Surface Microdefects Control during Chemical Mechanical Polishing of Silicon Wafers: an Example of in line Manufacturing Process Control

2019 ◽  
Vol 10 (1) ◽  
pp. 75-83
Author(s):  
Gabriella Borionetti ◽  
Alessandro Corradi ◽  
Nicola Mainardi ◽  
Antonio M. Rinaldi ◽  
Keiichi Takami
Keyword(s):  
Process Control ◽  
Chemical Mechanical Polishing ◽  
Manufacturing Process ◽  
Silicon Wafers ◽  
Mechanical Polishing ◽  
Manufacturing Process Control

Discrete part manufacturing process control with quality considerations

1992 ◽  
Vol 30 (8) ◽  
pp. 1889-1899
Author(s):  
ROBERT P. DAVIS ◽  
WILLIAM G. FERRELL ◽  
SANKAR SENGUPTA
Keyword(s):  
Process Control ◽  
Manufacturing Process ◽  
Manufacturing Process Control ◽  
Discrete Part

Slurry Residue Removal in Post Chemical Mechanical Polishing

1999 ◽  
Author(s):  
Ahmed A. Busnaina ◽  
Naim Moumen
Keyword(s):  
Chemical Mechanical Polishing ◽  
Silicon Wafers ◽  
Mechanical Polishing ◽  
Operating Conditions ◽  
Cleaning Process ◽  
Megasonic Cleaning ◽  
Residue Removal ◽  
Particulate Contamination

Abstract The megasonic cleaning process proved to be an essential process in cleaning silicon wafers after processes such as pre-oxidation, pre-CVD, pre-EPI, post-ASH and lately post-CMP. Current post-CMP cleans are contact cleaning techniques. These contact techniques have a low throughput and may cause wafer scratching. In addition, in contact cleaning, brush shedding which occurs under many operating conditions causes additional particulate contamination. There is a need for an effective post-CMP cleaning process. Megasonic cleaning provides the best alternative or compliment to brush clean.

Shape verification aimed for manufacturing process control

2011 ◽  
Vol 49 (3) ◽  
pp. 403-409 ◽  
Author(s):  
Per Bergström ◽  
Sara Rosendahl ◽  
Mikael Sjödahl
Keyword(s):  
Process Control ◽  
Manufacturing Process ◽  
Manufacturing Process Control

Neural Network Based Run-to-Run Process Controller for Copper Chemical Mechanical Polishing

2004 ◽  
Author(s):  
Gou-Jen Wang ◽  
Bor-Shin Lin ◽  
Kang J. Chang
Keyword(s):  
Neural Network ◽  
Process Control ◽  
Chemical Mechanical Polishing ◽  
Moving Average ◽  
Control Variable ◽  
Feedforward Neural Networks ◽  
Mechanical Polishing ◽  
Additional Control ◽  
Control Scheme ◽  
Time Varying Environment

Process Control is one of the key methods to improve manufacturing quality. This research proposes a neural network based run-to-run process control scheme that is adaptive to the time-varying environment. Two multilayer feedforward neural networks are implemented to conduct the process control and system identification duties. The controller neural network equips the control system with more capability in handling complicate nonlinear processes. With the system information provided by this neural network, batch polishing time (T) an additional control variable, can be implemented along with the commonly used down force (p) and relative speed between the plashing pad and the plashed wafer (v). Computer simulations and experiments on copper chemical mechanical polishing processes illustrate that in drafting suppression and environmental changing adaptation that the proposed neural network based run-to-run controller (NNRTRC) performs better than the double exponentially weighted moving average (d-EWMA) approach. It is also suggested that the proposed approach can be further implemented as both an end-point detector and a pad-conditioning sensor.

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