Real-Time Configuration Techniques for PnP Process Monitoring

2016 ◽  
pp. 57-83
Author(s):  
Hao Luo
Keyword(s):  
Real Time ◽  
Process Monitoring

Real time process monitoring using diffraction-based overlay measurements from YieldStar

2020 ◽  
Author(s):  
Henry Chen ◽  
Jimmy Chang ◽  
Sheng-Tsung Tsao ◽  
Junjun Zhang ◽  
Jie Du ◽  
...  
Keyword(s):  
Real Time ◽  
Process Monitoring ◽  
Time Process

Synthesis of Tailored Segmented Polyurethanes Utilizing Continuous-Flow Reactors and Real-Time Process Monitoring

2021 ◽  
Author(s):  
Xabier Lopez de Pariza ◽  
Tim Erdmann ◽  
Pedro L. Arrechea ◽  
Leron Perez ◽  
Charles Dausse ◽  
...  
Keyword(s):  
Real Time ◽  
Process Monitoring ◽  
Continuous Flow ◽  
Time Process ◽  
Flow Reactors ◽  
Segmented Polyurethanes ◽  
Continuous Flow Reactors

A New Real-Time Process Monitor Method Based on MRC

2014 ◽  
Vol 971-973 ◽  
pp. 1481-1484
Author(s):  
Ke He Wu ◽  
Long Chen ◽  
Yi Li
Keyword(s):  
Information System ◽  
Real Time ◽  
Process Monitoring ◽  
Time Process ◽  
Monitoring Methods ◽  
Traditional Process ◽  
Kernel Level ◽  
Process Monitor

In order to ensure safe and stable running of applications, this paper analyses the limitation of traditional process-monitoring methods, and then designs a new real-time process monitor method based on Mandatory Running Control (MRC) technology. This method not only can monitor the processes, but also can control them from system kernel level to improve the reliability and safety of applications, so as to ensure the security and stability of information system.

scholarly journals Real-Time Process Monitoring Based on Multivariate Control Chart for Anomalies Driven by Frequency Signal via Sound and Electrocardiography Cases

Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1510
Author(s):  
Chih-Hung Jen ◽  
Chien-Chih Wang
Keyword(s):  
Real Time ◽  
Process Monitoring ◽  
Sound Frequency ◽  
Detection Accuracy ◽  
Control Line ◽  
Time Process ◽  
Intrinsic Mode Functions ◽  
Low Frequencies ◽  
Linear Discriminant

Recent developments in network technologies have led to the application of cloud computing and big data analysis to industrial automation. However, the automation of process monitoring still has numerous issues that need to be addressed. Traditionally, offline statistical processes are generally used for process monitoring; thus, problems are often detected too late. This study focused on the construction of an automated process monitoring system based on sound and vibration frequency signals. First, empirical mode decomposition was combined with intrinsic mode functions to construct different sound frequency combinations and differentiate sound frequencies according to anomalies. Then, linear discriminant analysis (LDA) was adopted to classify abnormal and normal sound frequency signals, and a control line was constructed to monitor the sound frequency. In a case study, the proposed method was applied to detect abnormal sounds at high and low frequencies, and a detection accuracy of over 90% was realized. In another case study, the proposed method was applied to analyze electrocardiography signals and was similarly able to identify abnormal situations. Thus, the proposed method can be applied to real-time process monitoring and the detection of abnormalities with high accuracy in various situations.

Real Time Process Monitoring with an Integrated Fibre Monitor

1994 ◽  
pp. 395-398
Author(s):  
Chris Peters ◽  
Julian D. C. Jones ◽  
Daoning Su
Keyword(s):  
Real Time ◽  
Process Monitoring ◽  
Time Process
Sign in / Sign up

Export Citation Format

Share Document