scholarly journals The Digital Twin: Realizing the Cyber-Physical Production System for Industry 4.0

Procedia CIRP ◽  
2017 ◽  
Vol 61 ◽  
pp. 335-340 ◽  
Author(s):  
Thomas H.-J. Uhlemann ◽  
Christian Lehmann ◽  
Rolf Steinhilper
Keyword(s):  
Production System ◽  
Industry 4.0 ◽  
Digital Twin

scholarly journals Smart cyber-physical production system enabled workpiece production in digital twin job shop

2021 ◽  
Vol 13 (9) ◽  
pp. 168781402110408
Author(s):  
Wang Chuang ◽  
Zhou Guanghui ◽  
Wu Junsheng
Keyword(s):  
Production System ◽  
Industry 4.0 ◽  
Job Shop ◽  
Interaction Model ◽  
Machining Processes ◽  
Digital Twin ◽  
Future Production ◽  
Manufacturing Resources ◽  
Level Production ◽  
Process Level

Industry 4.0 describes the future production of workpiece in job shop as: the workpiece is a smart one; it knows the details of how to manufacture itself; and it can communicate with manufacturing environment to support its own machining processes. This means that the production of workpiece places more emphasis on the smart realization of the process level in Industry 4.0. However, how to implement the production scenario based on existing technologies has not yet been well studied. On account of this, this article aims to study how to use existing technologies in job shop such as digital twins, Internet of Things (IoT), Cyber-physical Production System (CPPS), etc., to realize the workpiece-driven process-level production. The process-level production of a workpiece is divided into three stages according to the different manufacturing resources involved. On this basis, the production of the workpiece in digital twin job shop is divided into process level, operation level, and IoT/sensor level. Firstly, the manufacturing requirements at process level are generated according to production planning and process sheet. And these requirements are written into RFID tag of the workpiece. The workpiece dynamically interacts with different workstations via RFID reader/antenna in order to complete the manufacturing requirements. Secondly, based on the tag data, the interaction model of operation level, and IoT/sensor level CPPSs is given. Thirdly, at IoT/sensor level, the RFID devices are treated as a CPPS to track the manufacturing resources. And different smart sensors are used as independent sensor CPPSs to monitor the running status of machine tool. The RFID and sensor CPPSs are triggered by operation level CPPSs. Finally, a digital twin job shop is taken as an example to illustrate the feasibility of the proposed models and methods.

scholarly journals Digital Twin for Designing and Reconfiguring Human–Robot Collaborative Assembly Lines

2021 ◽  
Vol 11 (10) ◽  
pp. 4620
Author(s):  
Niki Kousi ◽  
Christos Gkournelos ◽  
Sotiris Aivaliotis ◽  
Konstantinos Lotsaris ◽  
Angelos Christos Bavelos ◽  
...  
Keyword(s):  
Production System ◽  
Assembly Lines ◽  
Flexible Assembly ◽  
Digital Twin ◽  
Collaborative Assembly ◽  
Geometrical Information ◽  
Line Level ◽  
Dual Arm ◽  
Different Levels

This paper discusses a digital twin-based approach for designing and redesigning flexible assembly systems. The digital twin allows modeling the parameters of the production system at different levels including assembly process, production station, and line level. The approach allows dynamically updating the digital twin in runtime, synthesizing data from multiple 2D–3D sensors in order to have up-to-date information about the actual production process. The model integrates both geometrical information and semantics. The model is used in combination with an artificial intelligence logic in order to derive alternative configurations of the production system. The overall approach is discussed with the help of a case study coming from the automotive industry. The case study introduces a production system integrating humans and autonomous mobile dual arm workers.

scholarly journals Using Digital Twin Technology in Engineering Education – Course Concept to Explore Benefits and Barriers

2020 ◽  
Vol 10 (1) ◽  
pp. 377-385 ◽  
Author(s):  
Antti Liljaniemi ◽  
Heikki Paavilainen
Keyword(s):  
Engineering Education ◽  
Industry 4.0 ◽  
Digital Technologies ◽  
Digital Twin ◽  
New Knowledge

AbstractDigital Twin (DT) technology is an essential technology related to the Industry 4.0. In engineering education, it is important that the curricula are kept up-to-date. By adopting new digital technologies, such as DT, we can provide new knowledge for students, teachers, and companies. The main aim of this research was to create a course concept to research benefits and barriers of DT technology in engineering education. The research confirmed earlier findings concerning digitalization in engineering education. DT technology can increase motivation for studying and improve learning when applied correctly.

scholarly journals Robot Digital Twin towards Industry 4.0

2020 ◽  
Vol 53 (2) ◽  
pp. 10867-10872
Author(s):  
Luige Vlădăreanu ◽  
Alexandru I. Gal ◽  
Octavian D. Melinte ◽  
Victor Vlădăreanu ◽  
Mihaiela Iliescu ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Digital Twin

Digital Twins: Review and Challenges

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Maria G. Juarez ◽  
Vicente J. Botti ◽  
Adriana S. Giret
Keyword(s):  
Computer Science ◽  
Industry 4.0 ◽  
Multi Agent System ◽  
Agent System ◽  
Digital Twin ◽  
Digital Twins ◽  
Science Approach ◽  
Multi Agent ◽  
Current Operating

Abstract With the arises of Industry 4.0, numerous concepts have emerged; one of the main concepts is the digital twin (DT). DT is being widely used nowadays, however, as there are several uses in the existing literature; the understanding of the concept and its functioning can be diffuse. The main goal of this paper is to provide a review of the existing literature to clarify the concept, operation, and main characteristics of DT, to introduce the most current operating, communication, and usage trends related to this technology, and to present the performance of the synergy between DT and multi-agent system (MAS) technologies through a computer science approach.

scholarly journals Model Quality Assessment Method Based on Support Vector Machine

2021 ◽  
Vol 25 (1) ◽  
pp. 35-39
Author(s):  
Łukasz Glodek ◽  
Szymon Bysko ◽  
Witold Nocoń
Keyword(s):  
Support Vector Machine ◽  
Quality Assessment ◽  
Industry 4.0 ◽  
Assessment Method ◽  
Support Vector ◽  
Model Quality ◽  
Digital Twin ◽  
Model Quality Assessment ◽  
Virtual Commissioning ◽  
Quality Assessment Method

This paper proposes a model quality assessment method based on Support Vector Machine, which can be used to develop a digital twin. This work is strongly connected with Industry 4.0, in which the main idea is to integrate machines, devices, systems, and IT. One of the goals of Industry 4.0 is to introduce flexible assortment changes. Virtual commissioning can be used to create a simulation model of a plant or conduct training for maintenance engineers. On a branch of virtual commissioning is a digital twin. The digital twin is a virtual representation of a plant or a device. Thanks to the digital twin, different scenarios can be analyzed to make the testing process less complicated and less time-consuming. The goal of this work is to propose a coefficient that will take into account expert knowledge and methods used for model quality assessment (such as Normalized Root Mean Square Error – NRMSE, Maximum Error – ME). NRMSE and ME methods are commonly used for this purpose, but they have not been used simultaneously so far. Each of them takes into consideration another aspect of a model. The coefficient allows deciding whether the model can be used for digital twin appliances. Such an attitude introduces the ability to test models automatically or in a semi-automatic way.

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%.

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