Linking permissioned blockchain to Internet of Things (IoT)-BIM platform for off-site production management in modular construction

2022 ◽  
Vol 135 ◽  
pp. 103573
Author(s):  
Liupengfei Wu ◽  
Weisheng Lu ◽  
Fan Xue ◽  
Xiao Li ◽  
Rui Zhao ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Production Management ◽  
Modular Construction

scholarly journals Diagnosis of Problems in Truck Ore Transport Operations in Underground Mines Using Various Machine Learning Models and Data Collected by Internet of Things Systems

Minerals ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1128
Author(s):  
Sebeom Park ◽  
Dahee Jung ◽  
Hoang Nguyen ◽  
Yosoon Choi
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Production Management ◽  
Classification And Regression Tree ◽  
Underground Mines ◽  
Validation Dataset ◽  
Support Vector ◽  
Learning Models ◽  
K Nearest Neighbor ◽  
Machine Learning Models

This study proposes a method for diagnosing problems in truck ore transport operations in underground mines using four machine learning models (i.e., Gaussian naïve Bayes (GNB), k-nearest neighbor (kNN), support vector machine (SVM), and classification and regression tree (CART)) and data collected by an Internet of Things system. A limestone underground mine with an applied mine production management system (using a tablet computer and Bluetooth beacon) is selected as the research area, and log data related to the truck travel time are collected. The machine learning models are trained and verified using the collected data, and grid search through 5-fold cross-validation is performed to improve the prediction accuracy of the models. The accuracy of CART is highest when the parameters leaf and split are set to 1 and 4, respectively (94.1%). In the validation of the machine learning models performed using the validation dataset (1500), the accuracy of the CART was 94.6%, and the precision and recall were 93.5% and 95.7%, respectively. In addition, it is confirmed that the F1 score reaches values as high as 94.6%. Through field application and analysis, it is confirmed that the proposed CART model can be utilized as a tool for monitoring and diagnosing the status of truck ore transport operations.

scholarly journals Pellet Roasting Management System Based on Deep Learning and Internet of Things

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Weixing Liu ◽  
Liyan Zhang ◽  
Jiahao Wang ◽  
Yiming Yang ◽  
Jie Li ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Rotary Kiln ◽  
Management System ◽  
Production Management ◽  
Image Data ◽  
Control Mode ◽  
Enterprise Information ◽  
Blast Furnace Ironmaking ◽  
Use Of The Internet

Pellet is widely used in blast furnace ironmaking. Pellet quality affects the effect of ironmaking, the existing control system of grating-rotary kiln mainly adopts manual control mode, and the quality of pellet production largely depends on the experience, fatigue, and sense of responsibility of the site operators. The use of the Internet of things (IoT) technology in the integration and improvement of enterprise information level, to achieve fine, intelligent production management, at the same time, is conducive to promoting steel enterprises to reduce costs and increase efficiency, energy conservation and emission reduction, transformation and upgrading, and taking a new road to industrialization. According to the working principle and technological characteristics of the grate-rotary kiln at all stages, this paper designs the management system of firing pellets based on convolutional neural network (CNN) and IoT technology, so as to realize automatic recognition of image data obtained by the perceptual layer and make an intelligent analysis of it. The system can classify the working conditions of the current equipment, so as to judge whether the production process parameters of the grate-rotary kiln are up to the standard, thus achieving the goal of controlling the quality of the finished pellet.

scholarly journals Integrated Management Software for Factory Production of Modular Buildings

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
SungHoon Nam ◽  
DooYong Lee ◽  
BongHo Cho ◽  
KyungRai Kim
Keyword(s):  
Management System ◽  
Production Management ◽  
Integrated Management ◽  
Formal System ◽  
Modular Construction ◽  
Construction Time ◽  
Modular Systems ◽  
Production Management System ◽  
Modular Production ◽  
Result Analysis

After the first modular construction project in Korea in 2003, the scope and demand for modular systems have gradually increased. However, modular producers in Korea utilize spreadsheets to manage the process, manpower, and materials required for modular construction. This is inadequate compared to other countries that are more advanced in modular construction such as Japan and the United Kingdom. The management system in Korea decreases the effectiveness of modular construction in reducing construction time and cost. There is no formal system for managing modular production in Korea. Although some construction management programs utilized in the traditional construction industry are available, they do not reflect the flow of modular production, that is, to simultaneously produce several types of modules in accordance with demand in a factory. This research develops a modular-construction-specific production management system that has three overall functions: factory setup, project creation, and result analysis. These functions can link all the relevant data for managing modular production and can help manage several types of modules. The production management system is verified through simulation of the existing processes observed for a completed project and comparing the results to an alternative process. Through such comparisons, an optimized process design can be achieved.

scholarly journals Discussion on the Flexible Manufacturing and Operation Strategy Model for a Machine Tool Component Company in Taiwan

2021 ◽  
Vol 14 (10) ◽  
pp. 1
Author(s):  
Jui-Lung Chen ◽  
Shih-Hsuan Yang
Keyword(s):  
Internet Of Things ◽  
Flexible Manufacturing ◽  
Manufacturing Industry ◽  
Production Management ◽  
Production Model ◽  
Smart Manufacturing ◽  
Labor Costs ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
The Impact

