INTEGRATED PROUCTION LOSS MANAGEMENT

• US 20100023359A1
• Filed: 07/23/2008
• Published: 01/28/2010
• Est. Priority Date: 07/23/2008
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services GmbH (Accenture PLC)
• Inventors: Mei, Zhu-Song, Easo, Ajay Kurian, Kil, David H., Shah, Baiju
• Granted Patent: US 8,510,151 B2
• Time in Patent Office: Days
• US Class Current: 705/7
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/0635 Risk analysis of enterprise or organisation activities
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis

Abstract

Current monitoring systems often provide the operating condition of a specific component and do not consider the impact of a specific failure upon an entire system or a business. Nor do the current systems provide an avenue for the business to predict the loss, as well as its impact, and make an educated decision of mitigating the loss based upon economic, environmental, and health and safety considerations. Methods and systems are provided for predicting loss events, impacts of loss events, and providing potential corrective measures to reduce or eliminate the occurrence or impact of the loss events. One aspect relates to the use of system-wide information to predict variables that are directly linked to business impact, such as production loss. Extraneous and transactional data are also utilized according to other aspects of the invention.

Claims

1. A method comprising:

receiving system-wide information comprising operational data from a plurality of sensors, wherein a first sensor measures a parameter related to a first component of the system and a second sensor measures a parameter related to a second different component of the system;

receiving transactional data;

selecting at least a portion of the received system-wide information; and

applying a plurality of statistical models to the selected operational data, and transactional data to determine a best-fit model in regards to the correlation among the operational data with the transactional data to predict events and impacts of the predicted events in terms of at least one of economic impact, environmental impact, and health and safety impact.

2. The method of claim 1, further comprising:

utilizing the best-fit model to determine at least one intervention to reduce or eliminate the impact of the predicted events.

3. The method of claim 1, wherein the selection of at least a portion of the received system-wide information comprises the utilization of a threshold selected from the group consisting of a frequency threshold, an impact threshold, and combinations thereof.

4. The method of claim 3, wherein the impact threshold is selected from the impact group consisting of:

environmental, economic, health and safety, and combinations thereof.

5. The method of claim 1, wherein the selection of at least a portion of the collected system-wide data considers whether to utilize at least a portion of extraneous data to limit the operational data applied to the statistical models.

6. The method of claim 5, wherein the application of a plurality of statistical models to the selected operational data, extraneous data, and transactional data to determine a best-fit model in regards to the correlation among the operational data and extraneous data with the transactional data to predict events and impacts of the predicted events further comprises the investigation of any correlation of specific sensor data with other sensor data.

7. The method of claim 1, further comprising:

applying features to at least a portion of the selected data to amplify patterns before applying the data to the plurality of statistical models.

8. The method of claim 7, wherein upon the application of the features,

determining to alter the selection of the portion of the collected system-wide information that is utilized.

9. The method of claim 2, further comprising:

displaying on a display device at least one intervention.

10. The method of claim 9, wherein at least two interventions are displayed on the display device and wherein at least one intervention differs from another intervention in regards to at least one impact selected from the group consisting of:

environmental, economic, health and safety, and combinations thereof.

11. The method of claim 2, further comprising:

comparing at least one prediction determined by the best fit model with an actual outcome.

12. The method of claim 2, further comprising:

comparing an actual outcome with at least one statistical model that is not the best-fit model to determine if the at least one statistical model is more accurate than the best-fit model.

13. A computer-readable medium having computer-executable instructions that when executed perform a method comprising:

collecting system-wide information comprising operational data from a plurality of sensors, and transactional data;

receiving a user input selecting at least a portion of the collected system-wide information to apply statistical models upon to determine a best-fit model; and

executing analysis of the selected operational data, and transactional data by separately applying a plurality of statistical models to the to determine a best-fit model in regards to the correlation among the operational data with the transactional data to predict events and impacts of the predicted events in terms of at least one of economic impact, environmental impact, and health and safety impact.

14. The computer-readable medium of claim 13, wherein the method further comprises:

utilizing the best-fit model, calculating at least one intervention to reduce or eliminate the impact of the predicted events.

15. The computer-readable medium of claim 13, wherein the application of a plurality of statistical models to the selected operational data, and transactional data to determine a best-fit model in regards to the correlation among the operational data with the transactional data to predict events and impacts of the predicted events further comprises the calculation of any correlation of specific sensor data with other sensor data.

16. The computer-readable medium of claim 13, further comprising:

applying features to at least a portion of the selected data to amplify patterns before applying the data to the predictive model.

17. The computer-readable medium of claim 14, wherein at least two interventions are calculated and the method further comprising:

displaying at least two interventions on a display device, wherein at least one intervention differs from another intervention in regards to at least on impact selected from the impact group consisting of;

environmental, economic, health and safety, and combinations thereof.

18. The computer-readable medium of claim 14, the method further comprising:

comparing at least one prediction determined by the best fit model with an actual outcome.

19. The computer-readable medium of claim 14, further comprising:

comparing an actual outcome with at least one statistical model that is not the best-fit model to determine if the at least one statistical model is more accurate than the best-fit model.

20. A method comprising:

receiving system-wide information comprising operational data from a plurality of sensors, extraneous data, and transactional data;

determining to utilize at least a portion of the collected system-wide information to apply statistical models upon to determine a best-fit model;

executing analysis of the selected operational data, extraneous data, and transactional data by separately applying a plurality of statistical models to determine a best-fit model in regards to the correlation among the operational data and extraneous data with the transactional data to predict events and impacts of the predicted events in terms of at least economic impact, environmental impact, and health and safety impact;

utilizing the best-fit model, calculating at least one intervention to reduce or eliminate the impact of the predicted events; and

determining at least two interventions, wherein at least one intervention differs from another intervention in regards to at least one impact selected from the impact group consisting of;

environmental, economic, health and safety, and combinations thereof.