Additive manufacturing process plan optimization based on predicted temperature variation

1. A method for optimizing a process plan for manufacturing a workpiece by adding a material in a plurality of layers, the method comprising:

building a predicting model, the predicting model configured to predict a temperature variation of at least a portion of the workpiece;

predicting an expected temperature variation of the portion of the workpiece to be manufactured during a given time period based on the predicting model and the process plan;

adjusting the process plan in response to the expected temperature variation of the portion failing to meet a preset condition, to make the expected temperature variation of the portion meet the preset condition;

detecting a realtime temperature of at least one unit portion of the workpiece at a given moment, wherein the workpiece comprises a plurality of unit portions respectively corresponding to a plurality of voxels of a digital representation of the workpiece;

obtaining an expected temperature of the at least one unit portion at the given moment based at least in part on the predicting model and the process plan; and

calibrating the predicting model based on the realtime temperature and the expected temperature.

2. The method according to claim 1 ,

wherein the workpiece comprises a plurality of unit portions respectively corresponding to a plurality of voxels of a digital representation of the workpiece,

wherein predicting the expected temperature variation of the portion further comprises predicting a maximum temperature and a minimum temperature for each unit portion to be manufactured during the given time period, and

wherein the adjusting of the process plan further comprises adjusting the process plan in response to either the maximum temperature or the minimum temperature being outside of a preset temperature range.

3. The method according to claim 1 , wherein building the predicting model further comprises building the predicting model based on a boundary condition, a geometrical parameter of the workpiece and a property of the material of the workpiece.

4. The method according to claim 1 , wherein calibrating the predicting model further comprises calibrating at least one of a property of the material and a boundary condition of the workpiece.

5. The method according to claim 1 , wherein the process plan comprises a scanning path of a printer head, a scanning speed plan of the printer head, an energy input plan of an energy source, or a combination thereof.

6. The method according to claim 5 , wherein the scanning speed plan comprises a scanning speed variation of the printer head over time, a scanning speed variation of the printer head over space, or a combination thereof.

7. The method according to claim 5 , wherein the energy input plan comprises a power variation of the energy source over time, a power variation of the energy source over space, or a combination thereof.

8. An additive manufacturing method for manufacturing a workpiece, comprising:

adding a material in a plurality of layers to form the workpiece;

wherein adding each layer of the workpiece during a time period comprises:

predicting an expected temperature variation of the layer to be manufactured during the time period, based on a process plan and a predicting model;

if the expected temperature variation of the layer fails to meet a preset condition, adjusting the process plan to make the expected temperature variation meet the preset condition, and manufacturing the layer according to the adjusted process plan;

if the expected temperature variation of the layer meets the preset condition, manufacturing the layer according to the process plan;

detecting a realtime temperature of at least one unit portion of the workpiece at a given moment, wherein the workpiece comprises a plurality of unit portions respectively corresponding to a plurality of voxels of a digital representation of the workpiece;

obtaining an expected temperature of the at least one unit portion at the given moment based at least in part on the predicting model and the process plan; and

calibrating the predicting model based on the realtime temperature and the expected temperature.

9. The method according to claim 8 ,

wherein the workpiece comprises a plurality of unit portions respectively corresponding to a plurality of voxels of a digital representation of the workpiece,

wherein predicting the expected temperature variation of the layer further comprises predicting a maximum temperature and a minimum temperature for each unit portion in the layer during the given time period, and

wherein the adjusting of the process plan further comprises adjusting the process plan in response to either the maximum temperature or the minimum temperature being outside of a preset temperature range.

10. The method according to claim 8 , further comprising building the predicting model based on a boundary condition, a geometrical parameter of the workpiece and a property of the material of the workpiece.

11. The method according to claim 8 , further comprising making the process plan before adding the material, the process plan comprising a scanning path of a printer head, a scanning speed plan of the printer head, an energy input plan of an energy source, or a combination thereof.

12. The method according to claim 11 , wherein the scanning speed plan comprises a scanning speed variation of the printer head over time, a scanning speed variation of the printer head over space, or a combination thereof.

13. The method according to claim 11 , wherein the energy input plan comprises a power variation of the energy source over time, a power variation of the energy source over space, or a combination thereof.