Integrated production loss managment

• US 9,104,998 B2
• Filed: 07/11/2013
• Issued: 08/11/2015
• Est. Priority Date: 07/23/2008
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services Limited (Accenture PLC)
• Inventors: Easo, Ajay Kurian, Kil, David H., Mei, Zhu-Song, Shah, Baiju
• Primary Examiner(s): MANSFIELD, THOMAS L
• Application Number:
  US13/939,994
• Publication Number:
  US 20130297377A1
• Time in Patent Office: 761 Days
• US Class Current: 1/1
• 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:

collecting, from a plurality of sensors that are located at different components of a system, operational data, wherein the operational data includes first data collected from a first sensor located at a first component of the system and second data collected from a second sensor located at a second component of the system, the second component being different from the first component;

receiving, by a computer system, maintenance data describing maintenance performed on the components of the system, including the first component and the second component, and a time or a date of the maintenance performed on the first component;

selecting, by a computer system, at least a portion of the operational data and at least a portion of the maintenance data including utilizing a frequency threshold to exclude a portion of the operational data associated with an event that has a likelihood of occurring that is not above a predetermined frequency;

applying, by a computer system, at least one statistical process to the selected operational data and the selected maintenance data to determine a correlation among the selected operational data and the selected maintenance data for the components of the system including the first component and the second component; and

predicting, by a computer system, at least one of a loss event and impact of a loss event in terms of at least one of economic impact, environmental impact, and health and safety impact based on the correlation among the selected operational data and the selected maintenance data and operational data and maintenance data for the components of the system including the first component and the second component.

2. The method of claim 1, further comprising:

receiving extraneous data that comprises at least one of

     1) data originated outside the system and

     2) data originating inside the system regarding measurement of an external impact source upon the system, excluding any man-made intended input or output of the system or data regarding processing or manufacturing performed by the system,

wherein applying at least one statistical process to the selected operational data and the selected maintenance data comprises applying at least one statistical process to the selected operational data, the selected maintenance data, and the received extraneous data to determine a correlation among the selected operational data, the selected maintenance data, and the received extraneous data for the components of the system including the first component and the second component, and

wherein predicting at least one of a loss event and impact of a loss event comprises predicting at least one of a loss event and impact of a loss event based on the correlation among the selected operational data, the selected maintenance data, and the received extraneous data and operational data and maintenance data for the components of the system including the first component and the second component as well as extraneous data comprising at least one of

     1) data originated outside the system and

     2) data originating inside the system regarding measurement of an external impact source upon the system, excluding any man-made intended input or output of the system or data regarding processing or manufacturing performed by the system.

3. The method of claim 1, wherein the system is utilized in production of a good or service.

4. The method of claim 1, wherein predicting at least one of a loss event and impact of a loss event comprises predicting at least one of a loss event and impact of a loss event for the second component based on operational data and maintenance data collected for the first component.

5. The method of claim 1, further comprising applying features to at least a portion of the selected operational data to amplify patterns before applying the selected operational data to the at least one statistical process.

6. The method of claim 5, further comprising, upon the application of the features, determining to alter the selection of the collected operational data that is utilized.

7. The method of claim 1, wherein selecting at least a portion of the operational data comprises utilizing an impact threshold to remove a portion of the operational data by, when repetitive occurrence routinely or consistently provides an impact below a significant amount, excluding data associated with the impact.

8. The method of claim 1, wherein predicting at least one of a loss event and impact of a loss event comprises predicting a loss event and impact of the loss event, further comprising:

determining multiple, different preventive measures for reducing the impact of the predicted loss event;

determining a predicted impact and a predicted cost of using each of the multiple, different preventive measures; and

controlling display of the multiple, different preventive measures with the predicted impact and the predicted cost for each of the multiple, different preventive measures.

9. The method of claim 1, wherein predicting at least one of a loss event and impact of a loss event comprises predicting impact of a loss event in terms of economic impact, environmental impact, and health and safety impact.

10. A computer system comprising:

at least one processing device; and

at least one non-transitory computer-readable storage medium having computer-executable instructions that when executed, by the at least one processing device, cause the at least one processing device to perform operations comprising;

collecting, from a plurality of sensors that are located at different components of a system, operational data, wherein the operational data includes first data collected from a first sensor located at a first component of the system and second data collected from a second sensor located at a second component of the system, the second component being different from the first component;

receiving maintenance data describing maintenance performed on the components of the system, including the first component and the second component, and a time or a date of the maintenance performed on the first component;

selecting at least a portion of the operational data and at least a portion of the maintenance data including utilizing a frequency threshold to exclude a portion of the operational data associated with an event that has a likelihood of occurring that is not above a predetermined frequency;

applying at least one statistical process to the selected operational data and the selected maintenance data to determine a correlation among the selected operational data and the selected maintenance data for the components of the system including the first component and the second component; and

predicting at least one of a loss event and impact of a loss event in terms of at least one of economic impact, environmental impact, and health and safety impact based on the correlation among the selected operational data and the selected maintenance data and operational data and maintenance data for the components of the system including the first component and the second component.

11. The computer system of claim 10, wherein the operations further comprise:

receiving extraneous data that comprises at least one of

     1) data originated outside the system and

     2) data originating inside the system regarding measurement of an external impact source upon the system, excluding any man-made intended input or output of the system or data regarding processing or manufacturing performed by the system,

wherein applying at least one statistical process to the selected operational data and the selected maintenance data comprises applying at least one statistical process to the selected operational data, the selected maintenance data, and the received extraneous data to determine a correlation among the selected operational data, the selected maintenance data, and the received extraneous data for the components of the system including the first component and the second component, and

wherein predicting at least one of a loss event and impact of a loss event comprises predicting at least one of a loss event and impact of a loss event based on the correlation among the selected operational data, the selected maintenance data, and the received extraneous data and operational data and maintenance data for the components of the system including the first component and the second component as well as extraneous data comprising at least one of

     1) data originated outside the system and

     2) data originating inside the system regarding measurement of an external impact source upon the system, excluding any man-made intended input or output of the system or data regarding processing or manufacturing performed by the system.

12. The computer system of claim 10, wherein the system is utilized in production of a good or service.

13. The computer system of claim 10, wherein predicting at least one of a loss event and impact of a loss event comprises predicting at least one of a loss event and impact of a loss event for the second component based on operational data and maintenance data collected for the first component.

14. The computer system of claim 10, wherein the operations further comprise applying features to at least a portion of the selected operational data to amplify patterns before applying the selected operational data to the at least one statistical process.

15. The computer system of claim 14, wherein the operations further comprise, upon the application of the features, determining to alter the selection of the collected operational data that is utilized.

16. The computer system of claim 10, wherein selecting at least a portion of the operational data comprises utilizing an impact threshold to remove a portion of the operational data by, when repetitive occurrence routinely or consistently provides an impact below a significant amount, excluding data associated with the impact.

17. The computer system of claim 10, wherein predicting at least one of a loss event and impact of a loss event comprises predicting a loss event and impact of the loss event, wherein the operations further comprise:

determining multiple, different preventive measures for reducing the impact of the predicted loss event;

determining a predicted impact and a predicted cost of using each of the multiple, different preventive measures; and

controlling display of the multiple, different preventive measures with the predicted impact and the predicted cost for each of the multiple, different preventive measures.

18. The computer system of claim 10, wherein predicting at least one of a loss event and impact of a loss event comprises predicting impact of a loss event in terms of economic impact, environmental impact, and health and safety impact.