System and method for conveyor system configuration, testing and diagnostics

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 one 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 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;

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.

2. A method according to claim 1 , wherein the at least one operational parameter comprises at least one of power usage per motor and temperature.

3. A method according to claim 1 , wherein the determine if the configuration of the conveyor needs to be adjusted comprises:

determine if one of the operational parameters is outside of a predetermined range; and

determine a change in at least one configuration parameter in order to change the operational parameter.

4. 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 operational parameter.

5. 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 at least one operational parameter related to the conveyor system, wherein the at least one operational parameter is calculated based on the configuration parameters and a machine learning model based on operational data from actual conveyors, 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;

determine if configuration parameters need to be adjusted based on the at least one operational parameter;

if the configuration parameters need to be adjusted, return to receive input data, otherwise, continue the simulation until otherwise terminated.

6. A method according to claim 5 , wherein the at lease one operational parameter comprises at least one of power usage per motor and temperature.

7. A method according to claim 5 , 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.

8. A method according to claim 5 , 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.

9. A method according to claim 8 , 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.

10. 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 two-dimensional model of a conveyor system;

a simulation module configured to run a simulation of the configured conveyor system, monitor at least one operational parameter using a machine learning model during operation of the simulation of the conveyor system, wherein the machine learning module 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, 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.

11. A system according to claim 10 , 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.

12. A system according to claim 10 , wherein the at least one operational parameter comprises at least one of power usage per motor and temperature.