Future reliability prediction based on system operational and performance data modelling

• US 10,409,891 B2
• Filed: 04/11/2015
• Issued: 09/10/2019
• Est. Priority Date: 04/11/2014
• Status: Active Grant

• Current Assignee: Hartford Steam Boiler Inspection and Insurance Company (Münchener Rückversicherungs-Gesellschaft AG)
• Original Assignee: Hartford Steam Boiler Inspection and Insurance Company (Münchener Rückversicherungs-Gesellschaft AG)
• Inventors: Jones, Richard B.
• Primary Examiner(s): Thangavelu, Kandasamy
• Application Number:
  US14/684,358
• Publication Number:
  US 20150294048A1
• Time in Patent Office: 1,613 Days
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06F 2111/10 Numerical modelling
• CPC Class Codes: G06Q 10/0635 Risk analysis of enterprise or organisation activities
• CPC Class Codes: Y02P 90/845 Inventory and reporting systems for greenhouse gases [GHG]

Abstract

Systems, methods, and apparatuses for improving future reliability prediction of a measurable system by receiving operational and performance data, such as maintenance expense data, first principle data, and asset reliability data via an input interface associated with the measurable system. A plurality of category values may be generated that categorizes the maintenance expense data by a designated interval using a maintenance standard that is generated from one or more comparative analysis models associated with the measureable system. The estimated future reliability of the measurable system is determined based on the asset reliability data and the plurality of category values and the results of the future reliability are displayed on an output interface.

Claims

1. A system, comprising:

at least one measurable system that comprises a plurality of equipment assets that is operated at each respective facility of a plurality of facilities;

at least one measuring device;

wherein the at least one measuring device measures, to generate measuring data, one or more physical attribute, one or more characteristics, or both that are associated with an operation, a performance, or both, of the measurable system of each respective facility of the plurality of facilities;

at least one sensing device;

wherein the at least one sensing device senses, to generate sensing data, the one or more physical attribute, the one or more characteristics, or both that are associated with the operation, the performance, or both, of the measurable system of each respective facility of the plurality of facilities;

a processor that is operationally coupled to;

i) the at least one the at least one measuring device, the at least one sensing device, or both, and

ii) a non-transitory computer readable medium,

wherein the non-transitory computer readable medium comprises instructions which, when executed by the processor, cause the processor to;

receive maintenance expense data of the at least one measurable system for each respective facility of the plurality of facilities;

receive first principle data that comprises, for one or more first principle characteristics associated with one or more target variables of the at least one measurable system, the measuring data, the sensing data, or both;

receive asset reliability data of the at least one measurable system;

receive one or more comparative analysis models associated with the at least one measurable system;

utilize one or more comparative analysis models to generate at least one maintenance standard for the at least one measureable system, based on the maintenance expense data and the first principle data;

generate a plurality of category values that categorizes, by at least one designated interval, the maintenance expense data based upon the at least the one maintenance standard associated with the at least one measureable system;

determine an estimated future reliability data of the at least one measurable system based on the asset reliability data and the plurality of category values;

wherein the one or more comparative analysis models identifies one or more reliability-effective maintenance tasks that affect the one or more target variables of the at least one measurable system based at least in part on at least one primary first principle characteristic;

wherein the at least one primary first principle characteristic is determined based on an amount of the variation in the one or more target variables of the at least one measurable system between the plurality of facilities;

wherein, based on performance of the one or more reliability-effective maintenance tasks with the at least one measurable system, the at least one measuring device, the at least one sensing device, or both, obtain, intermittently or continuously, current data for the at least one primary first principle characteristic of the at least one measurable system and transmit the current data to the processor that updates the estimated future reliability data of the at least one measurable system to generate the updated estimated future reliability data of the at least one measurable system; and

an user interface configured to display the estimated future reliability data and the updated estimated future reliability data.

2. The system of claim 1, wherein the asset reliability data is Equivalent Forced Outage Rate data.

3. The system of claim 1, wherein the instructions, when executed by the processor, further cause the processor to compile the at least one maintenance standard and the asset reliability data into a compiled data file.

4. The system of claim 3, wherein the instructions, when executed by the processor, further cause the processor to:

generate a categorized time based maintenance expense data based upon at least the compiled data file; and

generate a categorized time based asset reliability data based upon at least the compiled data file.

