Aggregate Predictive Model & Workflow for Local Execution

Patent metadata

Field	Value
Publication number	US-2016371599-A1
Application number	US-201514744352-A
Country	US
Kind code	A1
Filing date	Jun 19, 2015
Priority date	Dec 1, 2014
Publication date	Dec 22, 2016
Grant date	—

Abstract

Disclosed herein are systems, devices, and methods related to assets and predictive models and corresponding workflows that are related to the operation of assets. In particular, examples involve defining and deploying aggregate, predictive models and corresponding workflows, defining and deploying individualized, predictive models and/or corresponding workflows, and dynamically adjusting the execution of model-workflow pairs.

First claim

1 . A computing system comprising:
at least one processor; a non-transitory computer-readable medium; and program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the computing system to:
receive respective operating data for a plurality of assets;
based on the received operating data, define a predictive model and a corresponding workflow that are related to the operation of the plurality of assets; and
transmit to at least one asset of the plurality of assets the predictive model and the corresponding workflow for local execution by the at least one asset.

2 . The computing system of claim 1 , wherein the respective operating data comprises (i) abnormal-condition data associated with a failure that occurred at a given asset at a particular time and (ii) at least one of sensor or actuator data indicating at least one operating condition of the given asset at the particular time.

3 . The computing system of claim 1 , wherein the predictive model is defined to output a probability that a particular event will occur at a given asset within a period of time into the future.

4 . The computing system of claim 3 , wherein the corresponding workflow comprises one or more operations to be performed based on the determined probability.

5 . The computing system of claim 1 , wherein the corresponding workflow comprises a given asset controlling one or more actuators of the given asset to facilitate modifying an operating condition of the given asset.

6 . The computing system of claim 1 , wherein the corresponding workflow comprises one or more diagnostic tools to be executed locally by a given asset.

7 . The computing system of claim 1 , wherein the corresponding workflow comprises acquiring sensor data according to a data-acquisition scheme.

8 . The computing system of claim 7 , wherein the data-acquisition scheme indicates one or more sensors of a given asset from which data is acquired.

9 . The computing system of claim 8 , wherein the data-acquisition scheme further indicates an amount of data that the given asset will acquire from each of the one or more sensors.

10 . The computing system of claim 1 , wherein the corresponding workflow comprises transmitting data to the computing system according to a data-transmission scheme.

11 . The computing system of claim 10 , wherein the data-transmission scheme indicates a frequency at which a given asset transmits data to the computing system.

12 . The computing system of claim 1 , wherein the computing system is a first computing system, and wherein the corresponding workflow comprises a given asset transmitting instructions to a second computing system to facilitate causing the second computing system to carry out an operation related to the given asset.

13 . The computing system of claim 1 , wherein the at least one asset of the plurality of assets comprises a first asset and a second asset, and wherein transmitting the predictive model and the corresponding workflow comprises transmitting to the first asset and the second asset the predictive model and the corresponding workflow.

14 . A non-transitory computer-readable medium having instructions stored thereon that are executable to cause a computing system to:
receive respective operating data for a plurality of assets; based on the received operating data, define a predictive model and a corresponding workflow that are related to the operation of the plurality of assets; and transmit to at least one asset of the plurality of assets the predictive model and the corresponding workflow for local execution by the at least one asset.

15 . The non-transitory computer-readable medium of claim 14 , wherein the predictive model is defined to output a probability that a particular event will occur at a given asset within a period of time into the future.

16 . The non-transitory computer-readable medium of claim 14 , wherein the corresponding workflow comprises a given asset controlling one or more actuators of the given asset to facilitate modifying an operating condition of the given asset.

17 . The non-transitory computer-readable medium of claim 14 , wherein the corresponding workflow comprises one or more diagnostic tools to be executed locally by a given asset.

18 . The non-transitory computer-readable medium of claim 14 , wherein the computing system is a first computing system, and wherein the corresponding workflow comprises a given asset transmitting instructions to a second computing system to facilitate causing the second computing system to carry out an operation related to the given asset.

19 . A computer-implemented method comprising:
receiving respective operating data for a plurality of assets; based on the received operating data, defining a predictive model and a corresponding workflow that are related to the operation of the plurality of assets; and transmitting to at least one asset of the plurality of assets the predictive model and the corresponding workflow for local execution by the at least one asset.

20 . The computer-implemented method of claim 19 , wherein the corresponding workflow comprises acquiring sensor data according to a data-acquisition scheme, wherein the data-acquisition scheme indicates one or more sensors of a given asset from which data is acquired.

Assignees

• Uptake Tech Inc

Inventors

• Nicholas Brad
• Kolb Jason

Classifications

• G06Q10/20 Primary

  Administration of product repair or maintenance · CPC title

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• G06Q10/0633

  Workflow analysis · CPC title

• G06Q50/08

  Construction · CPC title

• G06Q10/067

  Enterprise or organisation modelling · CPC title