System and method for conveyor system configuration, testing and diagnostics

Patent metadata

Field	Value
Publication number	US-2025074714-A1
Application number	US-202418886254-A
Country	US
Kind code	A1
Filing date	Sep 16, 2024
Priority date	Jun 30, 2021
Publication date	Mar 6, 2025
Grant date	—

Abstract

A system and method for conveyor configuration and testing. The system is configured to execute the method, which includes: receive input data relating to configuration of a conveyor system; prepare a simulation of the configured conveyor system; operate the simulation of the conveyor system; determine at least one operational parameter related to the conveyor system to be monitored; monitor the at least one operational parameter during operation of the simulation of the conveyor system; determine if the configuration of the conveyor system needs to be adjusted based on the monitored operational parameter; if the configuration needs to be adjusted, automatically make an adjustment and return to operate the simulation of the conveyor system; and continue the simulation until otherwise terminated. In some cases, the monitoring operational parameters uses a machine learning model based on actual data from operating conveyors.

First claim

What is claimed is:

1 . A method for conveyor configuration and testing, the method comprising:
receive input data relating to configuration of a conveyor system; prepare a simulation of the configured conveyor system; operate the simulation of the conveyor system; determine at least one operational parameter related to the conveyor system to be monitored; monitor the at least a first operational parameter during operation of the simulation of the conveyor system using a machine learning model, the machine learning model comprising:
at least one factor comprising at least a second operational parameter that can be generally co-related to the monitored first operational parameter in the conveyor system;
a physics model for predicting the simulated second operational parameter; and
a regression model for determining a predicted first operational parameter based on the simulated second operational parameter;
determine if the configuration of the conveyor system needs to be adjusted based on the predicted first operational parameter; if the configuration needs to be adjusted, automatically make an adjustment and return to operate the simulation of the conveyor system; and continue the simulation until otherwise terminated.

2 . A method according to claim 1 , wherein the first operational parameter comprises temperature; the at least one factor comprises current levels in the conveyor system; the physics model predicts simulated current; and the regression model determines temperature based on the simulated current.

3 . A method according to claim 1 , wherein the at least the first operational parameter comprises power usage per motor.

4 . A method according to claim 1 , wherein the determine if the configuration of the conveyor needs to be adjusted comprises:
determine if the simulated first operational parameter is outside of a predetermined range; and determine a change in at least one configuration parameter in order to change the first operational parameter.

5 . A method according to claim 1 , wherein the automatically make an adjustment comprises:
adding an additional element to the configuration in order to change the first operational parameter.

6 . A method for conveyor configuration and testing, the method comprising:
receive input data relating to configuration of a conveyor system; determine configuration parameters related to the conveyor system based on the input data; configure the conveyor system based on the configuration parameters; provide for changes to the configuration parameters; display the configuration of the conveyor system; simulate operation of the conveyor system; monitor a first operational parameter related to the conveyor system, wherein the first operational parameter is calculated based on the configuration parameters and a machine learning model based on operational data from actual conveyors, the machine learning model comprising:
at least one factor comprising at least a second operational parameter that can be generally co-related to the monitored first operational parameter in the conveyor system;
a physics model for predicting the simulated second operational parameter; and
a regression model for determining a predicted first operational parameter based on the simulated second operational parameter;
determine if configuration parameters need to be adjusted based on the predicted first operational parameter; if the configuration parameters need to be adjusted, return to receive input data, otherwise, continue the simulation until otherwise terminated.

7 . A method according to claim 6 , wherein the at least one operational parameter comprises at least one of power usage per motor and temperature.

8 . A method according to claim 6 , wherein the provide for changes comprises:
determine if the configuration parameters allow a functional conveyor system; and allow adjustment of configuration parameters by returning to receive input data.

9 . A method according to claim 6 , wherein the determine if configuration parameters need to be adjusted comprises:
determine if the at least one operational parameter is outside of a predetermined range; and suggest a change in at least one configuration parameter in order to change the at least one operational parameter.

10 . A method according to claim 10 , wherein the suggest a change in at least one configuration parameter comprises:
suggest an additional element to add to the configuration in order to change the at least one operational parameter.

11 . A system for conveyor configuration and testing, the system comprising:
a data acquisition module configured to receive input data relating to configuration of a conveyor system; a configuration module configured to prepare a digital model of a conveyor system; a simulation module configured to run a simulation of the configured conveyor system, monitor at least one operational parameter during operation of the simulation of the conveyor system using a machine learning model, and determine if the configuration of the conveyor system needs to be adjusted based on the monitored at least one operational parameter; and a results module configured to, if the configuration needs to be adjusted, automatically make an adjustment and return control to the configuration module, otherwise, to return to the simulation module to continue the simulation until otherwise terminated.

12 . A system according to claim 11 , wherein the machine learning model comprises:
at least one factor comprising current levels in the conveyor system; a physics model for determining simulated current; and a regression model for determining temperature based on the simulated current.

13 . A system according to claim 11 , wherein the results module is configured to automatically make an adjustment by adding an additional element to the configuration in order to change the at least one operational parameter.

14 . A system according to claim 11 , wherein the at least one operational parameter comprises at least one of power usage per motor and temperature.

Assignees

• Ats Corp

Inventors

• Kleinikkink Stanley
• Taylor Javan
• Ahmed Imran

Classifications

• B65G2203/045

  Thermic · CPC title

• B65G2203/0291

  Speed of the load carrier · CPC title

• B65G2203/0275

  Damage on the load carrier · CPC title

• G05B2219/2621

  Conveyor, transfert line · CPC title

• G05B2219/23446

  HIL hardware in the loop, simulates equipment to which a control module is fixed · CPC title