at least one respective Z score for said at least one scorecard;

generating a total Z score for all of said scorecards;

comparing said total Z score for all of said scorecards with a selected Zst value;

calculating a Z confidence range;

scoring a confidence level based upon said Z confidence range and said total Z value; and

reporting said confidence level.

19. The storage medium of claim 18, wherein said at least one category further comprises a Use and Environment category, an Analysis category, a Validation category.

20. The storage medium of claim 19, wherein said set of factors for said Use and Environment category further comprise a Customer Requirements factor, a Systems factor, a Characterization factor, and a Field Data factor.

21. The storage medium of claim 19, wherein said set of factors for said Analysis category further comprises a Standardization factor, a Tools factor, a 3D Master Model factor and a Boundary Conditions factor.

22. The storage medium of claim 19, wherein said set of factors for said Validation category further comprise a Similarity factor, a Field trials factor, and a Testing factor.

23. The storage medium of claim 18, wherein the step of reporting said confidence level further comprises reporting a confidence level for a reliability prediction.

24. The storage medium of claim 18, wherein the step of reporting said confidence level further comprises reporting a confidence level for a producibility prediction.

25. A method for using a computer to develop a confidence level in six sigma prediction scoring, comprising:

determining a customer expectation value;

determining an availability value;

determining a life calculation prediction value;

determining a Z factor comprising a set of factors;

selecting said set of factors;

generating a plurality of respective data sets for said set of factors;

collecting said data sets in at least one scorecard;

generating a respective trransfer function to quantify said respective data sets at said scorecards;

calculating at least one Z score for said at least one scorecard;

generating a total Z score for said scorecards;

comparing said total Z score for said scorecards with a selected Zst value;

calculating a Z confidence range;

scoring a confidence level based upon said Z confidence range and said total Z value; and

reporting said confidence level.