Analytics for abrasive products and processes

US2024134341A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2024134341-A1
Application numberUS-202218566298-A
CountryUS
Kind codeA1
Filing dateMay 31, 2022
Priority dateJun 3, 2021
Publication dateApr 25, 2024
Grant date

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  1. Title

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  2. Abstract

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  3. Assignees and inventors

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

The present application relates to systems and methods for obtaining real-time abrasion data. An example computer-implemented method could include receiving, at a computing device, sensor data from one or more sensors. The one or more sensors are disposed in proximity to an abrasive product or a workpiece associated with the abrasive product. The one or more sensors are configured to collect abrasion operational data associated with an abrasive operation involving the abrasive product or the workpiece. The computer-implemented method could further include training, based on the sensor data, a machine learning system to determine product specific information of the abrasive product and/or workpiece specific information. The computer-implemented method could also include providing the trained machine learning system using the computing device.

First claim

Opening claim text (preview).

1 - 15 . (canceled) 16 . A computer-implemented method, comprising: receiving, at a computing device, sensor data from one or more sensors, wherein the one or more sensors are disposed in proximity to an abrasive product or a workpiece associated with the abrasive product, wherein the one or more sensors are configured to collect abrasion operational data associated with an abrasive operation involving the abrasive product or the workpiece; performing at least one of the following operations: (i) displaying, on the computing device, a cycle chart plotting at least one grinding cycle corresponding to a time range or a machine; and displaying, at the computing device, the cycle chart; (ii) determining, based on the sensor data, a grinding cycle report relating to analysis of at least one portion of a grinding cycle; and displaying, at the computing device, the grinding cycle report; or (iii) determining, based on the sensor data, a computed metric report having values of various metrics, wherein the values include an average and at least one local maxima; and displaying, at the computing device, the computed metric report. 17 . The method of claim 16 , comprising determining the grinding cycle report relating to analysis of at least one portion of the grinding cycle; and displaying, at the computing device, the grinding cycle report, wherein the grinding cycle report comprises spark time and air time related to the abrasive product. 18 . The method of claim 17 , further comprising reducing air time verses spark time of the abrasive product, reducing air time and spark time of the abrasive product, or both. 19 . The method of claim 17 , further comprising performing at least one of the following operations: (i) reducing grinding cycle time by optimizing feeds and speeds for the abrasive product; (ii) providing feedback on grinding cycle time and automatically optimizing feeds and speeds for the abrasive product; (iii) recommending proper sparkout times related to the abrasive product; (iv) suggesting increases in parts per dress for the abrasive product; or (v) suggesting time reductions relating to dressing the abrasive product. 20 . The method of claim 17 , comprising displaying, on the computing device, a cycle chart plotting at least one grinding cycle corresponding to a time range or a machine; and displaying, at the computing device, the cycle chart. 21 . The method of claim 17 , further comprising determining part cycle time across a plurality of machines. 22 . The method of claim 21 , wherein determining part cycle time comprises using present and past sensor data. 23 . The method of claim 21 , further comprising determining, at the computing device, past sensor data received at the computing device; and displaying, at the computing device, the past sensor data. 24 . The method of claim 23 , further comprising receiving an user input indicative of changing a view of the past sensor data; and displaying the changed view of the past sensor data responsive to the user input. 25 . The method of claim 16 , further comprising performing at least one of the following operations: (i) displaying, on the computing device, a plurality of datasets from the sensor data; and determining a part production quality trend; (ii) determining, based on the sensor data, an optimum feed rate and an part cycle time, wherein a machine configured to use the optimum feed rate and part will minimize grinding wheel wear; and displaying, on the computing device, at least one of the optimum feed rate and the part cycle time; (iii) determining, based on the sensor data, a sparkout time; and displaying, on the computing device, the sparkout time. 26 . The method of claim 16 , comprising displaying, on the computing device, a cycle chart plotting at least one grinding cycle corresponding to a time range or a machine; and displaying, at the computing device, the cycle chart. 27 . The method of claim 16 , comprising performing the following operation: determining, based on the sensor data, the computed metric report having values of various metrics, wherein the values include an average and at least one local maxima; and displaying, at the computing device, the computed metric report. 28 . The method of claim 16 , comprising performing at least one of the following operations: (i) determining, at the computing device, patterns or values corresponding to an operational error over a predetermined period of time; and displaying the operational error; or (ii) receiving, at the computing device, data corresponding to a user input; determining, from the sensor data and data corresponding to the user input, cost reductions achieved through at least one of process optimization and troubleshooting; and displaying the cost reductions. 29 . The method of claim 16 , further comprising receiving, at the computing device, a user input indicating an organization of data; determining, based on the sensor data, a machine downtime report; based on the user input, organizing the machine downtime report; and determining, from the sensor data, an operator efficiency report; in response to receiving the sensor data, determining an operation metrics report; and selecting data organization types. 30 . The method of claim 16 , further comprising receiving, at the computing device, a user input indicating a data organization type wherein the data organization type includes by machine, by operator, or by process; determining, based on the sensor data and the data organization type, a setup time report; determining, based on the sensor data, a shift variation report, wherein the shift variation report provides information indicative of metric variations across a plurality of work shifts; and determining, based on the sensor data, a machine comparison report, wherein the machine comparison report provides information indicative of similar processes occurring on different machines; and displaying, on the computing device, at least one displayed report, wherein the displayed report comprises at least one of the downtime report, the operation metrics report, a setup time report, the shift variation report, or the machine comparison report. 31 . A system, comprising: a computing device configured to: receive sensor data from one or more sensors, wherein the one or more sensors are disposed in proximity to an abrasive product or a workpiece associated with the abrasive product, wherein the one or more sensors are configured to collect abrasion operational data associated with an abrasive operation involving the abrasive product or the workpiece; determine, based on the sensor data, a grinding cycle report relating to the analysis of at least one portion of a grinding cycle; and display, via a user interface, the grinding cycle report, wherein the grinding cycle report comprises spark time and/or air time related to the abrasive product. 32 . The system of claim 31 , wherein the computing device is configured to: determine, based on the sensor data, a computed metric report having values of various metrics, wherein the values include an average and at least one local maxima; and display, via the user interface at the computing device, the computed metric report. 33 . The system of claim 31 , wherein the computing device is configured to display, via the user interface, a cycle chart plotting at least one grinding cycle corresponding to a time range or a machine. 34 . The system of claim 31 , wherein the computin

Assignees

Inventors

Classifications

  • Monitoring tool breakage, life or condition · CPC title

  • Measuring or gauging equipment for controlling the feed movement of the grinding tool or work; Arrangements of indicating or measuring equipment, e.g. for indicating the start of the grinding operation (B24B33/06, B24B37/005 take precedence; if applicable to other machine tools, B23Q15/00 - B23Q17/00 take precedence) · CPC title

  • Life of tool, service life, decay, wear estimation · CPC title

  • Machine learning · CPC title

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What does patent US2024134341A1 cover?
The present application relates to systems and methods for obtaining real-time abrasion data. An example computer-implemented method could include receiving, at a computing device, sensor data from one or more sensors. The one or more sensors are disposed in proximity to an abrasive product or a workpiece associated with the abrasive product. The one or more sensors are configured to collect ab…
Who is the assignee on this patent?
Saint Gobain Abrasives Inc, Saint Gobain Abrasifs Sa
What technology area does this patent fall under?
Primary CPC classification G05B19/4065. Mapped technology areas include Physics.
When was this patent published?
Publication date Thu Apr 25 2024 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).