In-situ CMP copper endpoint control system

Author(s):  
R. Allen ◽  
C. Chen ◽  
T. Trikas ◽  
K. Lehman ◽  
R. Shinagawa ◽  
...  
2000 ◽  
Vol 278 (3) ◽  
pp. H998-H1007 ◽  
Author(s):  
Hiroshi Miyashita ◽  
Masaru Sugimachi ◽  
Takayuki Sato ◽  
Toru Kawada ◽  
Toshiaki Shishido ◽  
...  

To clarify the pathophysiological role of dynamic arterial properties in cardiovascular diseases, we attempted to develop a new control system that imposes desired aortic impedance on in situ rat left ventricle. In 38 anesthetized open-chest rats, ascending aortic pressure and flow waveforms were continuously sampled (1,000 Hz). Desired flow waveforms were calculated from measured aortic pressure waveforms and target impedance. To minimize the difference between measured and desired aortic flow waveforms, the computer generated commands to the servo-pump, connected to a side branch of the aorta. By iterating the process, we could successfully control aortic impedance in such a way as to manipulate compliance and characteristic impedance between 60 and 160% of their respective native values. The error between desired and measured aortic flow waveforms was 70 ± 34 μl/s (root mean square; 4.4 ± 1.4% of peak flow), indicating reasonable accuracy in controlling aortic impedance. This system enables us to examine the importance of dynamic arterial properties independently of other hemodynamic and neurohumoral factors in physiological and clinical settings.


Author(s):  
Yanhua Zhao ◽  
Jianyi Kong ◽  
Jintang Yang ◽  
Zhaohui Xia ◽  
Gongfa Li

Author(s):  
ZHIYING HU ◽  
CHRISTINE W. CHAN ◽  
GORDON H. HUANG

This study describes the development of a dynamic knowledge-based reasoning-enhanced model predictive control system (KBRECS) for in-situ bioremediation processes. The automated control system balances the complex physical, chemical, and biological processes involved in the remediation process while minimizing overall cost of the entire remediation process. The control system includes an optimization subsystem and a monitoring subsystem. The optimization subsystem consists of a simulation model supported by an optimization function which is designed to generate a series of optimal control actions. The monitoring subsystem is a knowledge-based system which is designed to monitor and adjust the online control actions. The numerical simulation model describes the fate and transport of the subsurface contaminants. The optimization function is a constrained, nonlinear function that has been implemented using a genetic algorithm (GA). Intermediate genetic algorithm individuals are indexed and stored in the knowledge base, thereby reducing search times for values to replace the unqualified schemes used by the monitoring subsystem. The system was applied to a lab experiment and compared with the control system presented in [9]. The results indicated that the knowledge based reasoning system enhanced the control system by generating an appropriate control strategy and adjusting control actions promptly. This helps to enhance efficiency in control of the in-situ bioremediation process at petroleum-contaminated groundwater systems.


2017 ◽  
Vol 7 (1) ◽  
pp. 100-105 ◽  
Author(s):  
Iaroslav Kovalenko ◽  
Sylvain Verron ◽  
Maryna Garan ◽  
Jiří Šafka ◽  
Michal Moučka

AbstractThis article describes a method of in-situ process monitoring in the digital light processing (DLP) 3D printer. It is based on the continuous measurement of the adhesion force between printing surface and bottom of a liquid resin bath. This method is suitable only for the bottom-up DPL printers. Control system compares the force at the moment of unsticking of printed layer from the bottom of the tank, when it has the largest value in printing cycle, with theoretical value. Implementation of suggested algorithm can make detection of faults during the printing process possible.


2012 ◽  
Vol 605-607 ◽  
pp. 1537-1540 ◽  
Author(s):  
Xiao Yu Wang

The application of PLC 、Stepper motor driver and Encoder are introduced in stepper motor closed-loop control system. The Principle diagram is analyzed, the Control System flow chart and Software program are designed. Through in-situ operation, the system has been proved well reliability、 stability and simplicity , achieved high accuracy and low cost requirements。


2008 ◽  
Vol 151 (3) ◽  
pp. 460-469 ◽  
Author(s):  
Y.F. Huang ◽  
G.Q. Wang ◽  
G.H. Huang ◽  
H.N. Xiao ◽  
A. Chakma

Sign in / Sign up

Export Citation Format

Share Document