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On the Identification of Physical Sources of Vibration Sensor Signal Patterns in Chemical Mechanical Planarization (CMP) Process


Affiliations
1 School of Mech., & Aerospace Engg, Oklahoma State University, Stillwater, Oklahoma, United States
2 School of Industrial Engg., & Management, Oklahoma State University, Stillwater, Oklahoma, United States
3 Central Manufacturing Technology Institute, Bangalore, India
4 Dept. of Mech. Engg., Indian Institute of Technology, Chennai, Tamil Nadu, India
5 School of Industrial Engg., & Management, Oklahoma State University, Stillwater, Oklahoma, India
     

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This document presents the battery of tests conducted to ascertain the physical sources of dominant vibration sensor signal patterns observed in chemical mechanical planarization (CMP) process. A Buehler (model Automet® 250) bench top CMP machine is instrumented with miniature MEMS 3-axis accelerometer (Analog Devices ADXL 335) and audio sensors (Analog Devices ADMP 401). The CMP setup is used for finishing blanket copper workpieces to a surface finish of Ra ~ 5 nm. While the sensor signals are sensitive to variations in the CMP process, the extraneous noise prevents the direct use of raw signal patterns for early detection of defects. Consequently, instead of primarily monitoring the raw sensor signal patters, we isolate signal features which are indicative of process state from those which are mere artifacts, and thus potentially valuable for process monitoring.

The frequency spectrum of typical MEMS vibration sensor signals acquired during the CMP process contains three dominant components, namely:

1. Low frequency component in the 0.5 - 1 Hz region.

2. Broadband frequency regions centered around 25 Hz and 50 Hz.

3. Broadband frequency region around 120 Hz.

A total of nine tests are reported to ascertain the underlying physical cause of each of these components. Component 1 is shown to result from eccentricity errors in the polishing head (spindle); component 2 is most likely a conjoined effect due to sensor characteristics, electromagnetic interference from machine elements, and structural vibration; component 3 is observed to respond to changing downforce (polishing load) conditions, and process state, such as pad wear, and as such is useful for process monitoring applications. In addition, a relatively small (-110 dB) background (white) noise is evident throughout the frequency spectrum of CMP vibration signals; this is explained as originating from measurement errors and environmental factors.


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  • On the Identification of Physical Sources of Vibration Sensor Signal Patterns in Chemical Mechanical Planarization (CMP) Process

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Authors

Ranga Komanduri
School of Mech., & Aerospace Engg, Oklahoma State University, Stillwater, Oklahoma, United States
Prahalad Rao
School of Industrial Engg., & Management, Oklahoma State University, Stillwater, Oklahoma, United States
Prakash Vinod
Central Manufacturing Technology Institute, Bangalore, India
Omer Beyca
School of Industrial Engg., & Management, Oklahoma State University, Stillwater, Oklahoma, United States
Sanjay Jagannath
Dept. of Mech. Engg., Indian Institute of Technology, Chennai, Tamil Nadu, India
Adam Fields
School of Industrial Engg., & Management, Oklahoma State University, Stillwater, Oklahoma, India
Zhenyu Kong
School of Industrial Engg., & Management, Oklahoma State University, Stillwater, Oklahoma, India
Satish Bukkapatnam
School of Industrial Engg., & Management, Oklahoma State University, Stillwater, Oklahoma, India

Abstract


This document presents the battery of tests conducted to ascertain the physical sources of dominant vibration sensor signal patterns observed in chemical mechanical planarization (CMP) process. A Buehler (model Automet® 250) bench top CMP machine is instrumented with miniature MEMS 3-axis accelerometer (Analog Devices ADXL 335) and audio sensors (Analog Devices ADMP 401). The CMP setup is used for finishing blanket copper workpieces to a surface finish of Ra ~ 5 nm. While the sensor signals are sensitive to variations in the CMP process, the extraneous noise prevents the direct use of raw signal patterns for early detection of defects. Consequently, instead of primarily monitoring the raw sensor signal patters, we isolate signal features which are indicative of process state from those which are mere artifacts, and thus potentially valuable for process monitoring.

The frequency spectrum of typical MEMS vibration sensor signals acquired during the CMP process contains three dominant components, namely:

1. Low frequency component in the 0.5 - 1 Hz region.

2. Broadband frequency regions centered around 25 Hz and 50 Hz.

3. Broadband frequency region around 120 Hz.

A total of nine tests are reported to ascertain the underlying physical cause of each of these components. Component 1 is shown to result from eccentricity errors in the polishing head (spindle); component 2 is most likely a conjoined effect due to sensor characteristics, electromagnetic interference from machine elements, and structural vibration; component 3 is observed to respond to changing downforce (polishing load) conditions, and process state, such as pad wear, and as such is useful for process monitoring applications. In addition, a relatively small (-110 dB) background (white) noise is evident throughout the frequency spectrum of CMP vibration signals; this is explained as originating from measurement errors and environmental factors.