scholarly journals Process Modelling of Geothermal Drilling System Using Digital Twin for Real-Time Monitoring and Control

Designs ◽  
2019 ◽  
Vol 3 (3) ◽  
pp. 45 ◽  
Author(s):  
Nahashon O. Osinde ◽  
Jean B. Byiringiro ◽  
Michael M. Gichane ◽  
Hasan Smajic
Keyword(s):  
Real Time ◽  
Energy Demand ◽  
Assembly System ◽  
Monitoring And Control ◽  
Real Time Monitoring ◽  
Drilling Tool ◽  
Digital Twin ◽  
Twin Model ◽  
Study Results ◽  
Geothermal Drilling

Currently, Kenya supplies its energy demand predominantly through hydroelectric power, which fluctuates due to poor and unpredictable rainfall in particular years. Geothermal energy is proposed as a clean and reliable energy source in meeting Kenya’s increasing energy demand. During geothermal drilling operations, disruptions due to tool wear and breakages increases the cost of operation significantly. Some of these causes can be mitigated by real-time monitoring of the tool head during operations. This paper presents the design and implementation of a digital twin model of a drilling tool head, represented as a section of a mechatronic assembly system. The system was modelled in Siemens NX and programmed via the TIA portal using S7 1200 PLC. The digital model was programmed to exactly match the operations of the physical system using OPC (open platform communications) standards. These operations were verified through the motion study by simultaneous running of the assembly system and digital twin model. The study results substantiate that a digital twin model of a geothermal drilling operation can closely mimic the physical operation.

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%.

Sign in / Sign up

Export Citation Format

Share Document