scholarly journals Structuring Reference Architectures for the Industrial Internet of Things

2019 ◽  
Vol 11 (7) ◽  
pp. 151 ◽  
Author(s):  
Sebastian R. Bader ◽  
Maria Maleshkova ◽  
Steffen Lohmann

The ongoing digital transformation has the potential to revolutionize nearly all industrial manufacturing processes. However, its concrete requirements and implications are still not sufficiently investigated. In order to establish a common understanding, a multitude of initiatives have published guidelines, reference frameworks and specifications, all intending to promote their particular interpretation of the Industrial Internet of Things (IIoT). As a result of the inconsistent use of terminology, heterogeneous structures and proposed processes, an opaque landscape has been created. The consequence is that both new users and experienced experts can hardly manage to get an overview of the amount of information and publications, and make decisions on what is best to use and to adopt. This work contributes to the state of the art by providing a structured analysis of existing reference frameworks, their classifications and the concerns they target. We supply alignments of shared concepts, identify gaps and give a structured mapping of regarded concerns at each part of the respective reference architectures. Furthermore, the linking of relevant industry standards and technologies to the architectures allows a more effective search for specifications and guidelines and supports the direct technology adoption.

2019 ◽  
Vol 9 (20) ◽  
pp. 4323 ◽  
Author(s):  
López de Lacalle ◽  
Posada

The new advances of IIOT (Industrial Internet of Things), together with the progress in visual computing technologies, are being addressed by the research community with interesting approaches and results in the Industry 4.0 domain[...]


2021 ◽  
Vol 166 ◽  
pp. 125-139
Author(s):  
Praveen Kumar Malik ◽  
Rohit Sharma ◽  
Rajesh Singh ◽  
Anita Gehlot ◽  
Suresh Chandra Satapathy ◽  
...  

2019 ◽  
Vol 109 (07-08) ◽  
pp. 550-554
Author(s):  
J. Pöppelbuß ◽  
M. Ebel ◽  
D. Jaspert ◽  
D. Mann ◽  
D. Behnke

Vorhandene Maschinen und Anlagen, die im Feld laufen, sind oftmals produktiv, aber nicht auf dem technologischen Stand, um Smart Services zu erbringen. Marktpotenziale im Servicegeschäft werden hierdurch nicht ausgeschöpft und neue Kundenbedürfnisse können nicht adressiert werden. Das stellt Unternehmen vor die Herausforderung ihr vorhandenes Equipment nachzurüsten. Dieser Beitrag soll praxisnah einen Einblick in das Vorgehen zur Nachrüstung von Maschinen und Anlagen geben.   Existing machines and plants in the field are often productive but not state of the art to provide smart services. Market potentials in the service business are not exploited and changing customer needs due to the Industrial Internet of Things (IIoT) cannot be addressed. This challenges companies to retrofit their existing of their existing equipment. This article describe a practice-oriented retrofit approach.


Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2855 ◽  
Author(s):  
Jesus Jaime Moreno Escobar ◽  
Oswaldo Morales Matamoros ◽  
Ixchel Lina Reyes ◽  
Ricardo Tejeida-Padilla ◽  
Liliana Chanona Hernández ◽  
...  

The Industrial Internet of Things (IIoT) network generates great economic benefits in processes, system installation, maintenance, reliability, scalability, and interoperability. Wireless sensor networks (WSNs) allow the IIoT network to collect, process, and share data of different parameters among Industrial IoT sense Node (IISN). ESP8266 are IISNs connected to the Internet by means of a hub to share their information. In this article, a light-diffusion algorithm in WSN to connect all the IISNs is designed, based on the Peano fractal and swarm intelligence, i.e., without using a hub, simply sharing parameters with two adjacent IINSs, assuming that any IISN knows the parameters of the rest of these devices, even if they are not adjacent. We simulated the performance of our algorithm and compared it with other state-of-the-art protocols, finding that our proposal generates a longer lifetime of the IIoT network when few IISNs were connected. Thus, there is a saving-energy of approximately 5% but with 64 nodes there is a saving of more than 20%, because the IIoT network can grow in a 3 n way and the proposed topology does not impact in a linear way but log 3 , which balances energy consumption throughout the IIoT network.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Jawhara Bader ◽  
Anna Lito Michala

The technological advancements in the Internet of Things (IoT) and related technologies lead to revolutionary advancements in many sectors. One of these sectors, is the industrial sector red that leverages IoT technologies forming the Industrial Internet of Things (IIoT). IIoT has the potential to enhance the manufacturing process by improving the quality, trace-ability, and integrity of the industrial processes. The enhancement of the manufacturing process is achieved by deploying IoT devices (sensors) across the manufacturing facilities; therefore, monitoring systems are required to collect (from multiple locations) and analyse the data, most likely in the cloud. As a result, IIoT monitoring systems should be secure, preserve the privacy, and provide real-time responses for critical decision-making. In this review, we identified a gap in the state-of-the-art of secure IIoT and propose a set of criteria for secure and privacy preserving IIoT systems to enhance efficiency and deliver better IIoT applications.


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.


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


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