Production System Optimization of Gas Fields Using Hybrid Fuzzy-Genetic Approach

2006 ◽  
Author(s):  
Hui-june Park ◽  
Jong-Se Lim ◽  
Jeongyong Roh ◽  
Joo Myung Kang ◽  
Bae-hyun Min
Keyword(s):  
Production System ◽  
System Optimization ◽  
Genetic Approach ◽  
Gas Fields ◽  
Fuzzy Genetic

Production-System Optimization of Gas Fields Using Hybrid Fuzzy/Genetic Approach

SPE Journal ◽  
2010 ◽  
Vol 15 (02) ◽  
pp. 417-425 ◽  
Author(s):  
Hui-June Park ◽  
Jong-Se Lim ◽  
Jeongyong Roh ◽  
Joo M. Kang ◽  
Bae-Hyun Min
Keyword(s):  
Production System ◽  
System Optimization ◽  
Genetic Approach ◽  
Gas Fields ◽  
Fuzzy Genetic

scholarly journals Construction of Intelligent Integrated Model Framework for the Workshop Manufacturing System Via Digital Twin

2021 ◽  
Author(s):  
Zhongyu Zhang ◽  
Zhenjie Zhu ◽  
Jinsheng Zhang ◽  
Jingkun Wang
Keyword(s):  
Real Time ◽  
Production System ◽  
Manufacturing System ◽  
System Optimization ◽  
Production Cycle ◽  
Model Framework ◽  
The Real ◽  
Digital Twin ◽  
Twin Model ◽  
Information Layer

Abstract With the drastic development of the globally advanced manufacturing industry, transition of the original production pattern from traditional industries to advanced intelligence is completed with the least delay possible, which are still facing new challenges. Because the timeliness, stability and reliability of them is significantly restricted due to lack of the real-time communication. Therefore, an intelligent workshop manufacturing system model framework based on digital twin is proposed in this paper, driving the deep inform integration among the physical entity, data collection, and information decision-making. The conceptual and obscure of the traditional digital twin is refined, optimized, and upgraded on the basis of the four-dimension collaborative model thinking. A refined nine-layer intelligent digital twin model framework is established. Firstly, the physical evaluation is refined into entity layer, auxiliary layer and interface layer, scientifically managing the physical resources as well as the operation and maintenance of the instrument, and coordinating the overall system. Secondly, dividing the data evaluation into the data layer and the processing layer can greatly improve the flexible response-ability and ensure the synchronization of the real-time data. Finally, the system evaluation is subdivided into information layer, algorithm layer, scheduling layer, and functional layer, developing flexible manufacturing plan more reasonably, shortening production cycle, and reducing logistics cost. Simultaneously, combining SLP and artificial bee colony are applied to investigate the production system optimization of the textile workshop. The results indicate that the production efficiency of the optimized production system is increased by 34.46%.

Sensitivity analysis of fuzzy-genetic approach applied to cabled-truss design

2014 ◽  
Vol 26 (4) ◽  
pp. 1931-1942 ◽  
Author(s):  
Vitor C. Finotto ◽  
Wilson R.L. da Silva ◽  
Petr Štemberk ◽  
Michael Valášek
Keyword(s):  
Sensitivity Analysis ◽  
Genetic Approach ◽  
Truss Design ◽  
Fuzzy Genetic
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