scholarly journals Automated Container Terminal Production Operation and Optimization via an AdaBoost-Based Digital Twin Framework

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Yu Li ◽  
Daofang Chang ◽  
Yinping Gao ◽  
Ying Zou ◽  
Chunteng Bao
Keyword(s):  
Real Time ◽  
Production Control ◽  
Container Terminal ◽  
Virtual Space ◽  
Experimental Results ◽  
Small Scale ◽  
Production Operation ◽  
Adaboost Algorithm ◽  
Digital Twin ◽  
Loading And Unloading

Digital twin (DT), machine learning, and industrial Internet of things (IIoT) provide great potential for the transformation of the container terminal from automation to intelligence. The production control in the loading and unloading process of automated container terminals (ACTs) involves complex situations, which puts forward high requirements for efficiency and safety. To realize the real-time optimization and security of the ACT, a framework integrating DT with the AdaBoost algorithm is proposed in this study. The framework is mainly composed of physical space, a data service platform, and virtual space, in which the twin space and service system constitute virtual space. In the proposed framework, a multidimensional and multiscale DT model in twin space is first built through a 3D MAX and U3D technology. Second, we introduce a random forest and XGBoost to compare with AdaBoost to select the best algorithm to train and optimize the DT mechanism model. Third, the experimental results show that the AdaBoost algorithm is better than others by comparing the performance indexes of model accuracy, root mean square error, interpretable variance, and fitting error. In addition, we implement empirical experiments by different scales to further evaluate the proposed framework. The experimental results show that the mode of the DT-based terminal operation has higher loading and unloading efficiency than that of the conventional terminal operation, increasing by 23.34% and 31.46% in small-scale and large-scale problems, respectively. Moreover, the visualization service provided by the DT system can monitor the status of automation equipment in real time to ensure the safety of operation.

A Digital Twin Concept for Manufacturing Systems

2018 ◽  
Author(s):  
Wesley Ellgass ◽  
Nathan Holt ◽  
Hector Saldana-Lemus ◽  
Julian Richmond ◽  
Ali Vatankhah Barenji ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Real Time ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Virtual Space ◽  
Smart Manufacturing ◽  
Shop Floor ◽  
Digital Twin ◽  
Physical Resources ◽  
Virtual Resources

With the developments and applications of the advanced information technologies such as cloud computing, internet of thing, artificial intelligence and virtual reality, industry 4.0 and smart manufacturing era are coming. In this respect, one of the specific challenges is to achieve a connection of physical resources on the shop floor with virtual resources, for real-time response, real time process optimization, and simulation, which is merged by big data problem. In this respect, Digital Twins (DT) concept is introduced as a key technology, which includes physical resources, virtual resources, service system, and digital twin data. DT considers current condition of physical resource and prediction of future events to make a responsive decision. However, due to the complexity of building a digital equivalent in virtual space to its physical counterpart, very little applications have been developed with this purpose, especially in the industrial manufacturing area. Therefore, the types of data and technology required to build the DT for a manufacturing system are presented in this work, trying to develop a framework of DT based manufacturing system, which is supported by the virtual reality for virtualization of physical resources.

scholarly journals Digital Twin for Operation of Microgrid: Optimal Scheduling in Virtual Space of Digital Twin

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5504
Author(s):  
Hyang-A Park ◽  
Gilsung Byeon ◽  
Wanbin Son ◽  
Hyung-Chul Jo ◽  
Jongyul Kim ◽  
...  
Keyword(s):  
Real Time ◽  
Industrial Revolution ◽  
Storage System ◽  
Research Field ◽  
Optimization Techniques ◽  
Virtual Space ◽  
Machine Learning Techniques ◽  
Time Data ◽  
Digital Twin ◽  
Learning Techniques

Due to the recent development of information and communication technology (ICT), various studies using real-time data are now being conducted. The microgrid research field is also evolving to enable intelligent operation of energy management through digitalization. Problems occur when operating the actual microgrid, causing issues such as difficulty in decision making and system abnormalities. Using digital twin technology, which is one of the technologies representing the fourth industrial revolution, it is possible to overcome these problems by changing the microgrid configuration and operating algorithms of virtual space in various ways and testing them in real time. In this study, we proposed an energy storage system (ESS) operation scheduling model to be applied to virtual space when constructing a microgrid using digital twin technology. An ESS optimal charging/discharging scheduling was established to minimize electricity bills and was implemented using supervised learning techniques such as the decision tree, NARX, and MARS models instead of existing optimization techniques. NARX and decision trees are machine learning techniques. MARS is a nonparametric regression model, and its application has been increasing. Its performance was analyzed by deriving performance evaluation indicators for each model. Using the proposed model, it was found in a case study that the amount of electricity bill savings when operating the ESS is greater than that incurred in the actual ESS operation. The suitability of the model was evaluated by a comparative analysis with the optimization-based ESS charging/discharging scheduling pattern.

