Systems and methods of predictive manufacturing of three-dimensional, multi-planar semiconductors
Predictive multi-planar semiconductor manufacturing systems and methods are provided including a processor, an artificial intelligence unit in communication with the processor, and a computer readable memory with processing instructions in communication with the processor. The manufacturing system receives and analyzes semiconductor design and manufacturing process rules and data and dimensions for a user's desired semiconductor. The artificial intelligence unit is configured to run simulations trying multiple three-dimensional, multi-planar shapes and analyzing for highest surface area yield based on the design and manufacturing process rules and data and the dimensions. The artificial intelligence unit is further configured to determine a three-dimensional, multi-planar shape for the desired semiconductor to optimize surface area based on the simulations and to construct the three-dimensional, multi-planar shape that optimizes surface area.
1. A method of predictive semiconductor manufacturing comprising:
receiving and analyzing semiconductor design and manufacturing process rules and data;
receiving and analyzing dimensions for a user's desired semiconductor;
running simulations trying multiple three-dimensional, multi-planar shapes and analyzing for highest surface area yield based on the design and manufacturing process rules and data and the dimensions;
determining a three-dimensional, multi-planar shape for the desired semiconductor to optimize surface area based on the simulations; and
constructing the three-dimensional, multi-planar shape that optimizes surface area.
2. The method of claim 1 wherein the analyzing for highest surface area yield comprises placing test chips on surfaces of the multiple three-dimensional, multi-planar shapes.
3. The method of claim 1 wherein trying multiple three-dimensional, multi-planar shapes comprises starting with a simple shape and increasing a number of surface planes to more complex three-dimensional, multi-planar shapes.
4. The method of claim 3 further comprising studying each shape and its optimization capabilities.
5. The method of claim 3 further comprising running a simulated optimal thermal dissipation test on each shape.
6. The method of claim 1 wherein the semiconductor design and manufacturing process rules comprise one or more of: process geometrical design rules, connectivity design rules, design for manufacturing rules, electrical rules, and reliability rules.
7. The method of claim 1 further comprising simulating packaging to fit the constructed three-dimensional, multi-planar shape.
8. The method of claim 1 further comprising testing the three-dimensional, multi-planar shapes for electrical connectivity and reliability.
9. A predictive multi-planar semiconductor manufacturing system comprising:
a processor;
an artificial intelligence unit in communication with the processor; and
a computer readable memory in communication with the processor, the computer readable memory containing processing instructions;
the manufacturing system receiving and analyzing semiconductor design and manufacturing process rules and data and dimensions for a user's desired semiconductor;
the artificial intelligence unit being configured to run simulations trying multiple three-dimensional, multi-planar shapes and analyzing for highest surface area yield based on the design and manufacturing process rules and data and the dimensions;
the artificial intelligence unit being configured to determine a three-dimensional, multi-planar shape for the desired semiconductor to optimize surface area based on the simulations and to construct the three-dimensional, multi-planar shape that optimizes surface area.
10. The manufacturing system of claim 9 further comprising a graphical user interface displaying the constructed three-dimensional, multi-planar shape that optimizes surface area.
11. The manufacturing system of claim 10 wherein the graphical user interface displays analytics for one or more of the three-dimensional, multi-planar shapes, the analytics comprising one or more of: simulation results, surface thermal maps, connectivity maps, and estimated yield area.
12. The manufacturing system of claim 10 wherein the graphical user interface displays statistics including silicon area utilization percentages for one or more of the three-dimensional, multi-planar shapes.
13. The manufacturing system of claim 9 wherein the artificial intelligence unit further comprises a neural network;
wherein the neural network mathematically models semiconductor manufacturing methods and tries multiple three-dimensional, multi-planar shapes starting with a simple shape and increasing a number of surface planes to more complex three-dimensional, multi-planar shapes.
14. The manufacturing system of claim 13 wherein the neural network has cognitive capabilities, learning from its operations to improve the three-dimensional, multi-planar shapes of the semiconductors.
15. The manufacturing system of claim 9 where the three-dimensional, multi-planar shape that optimizes surface area is comprised of segmented data points, creating a unique data set.
16. The manufacturing system of claim 9 wherein the system is configured to receive fabrication apparatus data.
17. The manufacturing system of claim 9 wherein the desired semiconductor is an existing semiconductor; and
wherein the artificial intelligence unit determines a three-dimensional, multi-planar shape for the existing semiconductor.
18. The manufacturing system of claim 9 wherein the artificial intelligence unit places test chips on surfaces of the multiple three-dimensional, multi-planar shapes.
19. The manufacturing system of claim 9 wherein the artificial intelligence unit simulates packaging to fit the constructed three-dimensional, multi-planar shape.
20. The manufacturing system of claim 9 wherein the artificial intelligence unit performs an electrothermal flow analysis on the multiple three-dimensional, multi-planar shapes.