scholarly journals Machine Failure Analysis Using Nearest Centroid Classification for Industrial Internet of Things

2019 ◽  
Vol 31 (5) ◽  
pp. 1751
Author(s):  
Jung-Hyok Kwon ◽  
Eui-Jik Kim
Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 501 ◽  
Author(s):  
Evangelina Lara ◽  
Leocundo Aguilar ◽  
Mauricio A. Sanchez ◽  
Jesús A. García

The Industrial Internet of Things (IIoT) consists of sensors, networks, and services to connect and control production systems. Its benefits include supply chain monitoring and machine failure detection. However, it has many vulnerabilities, such as industrial espionage and sabotage. Furthermore, many IIoT devices are resource-constrained, which impedes the use of traditional security services for them. Authentication allows devices to be confident of each other’s identity, preventing some security attacks. Many authentication protocols have been proposed for IIoT; however, they have high computing requirements not viable to resource-constrained devices, or they have been found insecure. In this paper, an authentication protocol for resource-constrained IIoT devices is proposed. It is based on the lightweight operations xor, addition, and subtraction, and a hash function. Also, only four messages are exchanged between the principals to authenticate. It has a low execution-time and communication-cost. Its security was successfully assessed with the formal methods Automated Validation of Internet Security Protocols and Applications (AVISPA) tool and Burrows–Abadi–Needham (BAN) logic, together with an informal analysis of its resistance to known attacks. Its performance and security were compared with state-of-the-art protocols, resulting in a good performance for resource-constrained IIoT devices, and higher security similar to computational expensive schemes.


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


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

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