Systems and methods for receiving sensor data for an operating manufacturing machine and producing an alert during manufacture of a part

• US 9,977,425 B1
• Filed: 07/14/2017
• Issued: 05/22/2018
• Est. Priority Date: 07/14/2017
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: McCann, Adam, Berlier, Jacob, Zhang, Li, Good, Brandon
• Primary Examiner(s): Paul, Antony M
• Application Number:
  US15/649,871
• Time in Patent Office: 312 Days
• Field of Search: 700 95, 700 96, 700 98, 700114, 700116, 700153, 700163, 700159, 700182, 700192, 700188, 700178, 700204, 700195, 700249, 700258, 700299, 700179, 700197, 29 33 R, 295642, 29650, 29700, 29712, 31840001, 318700, 318701, 318721, 318727, 318799, 318471, 318472
• CPC Class Codes: B22F 10/28 Powder bed fusion, e.g. selective laser melting [SLM] or electron beam melting [EBM]
• CPC Class Codes: B22F 10/368 Temperature or temperature gradient, e.g. temperature of the melt pool
• CPC Class Codes: B22F 10/38 to achieve specific product aspects, e.g. surface smoothness, density, porosity or hollow structures
• CPC Class Codes: B22F 10/85 for controlling or regulating additive manufacturing processes
• CPC Class Codes: B22F 12/90 Means for process control, e.g. cameras or sensors
• CPC Class Codes: B29C 64/00 Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
• CPC Class Codes: B29C 64/393 for controlling or regulating additive manufacturing processes
• CPC Class Codes: B33Y 10/00 Processes of additive manufacturing
• CPC Class Codes: B33Y 30/00 Apparatus for additive manufacturing; Details thereof or accessories therefor
• CPC Class Codes: B33Y 50/02 for controlling or regulating additive manufacturing processes
• CPC Class Codes: G05B 19/4063 Monitoring general control system G05B19/4062 takes precedence
• CPC Class Codes: G05B 19/4099 Surface or curve machining, making 3D objects, e.g. desktop manufacturing
• CPC Class Codes: G05B 2219/49018 Laser sintering of powder in layers, selective laser sintering SLS
• CPC Class Codes: G05B 2223/02 Indirect monitoring, e.g. monitoring production to detect faults of a system
• CPC Class Codes: G05B 23/0221 Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
• CPC Class Codes: G05B 23/027 Alarm generation, e.g. communication protocol; Forms of alarm
• CPC Class Codes: G05B 23/0272 Presentation of monitored results, e.g. selection of status reports to be displayed; Filtering information to the user
• CPC Class Codes: G05B 23/0283 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 Class Codes: G06F 3/12 Digital output to print unit , e.g. line printer, chain printer
• CPC Class Codes: G06F 3/1208 resulting in improved quality of the output result, e.g. print layout, colours, workflows, print preview
• CPC Class Codes: G06F 3/1254 : Automatic configuration, e.g. by driver
• CPC Class Codes: G06F 3/1259 : Print job monitoring, e.g. job status
• CPC Class Codes: G06N 20/00 : Machine learning
• CPC Class Codes: G06Q 10/06395 : Quality analysis or management
• CPC Class Codes: G06Q 10/20 : Administration of product repair or maintenance
• CPC Class Codes: Y02D 10/00 : Energy efficient computing, e.g. low power processors, power management or thermal management
• CPC Class Codes: Y02P 10/25 : Process efficiency
• CPC Class Codes: Y02P 90/02 : Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

Method, and corresponding system, for producing an alert during manufacture of a part formed by a plurality of layers. The method includes determining the sensor data values at the working tool positions of each of the plurality of layers based on a correlation of the values of the sensor data relative to time and the working tool positions of each of the plurality of layers relative to time. During the manufacturing process, the sensor data values at the working tool positions of at least one of the plurality of layers are compared to reference data values at the working tool positions for the at least one layer to determine a comparison measure for the at least one layer. An alert is transmitted if the determined comparison measure of a layer is not within a defined range. A defined action is applied to the manufacturing process based on the transmitted alert.

Claims

1. A method for receiving sensor data for an operating manufacturing machine and producing an alert during manufacture of a part formed by a plurality of layers, the method comprising:

receiving, at a first server, the sensor data from a sensor for the operating machine;

determining, using a processor of the first server, values of the sensor data relative to time;

determining, using the processor of the first server, working tool positions relative to time based on process data which controls operation of the manufacturing machine, the process data comprising vectors defining the working tool positions of each of the plurality of layers during a manufacturing process;

determining the sensor data values at the working tool positions of each of the plurality of layers based on a correlation of the values of the sensor data relative to time and the working tool positions of each of the plurality of layers relative to time;

comparing, during the manufacturing process, the sensor data values at the working tool positions of at least one of the plurality of layers to reference data values at the working tool positions for the at least one layer to determine a comparison measure for the at least one layer;

transmitting an alert if the determined comparison measure of a layer is not within a defined range; and

applying a defined action to the manufacturing process based on the transmitted alert.

2. The method of claim 1, further comprising, before the comparing, applying a probabilistic function to the reference data values at the working tool positions for the at least one layer.

3. The method of claim 1, further comprising:

receiving, at a second server, the sensor data values at the working tool positions of a fabricated layer;

receiving image data produced at the manufacturing machine for the fabricated layer; and

correlating the image data to the working tool positions of the fabricated layer.

