Design and implementation of a digital twin application for a connected micro smart factory

2019 ◽  
Vol 32 (6) ◽  
pp. 596-614 ◽  
Author(s):  
Kyu Tae Park ◽  
Young Wook Nam ◽  
Hyeon Seung Lee ◽  
Sung Ju Im ◽  
Sang Do Noh ◽  
...  
Keyword(s):  
Smart Factory ◽  
Digital Twin ◽  
Design And Implementation

scholarly journals Design and Implementation of a Digital Twin Platform for AM processes

Procedia CIRP ◽  
2021 ◽  
Vol 104 ◽  
pp. 1722-1727
Author(s):  
Panagiotis Stavropoulos ◽  
Alexios Papacharalampoloulos ◽  
Konstantinos Tzimanis
Keyword(s):  
Digital Twin ◽  
Design And Implementation ◽  
Am Processes

scholarly journals A DTMEs-Based Digital Twin System Construction Method For Smart Factory

2021 ◽  
Author(s):  
Luyao Xia ◽  
Lu Jianfeng ◽  
Hao Zhang ◽  
Mengying Xu ◽  
Zhaojia Li ◽  
...  
Keyword(s):  
Hydraulic Cylinder ◽  
Intelligent Manufacturing ◽  
Construction Method ◽  
Smart Factory ◽  
Smart Manufacturing ◽  
Digital Twin ◽  
Twin System ◽  
Work In Process ◽  
Single Field ◽  
Short Time

Abstract Many enterprises have built their own digital twin factory model for physical factory planning, simulation optimization and real-time monitoring. However, the digital twin system, which has a single field, a short time cycle and unsinkable service, cannot fully reflect the interaction and integration of the physical and information world required by intelligent manufacturing. Therefore, the research on the construction method of the smart factory digital twin system with cross-domain and multi-model has an important influence on the application of smart manufacturing. In view of the above problems, this paper proposes the concept and composition of digital twin manufacturing ecosystem (DTMEs) based on the requirements and characteristics of product lifecycle, and analyzes the construction requirements of DTMEs for factory digital twin system, product digital twin system and supply chain digital twin system from the perspective of lifecycle. Finally, the smart factory digital twin system architecture is applied to the digital and intelligent upgrading of the hydraulic cylinder factory. The experimental results show that the intelligent improvement of the hydraulic factory, the reduction of Work-in-process inventory and the advance of delivery time, and prove the feasibility and effectiveness of the smart factory digital twin system.

scholarly journals A Study on Intelligent Manufacturing Industrial Internet for Injection Molding Industry Based on Digital Twin

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Zhiyong Wang ◽  
Wei Feng ◽  
Junlin Ye ◽  
Jinbiao Yang ◽  
Chun Liu
Keyword(s):  
Injection Molding ◽  
Production Management ◽  
Production Efficiency ◽  
Intelligent Manufacturing ◽  
Management Control ◽  
Smart Factory ◽  
Digital Twin ◽  
Intelligent Control System ◽  
Twin System ◽  
Industrial Internet

As one of the basic manufacturing industries in China, injection molding industry is faced with the problems of low degree of informatization and intelligence, resulting in low production efficiency and high costs. It is urgent to integrate deeply with new generation of information technology to achieve transformation and upgrade. In this paper, an integrative industrial Internet architecture of “integration of intelligent equipment, intelligent production lines, intelligent workshops, intelligent factories, and intelligent formats” was described. The injection molding intelligent control system, the production management, control platform based on the MES system, and other key technologies were researched. Also, the smart factory architecture based on digital twin was established, and the implementation method of the smart factory digital twin system was elaborated. The feasibility and effectiveness of the method had been verified through the industrial application, which provided the technical supports for the injection molding industrial Internet system. Finally, the intelligent manufacturing industrial Internet cloud platform for injection molding industry was prospected.

scholarly journals Digital Twin and Reinforcement Learning-Based Resilient Production Control for Micro Smart Factory

2021 ◽  
Vol 11 (7) ◽  
pp. 2977
Author(s):  
Kyu Tae Park ◽  
Yoo Ho Son ◽  
Sang Wook Ko ◽  
Sang Do Noh
Keyword(s):  
Reinforcement Learning ◽  
Production Control ◽  
Control Method ◽  
Production Systems ◽  
Smart Factory ◽  
Production Cycle ◽  
Policy Network ◽  
Digital Twin ◽  
Event Logs ◽  
Architectural Framework

To achieve efficient personalized production at an affordable cost, a modular manufacturing system (MMS) can be utilized. MMS enables restructuring of its configuration to accommodate product changes and is thus an efficient solution to reduce the costs involved in personalized production. A micro smart factory (MSF) is an MMS with heterogeneous production processes to enable personalized production. Similar to MMS, MSF also enables the restructuring of production configuration; additionally, it comprises cyber-physical production systems (CPPSs) that help achieve resilience. However, MSFs need to overcome performance hurdles with respect to production control. Therefore, this paper proposes a digital twin (DT) and reinforcement learning (RL)-based production control method. This method replaces the existing dispatching rule in the type and instance phases of the MSF. In this method, the RL policy network is learned and evaluated by coordination between DT and RL. The DT provides virtual event logs that include states, actions, and rewards to support learning. These virtual event logs are returned based on vertical integration with the MSF. As a result, the proposed method provides a resilient solution to the CPPS architectural framework and achieves appropriate actions to the dynamic situation of MSF. Additionally, applying DT with RL helps decide what-next/where-next in the production cycle. Moreover, the proposed concept can be extended to various manufacturing domains because the priority rule concept is frequently applied.

Design and Implementation of IoT and Non-IoT Modules for Smart Factory

2018 ◽  
Vol 19 (12) ◽  
pp. 2447-2452 ◽  
Author(s):  
Jae-Hyun Han ◽  
Jung-Ho Kim ◽  
Jong-Hwan Bae ◽  
Seon-Hui Bak
Keyword(s):  
Smart Factory ◽  
Design And Implementation
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