Recently, many manufacturing industries have been facing challenges such as rising material costs, small-volume and large-variety products, shortened production cycles, increased labor costs and longer after-sales service times, which is a very tough challenge for most small and medium-sized component manufacturing suppliers. In addition to the current hot topics in the manufacturing industry - Smart Manufacturing (Industry 4.0) and lean production management, if small and medium-sized enterprises are not able to adjust the pace of manufacturing timely and find a suitable production model, they will soon be overwhelmed by the torrent of the era of speed and accuracy. In the face of the dramatic changes in the industry structure, the company can deploy the global expansion of overseas customers in advance, and adjust to apply and implement a flexible manufacturing model system through the introduction of the Industrial Internet of Things and flexible manufacturing production management. In order to meet the market needs, the manufacturing industry is gradually oriented towards customized production and the rapid development of new products. To meet such stringent requirements, flexible manufacturing becomes one of the necessary ways for enterprises to consider their development models. Therefore, the efficiency and reliability of work can be improved through the Industrial Internet of Things that facilitates machine-to-machine communication, cloud-based big data and learning and imitations of smart robots. This study is an in-depth study of a company that is currently in the process of digital transformation, collecting relevant information and reviewing the analysis to find a suitable smart manufacturing solution for the company and to explore the impact of the COVID-19 pandemic on the strategic development of the company. The findings can provide a significant reference for homotypic companies in the development of their business strategies.

scholarly journals Research on Intelligent Power Automation Technology Based on Edge Computing of Power Internet of Things

2020 ◽  
Vol 204 ◽  
pp. 02006
Author(s):  
Su Zhiyong ◽  
Lai Weiping ◽  
Zhang Yanghua ◽  
Huang Yanshan
Keyword(s):  
Internet Of Things ◽  
Management System ◽  
Production Management ◽  
Rapid Development ◽  
Edge Computing ◽  
Equipment Management ◽  
Power Equipment ◽  
Functional Requirements ◽  
Rfid Technology ◽  
Automation Technology

With the rapid development of modern economy and the rapid promotion of science and technology, electricity is the realistic need for further transformation of various industries in contemporary society. Because the traditional power management mode is relatively backward and the automation level of different industries is uneven, these will limit the development of intelligent power automation. Therefore, based on the edge computing of power Internet of Things, this paper studies intelligent power automation technology, which is of great value for realizing power automation and improving the management level of power equipment. In this paper, aiming at the research of intelligent power automation technology, based on the edge computing of power Internet of Things, the Internet of Things system based on RFID technology is studied. This system constructs the basic architecture of Internet of Things for smart power applications. The architecture is composed of sensing layer, network layer and application layer, which is used to realize information collection, identification and transmission, and its application in the production management of power Internet of Things. This paper analyzes the functional requirements, factors to be considered, main features and main functions of power equipment management system, gives the design ideas of power equipment management system, and designs an intelligent power equipment system based on edge computing of power Internet of Things. The research results show that RFID technology based on edge computing of power Internet of Things is feasible to realize intelligent power automation, can solve some problems in current power technology, and is of great significance to realize intelligent power automation.

scholarly journals Design of Online Mine Safety Detection System Based on Internet of Things

2016 ◽  
Vol 12 (12) ◽  
pp. 60 ◽  
Author(s):  
Zhao-ming Qian ◽  
Yan-bin Yuan ◽  
Sa-sa Zhang ◽  
Gao-feng Ren
Keyword(s):  
Internet Of Things ◽  
Production Management ◽  
Safety Management ◽  
Detection System ◽  
Mine Safety ◽  
Open Architecture ◽  
Comprehensive Management ◽  
Safety Production ◽  
On Line ◽  
Internet Of Things Technology

Safety production is a major problem faced by mining enterprises. In view of the requirements of mine safety production and the development of information technology, the application of Internet of Things technology to the mining process can not only improve the safety management technology of mine enterprises, The steady growth of the national economy and the sustainable and healthy development of mining have a profound impact. The on-line monitoring system of mining safety based on Internet of Things technology can help mine personnel, equipment and environment comprehensive management, enrich the mine safety production management means, and improve the ability of mine to resist various risks and disasters. In this paper, combined with the actual situation of the mine, focusing on the Internet of Things technology-based mine safety inspection and protection system construction of the necessity, and based on the three-tier architecture of the open architecture of the network, based on mine safety on-line detection support system Of the application model structure. For the construction of mine networking provides the experience and technology<strong>.</strong>

Mine Internet of Things Based on Neural Network and its Research and Application

2011 ◽  
Vol 467-469 ◽  
pp. 1746-1752
Author(s):  
Zhen Yu Wang ◽  
Chun Lei Wang ◽  
Zhi Dong Wang ◽  
Shao Yi Jia
Keyword(s):  
Neural Network ◽  
Internet Of Things ◽  
Production Management ◽  
Information Age ◽  
Mining Enterprise ◽  
Development Direction ◽  
Control Production ◽  
Neural Network System ◽  
Safety Production ◽  
And Control

Internet of things is an ultimate development direction of the information age, while mine informatization is only way to realize the safety production and management of mining enterprise. In this paper, we research and simulate the human neural network system and propose the structure of internet of things based on human neural network. We connect all the objects and systems of the mines through mine internet of things to simulate the reflex activities of human body, regulate and control production, management and other links of the mining enterprises, so that it will become a coordinated and efficient whole.

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