Digital twins for energy efficient asset maintenance

Patent metadata

Field	Value
Publication number	US-2016247129-A1
Application number	US-201615052992-A
Country	US
Kind code	A1
Filing date	Feb 25, 2016
Priority date	Feb 25, 2015
Publication date	Aug 25, 2016
Grant date	—

Abstract

A system for using digital twins for scalable, model-based machine predictive maintenance comprises a plurality of digital twins and a simulation platform. The plurality of digital twins correspond to plurality of remotely located physical machines. Each respective digital twin comprises: product nameplate data corresponding to a unique physical machine, one or more simulation models, and a database comprising run time log data collected from sensors associated with the unique physical machine. The simulation platform is configured to process simulation models corresponding to the plurality of digital twins using a plurality of multiprocessor computer systems.

First claim

1 . A system for using digital twins for scalable, model-based machine predictive maintenance, the system comprising:
a plurality of digital twins corresponding to plurality of remotely located physical machines, wherein each respective digital twin comprises:
product nameplate data corresponding to a unique physical machine,
one or more simulation models, and
a database comprising run time log data collected from sensors associated with the unique physical machine; and
a simulation platform configured to process simulation models corresponding to the plurality of digital twins using a plurality of multiprocessor computer systems.

2 . The system of claim 1 , further comprising:
a data platform configured to process a plurality of data query tasks using the plurality of multiprocessor computer systems.

3 . The system of claim 2 , wherein the data platform utilizes a map-reduce programming model to process each of the plurality of data query tasks.

4 . The system of claim 1 , wherein each simulation model included in the plurality of digital twins is implemented using a Bayesian filtering framework.

5 . The system of claim 1 , wherein each respective digital twin comprises a web service interface configured to facilitate communication between the respective digital twin and one or more remote devices.

6 . The system of claim 5 , wherein the system further comprises a mobile device interface configured to facilitate monitoring of the plurality of remotely located physical machines via the plurality of digital twins.

7 . The system of claim 5 , wherein the system further comprises a sensor interface configured to facilitate transfer of the run time log data from plurality of physical machines to the plurality of digital twins.

8 . The system of claim 7 , wherein the run time log data is collected from plurality of physical machines to the plurality of digital twins in real-time or near real-time.

9 . The system of claim 1 , wherein each respective digital twin further comprises:
a multimedia database configured to store maintenance data associated with the unique physical machine and inspection data associated with the unique physical machine.

10 . The system of claim 1 , wherein each respective digital twin is configured to:
calculate a domain-specific Condition Index (CI) value corresponding to conditions of the unique physical machine corresponding to the respective digital twin.

11 . The system of claim 10 , wherein each respective digital twin is configured to:
use an observer block operation within a simulation of the respective digital twin to calculate the domain-specific CI value.

12 . The system of claim 1 , wherein the simulation platform is configured to execute each respective simulation model using a plurality of simulation engines executing in parallel across a plurality of processors on the plurality of multiprocessor computer systems.

13 . A computer-implemented method for using a digital twin for scalable machine maintenance of a remotely located digital twin, the method comprising:
generating, by a computer system, a digital twin corresponding to a physical machine in a digital twin repository stored on the computer system by aggregating observer blocks of serial or parallel digital twin components; receiving, by the computer system, sensor data from the physical machine; storing, by the computer system, the sensor data in association with the digital twin; identifying, by the computer system, one or more required maintenance tasks for the physical machine; and sending, by the computer system, a notification of the one or more required maintenance tasks to an operator device.

14 . The method of claim 13 , wherein the digital twin is generated based on one or more of a manual associated with the physical machine or a datasheet associated with the physical machine received from the physical machine's original equipment manufacturer.

15 . The method of claim 13 , further comprising:
receiving, by the computer system, maintenance results generated in response to performance of the one or more required maintenance tasks by a maintenance engineer; and storing, by the computer system, the maintenance results in association with the digital twin.

16 . The method of claim 13 , further comprising:
receiving, by the computer system, inspection results generated in response to performance of an inspection of the physical machine; and storing, by the computer system, the inspection results in association with the digital twin.

17 . The method of claim 13 , wherein digital twin comprises a simulation model configured to simulate operation of the physical machine based on the sensor data.

18 . The method of claim 17 , wherein the one or more required maintenance tasks are identified for the physical machine using the simulation model.

19 . The method of claim 18 , further comprising:
executing the simulation model on the computer system using a plurality of simulation engines operating in parallel to identify the one or more required maintenance tasks.

20 . A system for using a digital twin for scalable machine maintenance, the system comprising:
an embedded computing sensor co-located with a physical machine and configured to:
collect monitoring data from the physical machine; and
transfer the monitoring data to a data center; and
a digital twin of the physical machine located at the data center and configured to:
identify one or more required maintenance tasks for the physical machine based on the monitoring data, and
send a notification of the one or more required maintenance tasks to an operator device.

Assignees

• Siemens Corp

Inventors

• Song Zhen
• Martinez Canedo Arquimedes

Classifications

• G06Q10/067

  Enterprise or organisation modelling · CPC title

• G06Q10/20 Primary

  Administration of product repair or maintenance · CPC title

• G05B23/0283

  Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL] (preventive maintenance, i.e. planning maintenance according to the available resources without monitoring the system G06Q10/06) · CPC title