Design of an on-line decision support system for process control

1988 ◽  
Author(s):  
Begonia Bi-Hsia Tai ◽  
Leonard H. Weiner
Keyword(s):  
Decision Support ◽  
Process Control ◽  
Decision Support System ◽  
Support System ◽  
On Line

Critiquing Team Procedure Execution

2000 ◽  
Vol 44 (22) ◽  
pp. 515-518 ◽  
Author(s):  
Stephanie Guerlain ◽  
Peter Bullemer
Keyword(s):  
Decision Support ◽  
Problem Solving ◽  
Process Control ◽  
Decision Support System ◽  
Real Time ◽  
Computer System ◽  
Support System ◽  
Single Person ◽  
On Line ◽  
Time Critical

Critiquing is a form of decision support whereby a computer system monitors the actions of people to help prevent errors. Critiquing systems developed to date (spell checkers, problem-solving assistants, etc.) traditionally support a single person performing a static, non time-critical task. We have now developed a critiquing system in the more dynamic world of process control. Specifically, we support the execution of complex procedures in petrochemical plants with an on-line, executable dynamic procedures decision support system, where we introduce critiquing as a means to assist teams of operators as they execute procedures in real time.

Prediction of flood abnormalities for improved public safety using a modified adaptive neuro-fuzzy inference system

2006 ◽  
Vol 54 (11-12) ◽  
pp. 11-19 ◽  
Author(s):  
M. Aqil ◽  
I. Kita ◽  
A. Yano ◽  
S. Nishiyama
Keyword(s):  
Decision Support ◽  
Process Control ◽  
Decision Support System ◽  
Real Time ◽  
Support System ◽  
Fuzzy System ◽  
Public Safety ◽  
Fuzzy Model ◽  
Neuro Fuzzy ◽  
Flood Monitoring

It is widely accepted that an efficient flood alarm system may significantly improve public safety and mitigate economical damages caused by inundations. In this paper, a modified adaptive neuro-fuzzy system is proposed to modify the traditional neuro-fuzzy model. This new method employs a rule-correction based algorithm to replace the error back propagation algorithm that is employed by the traditional neuro-fuzzy method in backward pass calculation. The final value obtained during the backward pass calculation using the rule-correction algorithm is then considered as a mapping function of the learning mechanism of the modified neuro-fuzzy system. Effectiveness of the proposed identification technique is demonstrated through a simulation study on the flood series of the Citarum River in Indonesia. The first four-year data (1987 to 1990) was used for model training/calibration, while the other remaining data (1991 to 2002) was used for testing the model. The number of antecedent flows that should be included in the input variables was determined by two statistical methods, i.e. autocorrelation and partial autocorrelation between the variables. Performance accuracy of the model was evaluated in terms of two statistical indices, i.e. mean average percentage error and root mean square error. The algorithm was developed in a decision support system environment in order to enable users to process the data. The decision support system is found to be useful due to its interactive nature, flexibility in approach, and evolving graphical features, and can be adopted for any similar situation to predict the streamflow. The main data processing includes gauging station selection, input generation, lead-time selection/generation, and length of prediction. This program enables users to process the flood data, to train/test the model using various input options, and to visualize results. The program code consists of a set of files, which can be modified as well to match other purposes. This program may also serve as a tool for real-time flood monitoring and process control. The results indicate that the modified neuro-fuzzy model applied to the flood prediction seems to have reached encouraging results for the river basin under examination. The comparison of the modified neuro-fuzzy predictions with the observed data was satisfactory, where the error resulted from the testing period was varied between 2.632% and 5.560%. Thus, this program may also serve as a tool for real-time flood monitoring and process control.

The Design and Implementation of Condition Monitoring and Decision Support System in HVDC Converter Station

2015 ◽  
Vol 734 ◽  
pp. 707-713
Author(s):  
Wei Wei Jin ◽  
Cun Yu ◽  
Xing Chao Yang ◽  
Zhan Xia Geng ◽  
Hao Ran Zhang ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Condition Monitoring ◽  
Support System ◽  
Engineering Application ◽  
Monitoring Method ◽  
Design And Implementation ◽  
On Line ◽  
Grid Construction ◽  
Condition Monitoring System

The shortcomings of current on-line condition monitoring system include: the research was concentrated in AC substation; the function was single and completely independent; the protocols were not compatible and the interface was not unified. To improve these disadvantages and better satisfy the needs of the condition monitoring in converter station, the design and implementation of condition monitoring and decision support system in HVDC converter station was realized. By studying of condition monitoring method, decision support technology and engineering application of HVDC project, the system design principle was discussed, the software structure was shown and the function realization was given in detail. The implementation realized real time monitoring for running equipments, provided reliable gist for maintenance and reduced the costs of resources. The implementation is applied to HVDC project witch has a great significance in improving the operation efficiency and promoting the smart grid construction.

scholarly journals Decision support system in the task of ensuring information security of automated process control systems

2019 ◽  
pp. 477-486
Author(s):  
A D Kirillova ◽  
V I Vasilyev ◽  
A V Nikonov ◽  
V V Berkholts
Keyword(s):  
Control System ◽  
Decision Support ◽  
Information Security ◽  
Process Control ◽  
Decision Support System ◽  
Control Systems ◽  
Support System ◽  
Decision Rules ◽  
Process Control Systems ◽  
Automated Process

The problem of ensuring the information security of an automated process control system (APCS) is considered. An overview of the main regulatory documents on ensuring the safety of automated process control systems is given. For the operative solution of the tasks of ensuring information security of the automated control system of technological processes it is proposed to use an intelligent decision support system (DSS). An example of the construction and implementation of decision rules in the composition of the DSS based on the use of neurofuzzy models is considered.

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