Artificial neural network application for magnetic core width prediction and modeling for magnetic disk drive manufacture
A method for predicting and optimizing magnetic core width of a write head using neural networks to analyze manufacturing parameters, and determining new manufacturing parameters that will provide more optimal magnetic core width results. The manufacturing parameters can include: write pole flare point; wrap around shield dimension; and side gap dimension.
1. A method for manufacturing magnetic heads for magnetic data recording, comprising:
collecting data regarding manufacturing parameters;
constructing a neural network;
analyzing the data using the neural network to produce an output from the neural network; and
using the output from the neural network to optimize a magnetic core width of a magnetic write head.
2. The method as in claim 1 , wherein the data includes: a write pole flare point; a wrap around shield dimension; and a side gap.
3. The method as in claim 2 wherein the data includes a magnetic sensor stripe height and a reader/writer offset.
4. The method as in claim 1 further comprising adjusting the manufacturing parameters based on the output from the neural network to optimize the magnetic core width.
5. The method as in claim 1 wherein the neural network comprises a multi-layer network of a plurality of perceptrons.
6. The method as in claim 1 wherein the neural network comprises a multi-layer model having an input layer at least one hidden layer and an output layer.
7. The method as in claim 1 wherein the neural network comprises a feed forward neural network.
8. The method as, in claim 1 wherein the neural network comprises a plurality of feed forward neural networks.
9. The method as in claim 1 wherein the neural network includes a perceptron.
10. The method as in claim 1 wherein the neural network includes a multilayer perceptron.
11. The method as in claim 1 wherein the neural network includes a feed forward multi-layer perceptron.
12. A non-transitory computer readable medium comprising instructions for:
collecting data regarding manufacturing parameters;
constructing a neural network;
analyzing the data using the neural network to 1oroduce an output from the neural network; and
using the output from the neural network to provide new manufacturing parameters for optimizing a magnetic core width of a write head.
13. The method as in claim 12 , wherein the data includes: a write pole flare point; a wrap around shield dimension; and a side gap.
14. The method as in claim 13 wherein the data includes a magnetic sensor stripe height and a reader/writer offset.
15. The method as in claim 12 wherein the neural network comprises a multi-layer network of a plurality of perceptrons.
16. The method as in claim 12 wherein the neural network comprises a multi-layer model having an input layer at least one hidden layer and an output layer.
17. The method as in claim 12 wherein the neural network comprises a feed forward neural network.
18. The method as in claim 12 wherein the neural network comprises a plurality of feed forward neural networks.
19. The method as in claim 12 wherein the neural network includes a perceptron.
20. The method as in claim 12 wherein the neural network includes a multilayer perceptron.