類神經模糊網路於感應藕合式蝕刻機型平台溫度控制之應用

The Application of Neural Fuzzy Network in Temperature Control of Heater Block of ICP Etcher

周俊廷(Jun-Tin Zhou)

指導教授 ： 張政元

中原大學/工學院/電機工程研究所/碩士(2011年)

https://doi.org/10.6840/cycu201100501

摘要

在半導體製程中之蝕刻技術，溫度控制為一個相當重要的因素。因為蝕刻速率的穩定與均勻性的好壞皆與溫度控制的精確度相關。
在機台設計有所缺陷的情況下，真空腔體中氣體的壓力變化，卻是造成溫度不穩定的原因之一。
本研究之目的，是在變動機台結構最少的前提之下，改善問題。因此我們發展出一套可參考壓力變化之智慧型溫度控制器，提高在蝕刻過程中溫度的穩定性，進而改善產品良率。在系統之數學模型無法精確建立之下，利用類神經模糊網路之線上學習功能，針對不同的歸屬函數調整成最佳狀態，使得溫度控制器在壓力變化過程中能夠即時達到最佳的控制效果。

關鍵字

類神經模糊網路 ； 溫度控制器

並列摘要

In the semiconductor manufacturing process of etching, temperature control is a very important factor. The stability of the etching rate and quality of uniformity are related to accuracy of temperature control. In situation that there are some defects of deigning machine, process of gas changes in vacuum chamber is one of reasons that cause the temperature becomes unstable.
To improve the problem on the premise that changes the structure of machine lowest is the purpose of this search, and therefore we develop a smart temperature controller for raising the stability of temperature in process and improving the yield. We used the learning ability of neruo-fuzzy to optimize the status of every membership functions. That will let the temperature controller achieve the optimum effect of control during pressure be changed.

並列關鍵字

temperature controller ； neural fuzzy network

參考文獻

[1] 陳衍文,“低真空環境下濕度對印刷電路板材料機械性質影響之研究”, 國立成功大學工程科學研

[4] Jyh-Shing. Roger Jang, “ANFIS：Adaptive-Network-Based Fuzzy Inference

System”, IEEE Trans on Systems, Man, and Cybern., Vol.23, No.03, pp.665-

[5] Analog devices, “AD594/AD595 Data Sheet”, 1999.

[7] Xilinx, “Spartan-3E Starter Kit Board User Guide”, 2006.