Method and system for computerizing quality management of a supply chain

• US 20050159973A1
• Filed: 12/22/2004
• Published: 07/21/2005
• Est. Priority Date: 12/22/2003
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Fleck, Thomas, Kleemann, Udo, Krause, Rainer, Kaltenbach, Michael, Waldenmaier, Christian
• Application Number:
  US11/022,450
• Publication Number:
  US 20050159973A1
• Time in Patent Office: Days
• US Class Current: 700/109
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: Y02P 90/80 Management or planning

Abstract

A system handling fully automated supplier quality control and enabling quality improvement by using supplier raw data as well as manufacturer manufacturing in-line data is described. The system not only maintains fully automated data transfers and handling, but also enables immediate automated reporting for both the manufacturer and the supplier. Based on this automated notification, communication between sides is thus introduced. The system also enables the transfer from reactive into preventive working mode, concerning supplier quality, giving advantages like early warning, fast feedback. Beyond the so-called automated quality control features, the system supports quality improvement enabling advanced analysis features like yield prediction, specification validation, best of breed analysis, and the like. These capabilities include a close feedback control loop with an adaptation feature to correct the prediction in case of a deviation and/or trend. The advanced features require the link to the supplier quality data with the manufacturer manufacturing data, to be able to use history data for ongoing analysis and prediction.

Claims

1. A method for managing quality in a production facility wherein products are manufactured using components, the method comprising the steps of:

receiving quality data for incoming components;

analyzing said received quality data on the basis of history quality data collected for prior received components and history data collected while processing prior received components in said production facility;

predicting the influence of the quality of incoming components on the yield of said production facility; and

selecting components in accordance with said prediction.

2. The method of claim 1, wherein the step of predicting said yield makes a correlation between at least one parameter of said component and the effect of said at least one parameter on said yield as determined by said history quality data.

3. The method of claim 1, wherein the step of selecting components further comprises rejecting said components whose quality data indicates a degradation of production yield above preset thresholds.

4. The method of claim 1, wherein the step of selecting components further comprises eliminating first components which quality data does not match a statistical quality distribution of second components that interact with said first components.

5. The method of claim 4, wherein logistics data is used in addition to said history quality data to identify matching ones of said second components.

6. The method of claim 1, wherein said history quality data defines quality specifications for incoming components.

7. The method of claim 1, wherein statistical data analysis is performed on parametric raw data for each of said components.

8. The method of claim 7, wherein said parametric raw data includes at least one functional, one dimensional parameter or at least one process parameter for manufacturing said product.

9. The method of claim 1, wherein history quality data triggers preventive maintenance for said production facility.

10. The method of claim 1, wherein quality data is exchanged electronically in predefined formats between said production facility and component suppliers.

11. A program storage device readable by a machine, tangibly embodying a program of instructions executable by as machine to perform method steps for managing quality in a production facility wherein products are manufactured using components, said method steps comprising:

receiving quality data for incoming components;

analyzing said received quality data on the basis of history quality data collected for prior received components and history data collected during processing of prior received components of said production facility;

predicting the influence of the quality of incoming components on the yield of said production facility; and

selecting components in accordance with said prediction.

14. The system of claim 11, wherein said selecting means comprises means for rejecting components whose quality data indicates a degradation of production yield above preset thresholds.

15. The system of claim 11, wherein said selecting means comprises means for eliminating first components whose quality data does not match a statistical quality distribution of second components that interact with said first components.

16. The system of claim 11, wherein means provide the history of quality data for triggering preventive maintenance for said production facility.

17. The system of claim 11, wherein means are provided to exchange quality data electronically in predefined formats between said production facility and suppliers of components.

12. A computer system for managing quality in a production facility where products are manufactured using components, said computer system comprising:

means for receiving quality data for incoming components;

means for analyzing said received quality data on the basis of history quality data collected for prior received components and history data collected during processing of prior received components in said production facility;

means for predicting the influence of the quality of incoming components on the yield of said production facility; and

means for selecting components in accordance with said prediction.

13. The computer system of claim 12, wherein said means for predicting yield comprises means for correlating at least one parameter of a component with the effect of that parameter on the yield as described by history data.