The Implementation of Smart Factory for Product Inspection and Validation A step by step guide to the implementation of the virtual plant of a smart factory using Digital Twin

Author(s):  
Okeme A. Peter ◽  
Skakun D. Anastasia ◽  
Alexander R. Muzalevskii
2021 ◽  
Author(s):  
Luyao Xia ◽  
Lu Jianfeng ◽  
Hao Zhang ◽  
Mengying Xu ◽  
Zhaojia Li ◽  
...  

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.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Zhiyong Wang ◽  
Wei Feng ◽  
Junlin Ye ◽  
Jinbiao Yang ◽  
Chun Liu

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.


2021 ◽  
Vol 11 (7) ◽  
pp. 2977
Author(s):  
Kyu Tae Park ◽  
Yoo Ho Son ◽  
Sang Wook Ko ◽  
Sang Do Noh

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.


2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Yan Bai ◽  
Jeong-Bong You ◽  
Il-Kyoo Lee

Aiming at the problems of irrational allocation of resources, low efficiency caused by unbalanced production line layout, and slow production line upgrade of the smart factory, this paper builds a real physical smart factory platform through the optimal control strategy and uses the GRAFCET algorithm to optimize the logistics scheduling during the actual system operation. The genetic algorithm is used to optimize the layout effect of the production line; the digital twin technology is used to provide predictive analysis technical support for the upgrading and reengineering of the production line. Through the analysis and comparison of the production capacity and equipment utilization of the physical smart factory and the virtual smart factory processing scheme, practice shows that the design of the digital twin system can effectively improve the effect and accuracy of the lean production method in the production process reorganization. Quantitative analysis of manufacturing industry provides powerful theoretical and technical support.


2018 ◽  
Vol 51 (11) ◽  
pp. 631-636 ◽  
Author(s):  
Antonio Padovano ◽  
Francesco Longo ◽  
Letizia Nicoletti ◽  
Giovanni Mirabelli

2019 ◽  
Vol 32 (6) ◽  
pp. 596-614 ◽  
Author(s):  
Kyu Tae Park ◽  
Young Wook Nam ◽  
Hyeon Seung Lee ◽  
Sung Ju Im ◽  
Sang Do Noh ◽  
...  

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