Enhanced temperature control method using ANFIS with FPGA.

Area of Science:

• Semiconductor Manufacturing Technology
• Process Control Engineering
• Artificial Intelligence in Engineering

Background:

• Accurate temperature control is critical for semiconductor manufacturing, directly impacting wafer quality and etching process efficiency.
• Vacuum chamber pressure fluctuations disrupt temperature stability, leading to reduced accuracy, speed, and quality in etching processes.
• Existing methods struggle to maintain consistent temperature under dynamic pressure conditions.

Purpose of the Study:

• To develop and validate an advanced system for precise temperature regulation in semiconductor etching environments.
• To mitigate the negative effects of pressure variations on wafer temperature and etching performance.
• To enhance the overall effectiveness and reliability of the etching process through intelligent control.

Main Methods:

• Implementation of an adaptive network-based fuzzy inference system (ANFIS) for real-time temperature adjustment.
• Utilizing a field-programmable gate array (FPGA) for efficient and high-speed processing of the ANFIS algorithm.
• Dynamic adjustment of membership functions within the ANFIS to maintain stable chamber temperature despite pressure changes.

Main Results:

• The proposed ANFIS-FPGA system demonstrated significant improvement in maintaining stable wafer temperatures.
• Effective compensation for temperature fluctuations caused by vacuum pressure variations was achieved.
• Enhanced accuracy, speed, and quality of the etching process were confirmed on a medium vacuum inductively-coupled plasma (ICP) etcher.

Conclusions:

• The ANFIS-FPGA approach offers a robust solution for precise temperature control in semiconductor etching.
• This intelligent system effectively addresses the challenges posed by pressure variations in vacuum chambers.
• The validated method promises to advance semiconductor manufacturing by improving process consistency and yield.