Development of external vibration control device with piezoelectric actuator for semiconductor manufacturing equipment

2019 ◽  
Vol 2019.16 (0) ◽  
pp. A303
Author(s):  
Jumpei SAKOJIRI ◽  
Yasutaka TAGAWA ◽  
Koji KAWATA
Keyword(s):  
Vibration Control ◽  
Piezoelectric Actuator ◽  
Semiconductor Manufacturing ◽  
Control Device ◽  
Manufacturing Equipment ◽  
External Vibration

Vibration Control of Serially Connected Isolation System Using Piezoelectric Actuator

2011 ◽  
Vol 250-253 ◽  
pp. 2112-2115
Author(s):  
Yan Hui Liu ◽  
Ping Tan ◽  
Fu Lin Zhou ◽  
Yong Feng Du ◽  
Wei Ming Yan
Keyword(s):  
Vibration Control ◽  
Piezoelectric Actuator ◽  
Performance Test ◽  
Control Experiment ◽  
Control Device ◽  
Shaking Table ◽  
Control Force ◽  
Isolation System ◽  
Control Efficiency ◽  
Fail Safe

This paper presents a bidirectional piezoelectric actuator, which can be used to vibration control of serially connected isolation System. Firstly, the performance test of this control device was processed. Then vibration control experiment of serially connected isolation system with this control device based on sweep sine shaking table was carried out. The experimental results show that this control device has stable mechanical properties, produces semi-active control force fast and has the outstanding control efficiency for serially connected isolation system. In addition, this control still has the satisfactory control efficiency when the piezoelectric actuator of this control is failed, which indicates the fail-safe function of this control.

Simultaneous Optimal Design of the Lyapunov-Based Semi-Active Control and the Semi-Active Vibration Control Device: Inverse Lyapunov Approach

2010 ◽  
Author(s):  
Kazuhiko Hiramoto ◽  
Taichi Matsuoka ◽  
Akira Fukukita ◽  
Katsuaki Sunakoda
Keyword(s):  
Optimal Design ◽  
Lyapunov Function ◽  
Vibration Control ◽  
Active Control ◽  
Control Device ◽  
Ball Screw ◽  
Design Parameters ◽  
Resistance Force ◽  
Control Law ◽  
Lyapunov Approach

We address a simultaneous optimal design problem of a semi-active control law and design parameters in a vibration control device for civil structures. The Vibration Control Device (VCD) that is being developed by authors is used as the semi-active control device in the present paper. The VCD is composed of a mechanism of a ball screw with a flywheel for the inertial resistance force and an electric motor with an electric circuit for the damping resistance force. A new bang-bang type semi-active control law referred to as Inverse Lyapunov Approach is proposed as the semi-active control law. In the Inverse Lyapunov Approach the Lyapunov function is searched so that performance measures in structural vibration control are optimized in the premise of the bang-bang type semi-active control based on the Lyapunov function. The design parameters to determine the Lyapunov function and the design parameters of the VCD are optimized for the good performance of the semi-active control system. The Genetic Algorithm is employed for the optimal design.

scholarly journals A monitoring method of semiconductor manufacturing processes using Internet of Things–based big data analysis

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771772181 ◽  
Author(s):  
Seok-Woo Jang ◽  
Gye-Young Kim
Keyword(s):  
Time Series ◽  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
Real Time ◽  
Semiconductor Manufacturing ◽  
Reference Model ◽  
Big Data Analysis ◽  
Monitoring Method ◽  
Manufacturing Equipment

This article proposes an intelligent monitoring system for semiconductor manufacturing equipment, which determines spec-in or spec-out for a wafer in process, using Internet of Things–based big data analysis. The proposed system consists of three phases: initialization, learning, and prediction in real time. The initialization sets the weights and the effective steps for all parameters of equipment to be monitored. The learning performs a clustering to assign similar patterns to the same class. The patterns consist of a multiple time-series produced by semiconductor manufacturing equipment and an after clean inspection measured by the corresponding tester. We modify the Line, Buzo, and Gray algorithm for classifying the time-series patterns. The modified Line, Buzo, and Gray algorithm outputs a reference model for every cluster. The prediction compares a time-series entered in real time with the reference model using statistical dynamic time warping to find the best matched pattern and then calculates a predicted after clean inspection by combining the measured after clean inspection, the dissimilarity, and the weights. Finally, it determines spec-in or spec-out for the wafer. We will present experimental results that show how the proposed system is applied on the data acquired from semiconductor etching equipment.

Diagnosability of Semiconductor Manufacturing Equipment

2006 ◽  
Vol 505-507 ◽  
pp. 1135-1140 ◽  
Author(s):  
Yuan Lin Wen ◽  
M.D. Jeng ◽  
Yi Sheng Huang
Keyword(s):  
Semiconductor Manufacturing ◽  
Manufacturing Equipment
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