Assembly error correction for assembly lines
Aspects of the disclosed technology provide a computational model that utilizes machine learning for detecting errors during a manual assembly process and determining a sequence of steps to complete the manual assembly process in order to mitigate the detected errors. In some implementations, the disclosed technology evaluates a target object at a step of an assembly process where an error is detected to a nominal object to obtain a comparison. Based on this comparison, a sequence of steps for completion of the assembly process of the target object is obtained. The assembly instructions for creating the target object are adjusted based on this sequence of steps.
1. A method for optimizing workflow in an assembly line, the method comprising:
receiving image data tracking assembly of a target object through a manufacturing process;
identifying a subset of image data corresponding to a step in the manufacturing process;
analyzing the subset of the image data to identify data associated with an operator performing the step in the manufacturing process on the target object;
analyzing the subset of the image data to identify the target object upon which the operator is performing the step;
determining that the target object is out of specification by:
comparing the data associated with the operator performing the step in the manufacturing process on the target object to nominal data associated with a nominal operator performing the step in the manufacturing process, and
comparing the target object at the step of the manufacturing process to a nominal target object; and
based on the determining, adjusting subsequent steps in the manufacturing process to bring the target object into specification.
2. The method of claim 1 , wherein determining that the target object is out of specification comprises:
determining a similarity between the data associated with the operator performing the step in the manufacturing process and the nominal data associated with the nominal operator performing the step in the manufacturing process.
3. The method of claim 1 , wherein determining that the target object is out of specification comprises:
determining a similarity between a first surface of the target object and a second surface of the nominal target object.
4. The method of claim 3 , wherein determining that the target object is out of specification comprises:
detecting an anomaly present on the first surface of the target object.
5. The method of claim 4 , wherein determining that the target object is out of specification comprises:
generating a quality score for the target object based on one or more of the determined similarity or the detected anomaly.
6. The method of claim 1 , wherein adjusting the subsequent steps in the manufacturing process to bring the target object into specification comprises:
minimizing a deviation between the target object and the nominal target object using a Markov Decision Process.
7. The method of claim 1 , wherein adjusting the subsequent steps in the manufacturing process to bring the target object into specification comprises:
deriving an updated sequence of steps to correct for errors in the target object.
8. A system comprising:
a processor; and
a memory having programming instructions stored thereon, which, when executed by the processor, causes a computing system to perform operations comprising:
receiving image data tracking assembly of a target object through a manufacturing process;
identifying a subset of image data corresponding to a step in the manufacturing process;
analyzing the subset of the image data to identify data associated with an operator performing the step in the manufacturing process on the target object;
analyzing the subset of the image data to identify the target object upon which the operator is performing the step;
determining that the target object is out of specification by:
comparing the data associated with the operator performing the step in the manufacturing process on the target object to nominal data associated with a nominal operator performing the step in the manufacturing process, and
comparing the target object at the step of the manufacturing process to a nominal target object; and
based on the determining, adjusting subsequent steps in the manufacturing process to bring the target object into specification.
9. The system of claim 8 , wherein determining that the target object is out of specification comprises:
determining a similarity between the data associated with the operator performing the step in the manufacturing process and the nominal data associated with the nominal operator performing the step in the manufacturing process.
10. The system of claim 8 , wherein determining that the target object is out of specification comprises:
determining a similarity between a first surface of the target object and a second surface of the nominal target object.
11. The system of claim 10 , wherein determining that the target object is out of specification comprises:
detecting an anomaly present on the first surface of the target object.
12. The system of claim 11 , wherein determining that the target object is out of specification comprises:
generating a quality score for the target object based on one or more of the determined similarity or the detected anomaly.
13. The system of claim 8 , wherein adjusting the subsequent steps in the manufacturing process to bring the target object into specification comprises:
minimizing a deviation between the target object and the nominal target object using a Markov Decision Process.
14. The system of claim 8 , wherein adjusting the subsequent steps in the manufacturing process to bring the target object into specification comprises:
deriving an updated sequence of steps to correct for errors in the target object.
15. A non-transitory computer readable medium comprising one or more sequences of instructions, which, when executed by a processor, causes a computing system to perform operations comprising:
receiving image data tracking assembly of a target object through a manufacturing process;
identifying a subset of image data corresponding to a step in the manufacturing process;
analyzing the subset of the image data to identify data associated with an operator performing the step in the manufacturing process on the target object;
analyzing the subset of the image data to identify the target object upon which the operator is performing the step;
determining that the target object is out of specification by:
comparing the data associated with the operator performing the step in the manufacturing process on the target object to nominal data associated with a nominal operator performing the step in the manufacturing process, and
comparing the target object at the step of the manufacturing process to a nominal target object; and
based on the determining, adjusting subsequent steps in the manufacturing process to bring the target object into specification.
16. The non-transitory computer readable medium of claim 15 , wherein determining that the target object is out of specification comprises:
determining a similarity between the data associated with the operator performing the step in the manufacturing process and the nominal data associated with the nominal operator performing the step in the manufacturing process.
17. The non-transitory computer readable medium of claim 15 , wherein determining that the target object is out of specification comprises:
determining a similarity between a first surface of the target object and a second surface of the nominal target object.
18. The non-transitory computer readable medium of claim 17 , wherein determining that the target object is out of specification comprises:
detecting an anomaly present on the first surface of the target object.
19. The non-transitory computer readable medium of claim 18 , wherein determining that the target object is out of specification comprises:
generating a quality score for the target object based on one or more of the determined similarity or the detected anomaly.
20. The non-transitory computer readable medium of claim 15 , wherein adjusting the subsequent steps in the manufacturing process to bring the target object into specification comprises:
deriving an updated sequence of steps to correct for errors in the target object.