Design and Optimization of Smart Factory Control System Based on Digital Twin System Model

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.

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Implementation of Digital Twin for Engine Block Manufacturing Processes

Applied Sciences ◽

10.3390/app10186578 ◽

2020 ◽

Vol 10 (18) ◽

pp. 6578

Author(s):

Roman Bambura ◽

Marek Šolc ◽

Miroslav Dado ◽

Luboš Kotek

Keyword(s):

Real Time ◽

Production Line ◽

Manufacturing Industry ◽

Real Life ◽

Engine Block ◽

Manufacturing Processes ◽

Production Plant ◽

Implementation Framework ◽

Digital Twin ◽

Programmable Logic Control

The digital twin (DT) is undergoing an increase in interest from both an academic and industrial perspective. Although many authors proposed and described various frameworks for DT implementation in the manufacturing industry context, there is an absence of real-life implementation studies reported in the available literature. The main aim of this paper is to demonstrate feasibility of the DT implementation under real conditions of a production plant that is specializing in manufacturing of the aluminum components for the automotive industry. The implementation framework of the DT for engine block manufacturing processes consists of three layers: physical layer, virtual layer and information-processing layer. A simulation model was created using the Tecnomatix Plant Simulation (TPS) software. In order to obtain real-time status data of the production line, programmable logic control (PLC) sensors were used for raw data acquisition. To increase production line productivity, the algorithm for bottlenecks detection was developed and implemented into the DT. Despite the fact that the implementation process is still under development and only partial results are presented in this paper, the DT seems to be a prospective real-time optimization tool for the industrial partner.

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

10.21203/rs.3.rs-633211/v1 ◽

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.

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

Complexity ◽

10.1155/2021/8838914 ◽

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.

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Augmented reality and digital twin system for interaction with construction machinery

Journal of Asian Architecture and Building Engineering ◽

10.1080/13467581.2020.1869557 ◽

2021 ◽

pp. 1-12

Author(s):

Syed Mobeen Hasan ◽

Kyuhyup Lee ◽

Daeyoon Moon ◽

Soonwook Kwon ◽

Song Jinwoo ◽

...

Keyword(s):

Augmented Reality ◽

Construction Machinery ◽

Digital Twin ◽

Twin System

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Industrie 4.0 in der Textilindustrie*/Industry 4.0 - Integrated Industry in the textile industry: Smart factory approaches with a special focus on textile products and processes

wt Werkstattstechnik online ◽

10.37544/1436-4980-2015-04-37 ◽

2015 ◽

Vol 105 (04) ◽

pp. 195-199

Author(s):

R. Riedel ◽

N. Göhlert ◽

E. Müller

Keyword(s):

Textile Industry ◽

Industry 4.0 ◽

Manufacturing Industry ◽

Industrie 4.0 ◽

Smart Factory ◽

Special Focus ◽

Considerable Potential ◽

Textile Products

Industrie 4.0 bietet für die produzierende Industrie in Deutschland erhebliche Potentiale zur Steigerung der Wettbewerbsfähigkeit. Die Anwendung und volle Ausnutzung der Möglichkeiten entsprechender Technologien sind jedoch an bestimmte Voraussetzungen gebunden. Der Fachbeitrag reflektiert vor diesem Hintergrund die Umsetzungspotentiale von Industrie 4.0 in der Textilindustrie.   Industry 4.0, also called Integrated Industry, provides considerable potential for the manufacturing industry in Germany to increase its competitiveness. However, the application and the full exploitation of the potential of those technologies depend on certain conditions. Against this background, the article reflects on the implementation potential of Industrie 4.0 in the textile industry.

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Measurement Framework of Smart Factory Technology Capability in Small-Medium Manufacturing Industry

Journal of the Korea Management Engineers Society ◽

10.35373/kmes.25.3.8 ◽

2020 ◽

Vol 25 (3) ◽

pp. 121-134

Author(s):

Chui-Young Yoon

Keyword(s):

Manufacturing Industry ◽

Smart Factory ◽

Measurement Framework ◽

Technology Capability

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Productivity Analysis Of Filling Machine With The Objective Matrix (OMAX) Method

ABDIMAS TALENTA: Jurnal Pengabdian Kepada Masyarakat ◽

10.32734/abdimastalenta.v6i1.5444 ◽

2021 ◽

Vol 6 (1) ◽

pp. 32-39

Author(s):

Katrin Sinaga ◽

Kevin Lie ◽

Nico Williams ◽

Theresia Sunarni

Keyword(s):

Production Line ◽

Manufacturing Industry ◽

Working Hours ◽

Productivity Analysis ◽

Productivity Measurement ◽

Productivity Level ◽

Increase In Productivity ◽

Productivity Ratio

A Factory is a manufacturing industry that produces tea drinks in cups. A Factory is also inseparable from problems related to machine/equipment productivity. Based on the results of observations made at A Factory part of the production line that there is often a sudden stop of the production process. The discontinuation will affect the quality of the product expected and the production targets to be achieved. The problem was discussed in this research is how much the productivity level of the filling production department is, how much the production effectiveness, effective working hours, the number of defective products, and machine downtime criteria. The productivity measurement method used is the Objective Matrix (OMAX) method, so the steps of this study refer to OMAX steps, which is the criteria determination/productivity ratio of the production line, the calculation of the productivity ratio value, the calculation of the initial standard score (score 3), The determination of the goal (score 10) and the lowest score (score 0), the determination of weight, the calculation of value/criteria value, the determination of productivity value for each period, determination of index percentage. With the OMAX method, it can be seen that in period 11 (compared to period 10) there was an increase in productivity, this can be seen because the IP value (Index of Performance) which is positive (+) is 27.79 and there is an increase in the value of the calculation at the time of measurement (current) from 383.36 to 300. This increase was due to an increase in the value of all criteria.

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3D Digital Twin of Intelligent Transportation System based on Road-Side Sensing

Journal of Physics Conference Series ◽

10.1088/1742-6596/2083/3/032022 ◽

2021 ◽

Vol 2083 (3) ◽

pp. 032022

Author(s):

Yunpeng Guo ◽

Kai Zou ◽

Shengdong Chen ◽

Feng Yuan ◽

Fang Yu

Keyword(s):

Virtual World ◽

Intelligent Transportation System ◽

Road Traffic ◽

Intelligent Transportation ◽

Physical World ◽

Transportation System ◽

Traffic Information ◽

Digital Twin ◽

Twin System ◽

Infrastructure System

Abstract Cooperative vehicle-infrastructure is one of the most import developing direction of future intelligent transportation system, while digital twin system can record, reproduce, and even deduce the physical system, which could be helpful for the development of cooperative vehicle-infrastructure. In this study, we proposed a 3D digital twin platform of intelligent transportation system based on road-side sensing, a core component of cooperative vehicle-infrastructure system. This platform consists of real road-side sensing unit,3D virtual environment, and the ROS bridge between them, by receiving the sensing results of physical world in real-time, the virtual world can reproduce the compatible road traffic information, such as the type,3D position and orientation of traffic participants.

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