Systems, Methods, and Media for Manufacturing Processes

1 . A manufacturing system, comprising:

one or more stations, each station configured to perform at least one step in a multi-step manufacturing process for a component;

a monitoring platform configured to monitor progression of the component throughout the multi-step manufacturing process; and

a control module configured to dynamically adjust processing parameters of each step of the multi-step manufacturing process to achieve a desired final quality metric for the component, the control module configured to perform operations, comprising:

receiving, from the monitoring platform, an input associated with the component at a step of the multi-step manufacturing process;

determining, by the control module, that at least a first step of a plurality of steps has not experienced an irrecoverable failure and that at least a second step of the plurality of steps has experienced the irrecoverable failure;

based on the determining, generating, by the control module, a state encoding for the component based on the input;

determining, by the control module, based on the state encoding and the input of the component that the final quality metric is not within a range of acceptable values; and

based on the determining, adjusting by the control module, control logic for at least a following station, wherein the adjusting comprising a corrective action to be performed by the following station and an instruction to cease processing of at least the second step.

2 . The manufacturing system of claim 1 , wherein the final quality metric cannot be measured until processing of the component is complete.

3 . The manufacturing system of claim 1 , wherein adjusting, by the control module, the control logic for at least the following station, comprises:

identifying the corrective action to be performed by the following station; and

projecting the final quality metric based on the corrective action and the state encoding.

4 . The manufacturing system of claim 1 , wherein the operations further comprise:

training a convolutional neural network to identify when the irrecoverable failure is present.

5 . The manufacturing system of claim 4 , wherein the input comprises an image and wherein the control module determines that the irrecoverable failure is present using a convolutional neural network.

6 . The manufacturing system of claim 1 , wherein adjusting by the control module, the control logic for at least the following station, comprises:

adjusting a further control logic for a further following station.

7 . The manufacturing system of claim 1 , wherein each of the one or more processing stations correspond to a layer deposition in a 3D printing process.

8 . A multi-step manufacturing method, comprising:

receiving, by a computing system from a monitoring platform of a manufacturing system, an image of a component at a station of one or more stations, each station configured to perform a step of a multi-step manufacturing process;

determining, by the computing system, that at least a first step of a plurality of steps has not experienced an irrecoverable failure and that at least a second step of the plurality of steps has experienced the irrecoverable failure;

based on the determining, generating, by the computing system, a state encoding for the component based on the image of the component;

determining, by the computing system, based on the state encoding and the image of the component that a final quality metric of the component is not within a range of acceptable values; and

based on the determining, adjusting by the computing system, control logic for at least a following station, wherein the adjusting comprising a corrective action to be performed by the following station and an instruction to cease processing of at least the second step.

9 . The multi-step manufacturing method of claim 8 , wherein the final quality metric cannot be measured until processing of the component is complete.

10 . The multi-step manufacturing method of claim 8 , wherein adjusting, by the computing system, the control logic for at least the following station, comprises:

identifying the corrective action to be performed by the following station; and

projecting the final quality metric based on the corrective action and the state encoding.

11 . The multi-step manufacturing method of claim 8 , further comprising:

training, by the computing system, a convolutional neural network to identify when the irrecoverable failure is present.

12 . The multi-step manufacturing method of claim 11 , wherein the computing system determines that an irrecoverable failure is present using a convolutional neural network.

13 . The multi-step manufacturing method of claim 8 , wherein adjusting by the computing system, the control logic for at least the following station, comprises:

adjusting a further control logic for a further following station.

14 . The multi-step manufacturing method of claim 8 , wherein each of the one or more stations correspond to a layer deposition in a 3D printing process.

15 . A three-dimensional (3D) printing system, comprising:

a processing station configured to deposit a plurality of layers to form a component;

a monitoring platform configured to monitor progression of the component throughout a deposition process; and

a control module configured to dynamically adjust processing parameters for each layer of the plurality of layers to achieve a desired final quality metric for the component, the control module configured to perform operations, comprising:

receiving, from the monitoring platform, an image of the component after a layer has been deposited;

determining, by the control module, that at least a first step of a plurality of steps has not experienced an irrecoverable failure and that at least a second step of the plurality of steps has experienced the irrecoverable failure;

generating, by the control module, a state encoding for the component based on the image of the component;

determining, by the control module, based on the state encoding and the image of the component that the final quality metric is not within a range of acceptable values; and

based on the determining, adjusting, by the control module, control logic for depositing at least a following layer of the plurality of layers, wherein the adjusting comprising a corrective action to be performed during deposition of the following layer and an instruction to cease processing of at least the second step.

16 . The system of claim 15 , wherein the final quality metric cannot be measured until processing of the component is complete.

17 . The system of claim 15 , wherein adjusting, by the control module, the control logic for depositing at least the following layer, comprises:

identifying the corrective action to be performed during deposition of the following layer; and

projecting the final quality metric based on the corrective action and the state encoding.

18 . The system of claim 15 , further comprising:

training a convolutional neural network to identify when the irrecoverable failure is present.

19 . The system of claim 18 , wherein the control module determines that the irrecoverable failure is present using the convolutional neural network.

20 . The system of claim 15 , wherein adjusting the control logic for depositing at least the following layer, comprises:

adjusting a further control logic for a further following layer.