4. The method of claim 3, wherein the correlating of the image data to the working tool positions comprises converting high intensity lines of the image data into vectors.

5. The method of claim 3, further comprising comparing, during the manufacturing process, the image data of at least one of the plurality of layers to reference image data for the at least one layer to determine a second comparison measure for the at least one layer.

6. The method of claim 5, wherein the reference image data of the at least one layer are determined by analysis of a reference part.

7. The method of claim 1, further comprising:

outputting the comparison measure for the at least one layer to an analytic model of the manufacturing machine;

receiving, from the analytic model of the manufacturing machine, adjusted process data, the adjusted process data being determined based at least in part on the analytic model and the comparison measure for the at least one layer, the analytic model being based at least in part on a measured characteristic of the manufacturing machine; and

using the adjusted process data to control the operation of the manufacturing machine.

8. The method of claim 1, wherein the reference data values at the working tool positions of the at least one layer are determined by analysis of a reference part.

9. The method of claim 8, wherein the reference data values at the working tool positions of the at least one layer are determined based on a correlation of values of sensor data relative to time measured for the reference part and working tool positions of a corresponding layer of the reference part relative to time, and

the working tool positions of the corresponding layer of the reference part relative to time are determined based on process data comprising vectors defining the working tool positions of the corresponding layer of the reference part during a manufacturing process of the reference part.

10. The method of claim 1, wherein the method further comprises transmitting the alert via a network to at least one user interface device.

11. The method of claim 1, wherein the alert identifies the layer for which the alert was produced.

12. The method of claim 1, wherein the defined action is halting the manufacturing process.

13. A method for receiving sensor data for an operating manufacturing machine and producing an alert during manufacture of a part formed by a plurality of layers, the method comprising:

receiving, at a first server, the sensor data from a sensor for the operating machine;

determining, using a processor of the first server, values of the sensor data relative to time;

determining, using the processor of the first server, working tool positions relative to time based on process data which controls operation of the manufacturing machine, the process data comprising vectors defining the working tool positions of each of the plurality of layers during a manufacturing process;

determining the sensor data values at the working tool positions of each of the plurality of layers based on a correlation of the values of the sensor data relative to time and the working tool positions of each of the plurality of layers relative to time;

determining a quality score of at least one of the plurality of layers using a machine learning algorithm, the machine learning algorithm being trained based at least in part on sensor data from another machine manufacturing a same part;

comparing, during the manufacturing process, the quality score of at least one of the plurality of layers to a quality threshold for the at least one layer to determine a comparison measure for the at least one layer;

transmitting an alert if the determined comparison measure of a layer is not within a defined range; and

applying a defined action to the manufacturing process based on the transmitted alert.

14. A system for receiving sensor data for an operating manufacturing machine and producing an alert during manufacture of a part formed by a plurality of layers, the system comprising:

a first server having a processor configured to perform;

receiving, at a first server, the sensor data from a sensor for the operating machine;

determining, using a processor of the first server, values of the sensor data relative to time;

determining, using the processor of the first server, working tool positions relative to time based on process data which controls operation of the manufacturing machine, the process data comprising vectors defining the working tool positions of each of the plurality of layers during a manufacturing process;

determining the sensor data values at the working tool positions of each of the plurality of layers based on a correlation of the values of the sensor data relative to time and the working tool positions of each of the plurality of layers relative to time;

comparing, during the manufacturing process, the sensor data values at the working tool positions of at least one of the plurality of layers to reference data values at the working tool positions for the at least one layer to determine a comparison measure for the at least one layer;

transmitting an alert if the determined comparison measure of a layer is not within a defined range; and

applying a defined action to the manufacturing process based on the transmitted alert.

15. The system of claim 14, wherein the first server is further configured to perform, before the comparing, applying a probabilistic function to the reference data values at the working tool positions for the at least one layer.

16. The system of claim 15, wherein the correlating of the image data to the working tool positions comprises converting high intensity lines of the image data into vectors.

17. The system of claim 15, wherein the second server is further configured to perform comparing, during the manufacturing process, the image data of at least one of the plurality of layers to reference image data for the at least one layer to determine a second comparison measure for the at least one layer.

18. The system of claim 14, further comprising a second server having a processor configured to perform:

receiving, at a second server, the sensor data values at the working tool positions of a fabricated layer;

receiving image data produced at the manufacturing machine for the fabricated layer; and

correlating the image data to the working tool positions of the fabricated layer.

19. The system of claim 14, wherein the first server is further configured to perform:

outputting the comparison measure for the at least one layer to an analytic model of the manufacturing machine;

receiving, from the analytic model of the manufacturing machine, adjusted process data, the adjusted process data being determined based at least in part on the analytic model and the comparison measure for the at least one layer, the analytic model being based at least in part on a measured characteristic of the manufacturing machine; and

using the adjusted process data to control the operation of the manufacturing machine.

20. The system of claim 14, wherein the reference data values at the working tool positions of the at least one layer are determined based on a correlation of values of sensor data relative to time measured for a reference part and working tool positions of a corresponding layer of the reference part relative to time, and

the working tool positions of the corresponding layer of the reference part relative to time are determined based on process data comprising vectors defining the working tool positions of the corresponding layer of the reference part during a manufacturing process of the reference part.