Production management guided by industrial internet of things and adaptive scheduling in smart factories

2022 ◽  
pp. 117-152
Author(s):  
Dimitris Mourtzis ◽  
Nikos Panopoulos ◽  
John Angelopoulos
2020 ◽  
Author(s):  
Karthik Muthineni

The new industrial revolution Industry 4.0, connecting manufacturing process with digital technologies that can communicate, analyze, and use information for intelligent decision making includes Industrial Internet of Things (IIoT) to help manufactures and consumers for efficient controlling and monitoring. This work presents the design and implementation of an IIoT ecosystem for smart factories. The design is based on Siemens Simatic IoT2040, an intelligent industrial gateway that is connected to modbus sensors publishing data onto Network Platform for Internet of Everything (NETPIE). The design demonstrates the capabilities of Simatic IoT2040 by taking Python, Node-Red, and Mosca into account that works simultaneously on the device.


2021 ◽  
Vol 14 (10) ◽  
pp. 1
Author(s):  
Jui-Lung Chen ◽  
Shih-Hsuan Yang

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.


2019 ◽  
Vol 252 ◽  
pp. 09003
Author(s):  
Jakub Pizoń ◽  
Grzegorz Kłosowski ◽  
Jerzy Lipski

The following paper presents a key role and potential of Industrial Internet of Things (IIoT) in industrial applications as a solution for monitoring and maintaining manufacturing assets. IIoT is particularly important due to progressing computerisation of hardware resources leading to development of a virtualised model of autonomous real-time production management. Adequately article presents case study of IIoT use in production environment – both methodical and analytic approach is presented.


2020 ◽  
Vol 24 (1) ◽  
pp. 183-188
Author(s):  
D. Smolych ◽  
◽  
V. Stelmashchuk ◽  

Annotation. Introduction. Production management in current conditions is difficult, given the constant updating of techniques and technologies. The methodology of production management successfully chosen by the management is a guarantee of high efficiency of production operations at all stages of production – from the receipt of raw materials on the production line, to the shipment of finished products. Different management methodologies have their pros and cons for different types of industries. Therefore, the problem of qualitative selection of the best methods and construction of an effective mechanism of production management today is quite important. Purpose. The purpose of the study is to analyze the methods and technologies of production management of industrial enterprises within the modern concept of Industry 4.0. аnd highlight the benefits of their use. Results. The methods of production process management used in industry are studied. The factors influencing the improvement of production management methods are considered: human factor, labor factor, information factor, system factors. The principles of the Industry 4.0 concept are analyzed. compatibility; decentralization; real-time analytics; virtualization; service orientation; modularity and scalability. The necessity of introduction and operation of the following systems and methods of information processing is proved: production management system (MES), ERP-systems, industrial (industrial) Internet of things, method of customer profiling. The tools of improvement of direct production operations within the framework of the Industry 4.0 concept are studied, namely: 3D-printing, augmented reality, robotics and process automation. The advantages of using the considered methods of production management provided by the concept of industry Industry 4.0 are systematized. Conclusions. Achieving high management efficiency is possible only as a result of continuous improvement of techniques and methods, because the use of the same methods can lead to stagnation. That is why management must constantly monitor the improvement or updating of existing management methods, in accordance with the trends dictated by the changing modern environment. Today, there are major changes in the industry, as new concepts and production management systems emerge that require the introduction of best practices and technologies, including Industry 4.0, which focuses on advanced robotics and automation. Keywords: production management system; ERP-systems; industrial Internet of Things; 3D-printing; augmented reality; robotics; automation.


Author(s):  
С.Л. Добрынин ◽  
В.Л. Бурковский

Произведен обзор технологий в рамках концепции четвертой промышленной революции, рассмотрены примеры реализации новых моделей управления технологическими процессами на базе промышленного интернета вещей. Описано техническое устройство основных подсистем системы мониторинга и контроля, служащей для повышения осведомленности о фактическом состоянии производственных ресурсов в особенности станков и аддитивного оборудования в режиме реального времени. Архитектура предлагаемой системы состоит из устройства сбора данных (УСД), реализующего быстрый и эффективный сбор данных от станков и шлюза, передающего ликвидную часть информации в облачное хранилище для дальнейшей обработки и анализа. Передача данных выполняется на двух уровнях: локально в цехе, с использованием беспроводной сенсорной сети (WSN) на базе стека протоколов ZigBee от устройства сбора данных к шлюзам и от шлюзов в облако с использованием интернет-протоколов. Разработан алгоритм инициализации протоколов связи между устройством сбора данных и шлюзом, а также алгоритм выявления неисправностей в сети. Расчет фактического времени обработки станочных подсистем позволяет более эффективно планировать профилактическое обслуживание вместо того, чтобы выполнять задачи обслуживания в фиксированные интервалы без учета времени использования оборудования We carried out a review of technologies within the framework of the concept of the fourth industrial revolution; we considered examples of the implementation of new models of process control based on the industrial Internet of things. We described the technical structure of the main subsystems of the monitoring and control system to increase awareness of the actual state of production resources in particular machine tools and additive equipment in real time. The architecture of the proposed system consists of a data acquisition device (DAD) that implements fast and efficient data collection from machines and a gateway that transfers the liquid part of information to the cloud storage for further processing and analysis. We carried out the data transmission at two levels, locally in the workshop, using a wireless sensor network (WSN) based on ZigBee protocol stack from the data acquisition device to the gateways and from the gateways to the cloud using Internet protocols. An algorithm was developed for initializing communication protocols between a data acquisition device and a gateway, as well as an algorithm for detecting network malfunctions. Calculating the actual machining time of machine subsystems allows us to more efficiently scheduling preventive maintenance rather than performing maintenance tasks at fixed intervals without considering equipment usage


2021 ◽  
Vol 173 ◽  
pp. 150-159
Author(s):  
Keming Mao ◽  
Gautam Srivastava ◽  
Reza M. Parizi ◽  
Mohammad S. Khan

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