Monitoring and Control of Semiconductor Manufacturing Using Acoustic Techniques

Acoustic sensor;Semiconductor manufacturing;Electroplating;MEMS

Williams, Frances R. ; Electrical and Computer Engineering

University:Georgia Institute of Technology

Department:Electrical and Computer Engineering

关键词: Acoustic sensor;    Semiconductor manufacturing;    Electroplating;    MEMS;   

Others  :  https://smartech.gatech.edu/bitstream/1853/5278/1/williams_frances_r_200312.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

Since semiconductor fabrication processes require numerous steps, cost and yield are critical concerns.In-situ monitoring is therefore vital for process control.However, this goal is currently restricted by the shortage of available sensors capable of performing in this manner.The goal of this research therefore, was to investigate the use of acoustic signals for monitoring and control of semiconductor fabrication equipment and processes.Currently, most methods for process monitoring (such as optical emission or interferometric techniques) rely on "looking" at a process to monitor its status. What was investigated here involved "listening" to the process.Using acoustic methods for process monitoring enhances the amount and sensitivity of data collection to facilitate process diagnostics and control.A silicon acoustic sensor was designed, fabricated, and implemented as a process monitor.Silicon acoustic sensors are favorable because of their utilization of integrated circuit and micromachining processing techniques; thus, enabling miniature devices with precise dimensions, batch fabrication of sensors, good reproducibility, and low costs.The fabricated sensor was used for in-situ monitoring of nickel-iron electrochemical deposition processes.During this process, changes occur in its plating bath as the alloy is being deposited. It is known that changes in the process medium affect the acoustic response. Thus, the sensor was implemented in an electroplating set-up and its response was observed during depositions.By mapping the sensor response received to the film thickness measured at certain times, a predictive model of the plated alloy thickness was derived as a function of sensor output and plating time.Such a model can lead to real-time monitoring of nickel-iron thickness.