Towards a shape-performance integrated digital twin for lumbar spine analysis

Digital Twin ◽  
2021 ◽  
Vol 1 ◽  
pp. 8
Author(s):  
Xiwang He ◽  
Yiming Qiu ◽  
Xiaonan Lai ◽  
Zhonghai Li ◽  
Liming Shu ◽  
...  
Keyword(s):  
Lumbar Spine ◽  
Real Time ◽  
Body Movement ◽  
Physical Space ◽  
Gaussian Process Regression ◽  
Human Movement ◽  
The Body ◽  
Virtual Space ◽  
The Real ◽  
Digital Twin

Background: With significant advancement and demand for digital transformation, the digital twin has been gaining increasing attention as it is capable of establishing real-time mapping between physical space and virtual space. In this work, a shape-performance integrated digital twin solution is presented to predict the real-time biomechanics of the lumbar spine during human movement. Methods: A finite element model (FEM) of the lumbar spine was firstly developed using computed tomography (CT) and constrained by the body movement which was calculated by the inverse kinematics algorithm. The Gaussian process regression was utilized to train the predicted results and create the digital twin of the lumbar spine in real-time. Finally, a three-dimensional virtual reality system was developed using Unity3D to display and record the real-time biomechanics performance of the lumbar spine during body movement. Results: The evaluation results presented an agreement (R-squared > 0.8) between the real-time prediction from digital twin and offline FEM prediction. Conclusions: This approach provides an effective method of real-time planning and warning in spine rehabilitation.

Research on Assembly Process Simulation of Construction Machinery Arm Based on Digital Twin

2021 ◽  
Vol 10 (1) ◽  
pp. 52
Author(s):  
Yunxi Zhang ◽  
Gangfeng Wang ◽  
Dong Zhang ◽  
Qi Zhang
Keyword(s):  
Real Time ◽  
Measurement Data ◽  
Physical Space ◽  
Feedback Mechanism ◽  
Virtual Space ◽  
Assembly Process ◽  
Time Data ◽  
Construction Machinery ◽  
Digital Twin ◽  
Assembly Simulation

The construction machinery arm is the key component of construction machinery to complete the operation task; its assembly link directly affects the product quality and operational performance of the whole machinery. To solve the problems of low assembly efficiency and the inability to fully reflect the assembly process indexes and product characteristics in the traditional construction machinery arm assembly, this paper studies assembly process modeling and simulation for the construction machinery arm based on assembly sensing data and digital twin. By extracting and processing the assembly resource data and field measurement data of the machinery arm, the assembly process information database under the digital twin environment is constructed, which lays the foundation for the virtual assembly model construction of the machinery arm. Through the real-time data interaction between virtual space and physical space, a complete assembly of digital twin spaces is formed. Finally, taking the assembly line of an excavator armed as an example, it is shown that the digital twin-based assembly simulation can monitor the assembly process in real-time and optimize its configuration to improve assembly efficiency. Therefore, an effective closed-loop feedback mechanism is constructed for the whole assembly process of the construction machinery arm.

Petri Net Modeling: Container Terminal Production Operation Processing System Analysis

2013 ◽  
Vol 409-410 ◽  
pp. 1320-1324 ◽  
Author(s):  
Wei Zhu Zhong ◽  
Xiao Qing Fu ◽  
Ya Ping Wang
Keyword(s):  
Petri Net ◽  
System Analysis ◽  
Production Control ◽  
Low Cost ◽  
Container Terminal ◽  
Processing System ◽  
Production Operation ◽  
Production Control System ◽  
New Development ◽  
New System

Abstract— The paper presents a new redesigned solution for container terminal production processing system. Firstly, the container terminal Production Operation Processing System process was describe by workflow and DFD Then introduce a new terminal production control system with Computing, Communicating, Controlling Technology character. In the last of article, and the integrality and credibility of new system was proved using Petri Net analysis. The new development solution is to improve some disadvantages existed in old system and to rebuild logistics processes with low cost, high quality, more flexible, faster and smart responsiveness to whole terminal production system.

scholarly journals Flexible and Efficient MMC Digital Twin Realized With Small-Scale Real-Time Simulators

2021 ◽  
Vol 8 (2) ◽  
pp. 24-33
Author(s):  
Stefan Milovanovic ◽  
Ignacio Polanco ◽  
Milan Utvic ◽  
Drazen Dujic
Keyword(s):  
Real Time ◽  
Small Scale ◽  
Digital Twin

scholarly journals OFCOD: On the Fly Clustering Based Outlier Detection Framework

Data ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ahmed Elmogy ◽  
Hamada Rizk ◽  
Amany M. Sarhan
Keyword(s):  
Data Mining ◽  
Image Processing ◽  
Intrusion Detection ◽  
Real Time ◽  
Outlier Detection ◽  
Real World ◽  
Medical Data ◽  
Experimental Results ◽  
Real Time Applications ◽  
Real World Datasets

In data mining, outlier detection is a major challenge as it has an important role in many applications such as medical data, image processing, fraud detection, intrusion detection, and so forth. An extensive variety of clustering based approaches have been developed to detect outliers. However they are by nature time consuming which restrict their utilization with real-time applications. Furthermore, outlier detection requests are handled one at a time, which means that each request is initiated individually with a particular set of parameters. In this paper, the first clustering based outlier detection framework, (On the Fly Clustering Based Outlier Detection (OFCOD)) is presented. OFCOD enables analysts to effectively find out outliers on time with request even within huge datasets. The proposed framework has been tested and evaluated using two real world datasets with different features and applications; one with 699 records, and another with five millions records. The experimental results show that the performance of the proposed framework outperforms other existing approaches while considering several evaluation metrics.

Sign in / Sign up

Export Citation Format

Share Document