5. The system of claim 4, wherein the instructions, when executed by the processor, further cause the processor to generate the categorized time based maintenance expense data by arranging the category values according to one or more time intervals for the plurality of facilities.

6. The system of claim 4, wherein the instructions, when executed by the processor, further cause the processor to generate the categorized time based asset reliability data by arranging asset reliability data values according to one or more time intervals for the plurality of ether facilities.

7. The system of claim 1, wherein a future reliability interval of the estimated future reliability is based upon an amount of the maintenance expense data, the asset reliability data, and the first principle data.

8. The system of claim 1, wherein the at least one maintenance standard is utilized to normalize the maintenance expense data.

9. The system of claim 8, wherein the instructions, when executed by the processor, further cause the processor to normalize the maintenance expense data by generating a periodic maintenance spending divisor for a time period.

10. The system of claim 1, wherein the estimated future reliability report comprises a graph displaying the asset reliability data according to the plurality of category values.

11. A method, comprising:

measuring, by at least one measuring device, to generate measuring data, one or more physical attribute, one or more characteristics, or both, which are associated with an operation, a performance, or both, of at least one measurable system of each respective facility of a plurality of facilities;

sensing, by at least one sensing device, to generate sensing data, the one or more physical attribute, the one or more characteristics, or both that are associated with the operation, the performance, or both, of the measurable system of each respective facility of the plurality of facilities;

wherein the at least one measurable system that comprises a plurality of equipment assets that is operated at each respective facility of the plurality of facilities;

receiving, by a processor, maintenance expense data associated with at least one measurable system for each respective facility of the plurality of facilities;

wherein the processor is operationally coupled to the at least one the at least one measuring device, the at least one sensing device, or both;

receiving, by the processor, first principle data that comprises, for one or more first principle characteristics associated with one or more target variables of the at least one measurable system, the measuring data, the sensing data, or both;

receiving, by the processor, asset reliability data associated with the at least one measureable system;

receiving, by the processor, one or more comparative analysis models associated with the at least one measureable system;

utilizing, by the processor, one or more comparative analysis models to generate at least one maintenance standard for the at least one measureable system, based on the maintenance expense data and the first principle data;

generating, by the processor, a plurality of category values that categorizes, by at least one designated interval, the maintenance expense data based upon the at least one maintenance standard associated with the at least one measureable system;

generating, by the processor, an estimated future reliability data of the at least one measureable system based on the asset reliability data and the plurality of category values;

wherein the one or more comparative analysis models identifies one or more reliability-effective maintenance tasks that affect the one or more target variables of the at least one measurable system based at least in part on at least one primary first principle characteristic;

wherein the at least one primary first principle characteristic is determined based on an amount of variation in the one or more target variables of the at least one measurable system between the plurality of facilities;

wherein, based on performance of the one or more reliability-effective maintenance tasks with the at least one measurable system, the at least one measuring device, the at least one sensing device, or both, obtain, intermittently or continuously, current data for the at least one primary first principle characteristic of the at least one measurable system and transmit the current data to the processor that updates the estimated future reliability data of the at least one measurable system to generate the updated estimated future reliability data of the at least one measurable system; and

outputting, by the processor, the estimated future reliability data and the updated estimated future reliability data, using an output interface.

12. The method of claim 11, wherein the asset reliability data is Equivalent Forced Outage Rate data.

13. The method of claim 11, wherein the at least one maintenance standard is utilized to generate normalized maintenance expense data from the maintenance expense data and the one or more comparative analysis models.

14. The method of claim 13, further comprising:

generating the normalized maintenance expense data by generating a periodic maintenance spending divisor.

15. The method of claim 11, further comprising:

compiling the at least one maintenance standard and the asset reliability data into a compiled data file;

generating a categorized time based maintenance expense data based upon at least the compiled data file; and

generating a categorized time based asset reliability data based upon at least the compiled data file.

16. The method of claim 15, wherein the generating the categorized time based maintenance expense data comprises arranging the category values according to one or more time intervals for the plurality of facilities.

17. The apparatus of claim 15, wherein the generating the categorized time based asset reliability data comprises arranging asset reliability data values according to one or more time intervals for the plurality of facilities.