METHODS AND SYSTEMS FOR DATA COLLECTION OF MACHINE SIGNALS UTILIZING A DISTRIBUTED LEDGER FOR ANALYTICS AND MAINTENANCE USING THE INDUSTRIAL INTERNET OF THINGS

Abstract

An industrial machine predictive maintenance system may include an industrial machine data analysis facility that generates streams of industrial machine health monitoring data by applying machine learning to data representative of conditions of portions of industrial machines received via a data collection network. The system can utilize a distributed ledger to track one or more transactions executed in an automated data marketplace for industrial Internet of Things data. The distributed ledger distributes storage for data indicative of the one or more transactions across one or more devices, wherein the data indicative of the one or more transactions corresponds to transaction records. A transaction record stored in the distributed ledger represents one or more of sensor data, the condition of an industrial machine, orders or the requests for service and parts, an issue associated with the condition of a machine, or a hash used to identify the transaction record.

Claims

1. A method comprising: using a distributed ledger to track one or more transactions executed in an automated data marketplace for industrial Internet of Things data, wherein the distributed ledger distributes storage for data indicative of the one or more transactions across one or more devices, wherein the data indicative of the one or more transactions corresponds to transaction records; and using one or more mobile data collectors to generate sensor data representative of a condition of an industrial machine, wherein the sensor data is used to determine at least one of orders or requests for service and parts used to resolve an issue associated with the condition of the machine, wherein a transaction record stored in the distributed ledger represents one or more of the sensor data, the condition of the industrial machine, the at least one of the orders or the requests for service and parts, the issue associated with the condition of the machine, or a hash used to identify the transaction record.

2. The method of claim 1, wherein the distributed ledger uses a blockchain structure to store the transaction records, wherein each of the transaction records is stored as a block in the blockchain structure.

3. The method of claim 2, wherein using the blockchain structure to store the transaction records comprises: initiating a blockchain of industrial machine information for a specific industrial machine by generating an initiating block; and generating subsequent blocks of the specific industrial machine blockchain by combining data from at least one of shipment readiness, installation, operational sensor data, service events, parts orders, service orders, and diagnostic activity and a hash of the most recently generated block in the blockchain.

4. The method of claim 1, wherein each mobile data collector is one of a mobile vehicle, a mobile robot, a handheld device, or a wearable device.

5. The method of claim 1, further comprising: applying machine fault detection and classification algorithms to the sensor data to produce an industrial machine service recommendation; and producing the at least one of the orders or the requests for service and parts based on the industrial machine service recommendation.

6. The method of claim 5, wherein the one or more mobile data collectors use a computer vision system to generate the sensor data by capturing raw image data using one or more data capture devices and processing the raw image data to generate image set data, wherein the image set data is used to produce the industrial machine service recommendation.

7. A system comprising: an industrial Internet of Things (IoT) network connecting an industrial machine and one or more mobile data collectors, each mobile data collector including one or more sensors for generating sensor data indicative of conditions of the industrial machine; and a server in communication with the IoT network, the server implementing a predictive maintenance platform that uses a distributed ledger to track maintenance transactions related to the industrial machine, the distributed ledger storing transaction records corresponding to the maintenance transactions, wherein the predictive maintenance platform distributes at least some of the transaction records to the one or more mobile data collectors.

8. The system of claim 7, further comprising: a self-organizing storage system that optimizes storage of the transaction records within the distributed ledger.

9. The system of claim 7, further comprising: a self-organizing storage system that optimizes storage of maintenance data associated with the industrial machine.

10. The system of claim 7, further comprising: a self-organizing storage system that optimizes storage of IoT data associated with the IoT network.

11. The system of claim 7, further comprising: a self-organizing storage system that optimizes storage of parts and service data related to the maintenance transactions.

12. The system of claim 7, further comprising: a self-organizing storage system that optimizes storage of knowledge base data associated with the industrial machine.

13. The system of claim 7, wherein each mobile data collector is one of a mobile vehicle, a mobile robot, a handheld device, or a wearable device.

14. The system of claim 7, further comprising: an industrial machine predictive maintenance facility that produces an industrial machine service recommendation for the condition by applying machine fault detection and classification algorithms to the sensor data.

15. The system of claim 14, further comprising: a severity unit algorithm that produces a severity value for the condition based on the sensor data, wherein the industrial machine service recommendation is produced based on the severity value.

16. The system of claim 14, wherein at least one of the one or more mobile data collectors uses a computer vision system to generate the sensor data by capturing raw image data using one or more data capture devices and processing the raw image data to generate image set data, wherein the image set data is used to produce the industrial machine service recommendation.