Abstract
The main goal of the study is to make an optimization algorithm for plasma etch rate of deposited thin films by adaptive neuro fuzzy inference system (ANFIS). ANFIS represent a heuristic optimization method with back propagation training in one direction and gradient descent algorithm in backwards. The experimental training data samples are acquired for published literature. There are operating parameters which have impact on the plasma etch rate. Input attribute source power has the highest influence on the etch rate. Combination of source power and bias power has the highest influence on the etch rate. Combination of source power, bias power, and pressure has the highest influence on the etch rate. The study considering different operating parameters simultaneously is believed to be the first on a small scale and to attract the interest of everyone.
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Nikola Petrovic wrote the article.
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Petrovic, N. Optimization of plasma etch rate of deposited thin films by adaptive neuro fuzzy inference system. Int J Adv Manuf Technol 123, 111–118 (2022). https://doi.org/10.1007/s00170-022-10198-z
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DOI: https://doi.org/10.1007/s00170-022-10198-z