Interoperability of the Time of Industry 4.0 and the Internet of Things

Lelli, Francesco

doi:10.3390/fi11020036

Cited by 57 publications

(28 citation statements)

References 17 publications

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“…IoT is defined as a "group of infrastructures interconnecting connected objects and allowing their management, data mining and the access to data they generate" [11] (p. 73). It embodies the next phase toward mass digitization of supply chains to facilitate the so-called Industry 4.0 [12]. IoT encompasses devices such as sensors as well as passive, semi-passive (or semi-active), and active Radio Frequency ID tags (RFID), and other electronics which are connected over a network.…”

Section: Introductionmentioning

confidence: 99%

Leveraging the Internet of Things and Blockchain Technology in Supply Chain Management

2019

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Modern supply chains have evolved into highly complex value networks and turned into a vital source of competitive advantage. However, it has become increasingly challenging to verify the source of raw materials and maintain visibility of products and merchandise while they are moving through the value chain network. The application of the Internet of Things (IoT) can help companies to observe, track, and monitor products, activities, and processes within their respective value chain networks. Other applications of IoT include product monitoring to optimize operations in warehousing‚ manufacturing, and transportation. In combination with IoT, Blockchain technology can enable a broad range of different application scenarios to enhance value chain transparency and to increase B2B trust. When combined, IoT and Blockchain technology have the potential to increase the effectiveness and efficiency of modern supply chains. The contribution of this paper is twofold. First, we illustrate how the deployment of Blockchain technology in combination with IoT infrastructure can streamline and benefit modern supply chains and enhance value chain networks. Second, we derive six research propositions outlining how Blockchain technology can impact key features of the IoT (i.e., scalability, security, immutability and auditing, information flows, traceability and interoperability, quality) and thus lay the foundation for future research projects.

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Section: Introductionmentioning

confidence: 99%

Leveraging the Internet of Things and Blockchain Technology in Supply Chain Management

2019

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“…Nevertheless, RDF is proven more effective due to providing models extendable to multiple techniques that are represented by unique ontologies [37]. A thorough list of ontologies by the devices that use them has been published by Lelli [38] in which they discuss and compare World Wide Web Consortium (W3C) Semantic Sensor Network, Fiesta-IoT, Smart Energy Aware Systems (SEASD), Machine-to-Machine (M2M) solutions (http://www.onem2m.org), and Schema.org technologies, to name a few.…”

Section: Semantic Interoperabilitymentioning

confidence: 99%

Interoperability in Smart Manufacturing: Research Challenges

et al. 2019

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Recent advances in manufacturing technology, such as cyber–physical systems, industrial Internet, AI (Artificial Intelligence), and machine learning have driven the evolution of manufacturing architectures into integrated networks of automation devices, services, and enterprises. One of the resulting challenges of this evolution is the increased need for interoperability at different levels of the manufacturing ecosystem. The scope ranges from shop–floor software, devices, and control systems to Internet-based cloud-platforms, providing various services on-demand. Successful implementation of interoperability in smart manufacturing would, thus, result in effective communication and error-prone data-exchange between machines, sensors, actuators, users, systems, and platforms. A significant challenge to this is the architecture and the platforms that are used by machines and software packages. A better understanding of the subject can be achieved by studying industry-specific communication protocols and their respective logical semantics. A review of research conducted in this area is provided in this article to gain perspective on the various dimensions and types of interoperability. This article provides a multi-faceted approach to the research area of interoperability by reviewing key concepts and existing research efforts in the domain, as well as by discussing challenges and solutions.

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“…The former, also known as the 4th industrial revolution, portrays that business objectives, intelligent algorithms, analytics, predictive technologies and cyber-physical systems are teaming together to realize a new thinking of production management and factory transformation [4]. It ultimately represents a convergence of information technology and operational technology in which supply and production chains will dynamically adjust themselves to provide on-demand customization of manufacturing [5]. The latter refers to the adoption of the IT (Information Technology) domain IoT (Internet of Things) paradigm in manufacturing by joining sensors and actuators, control systems, communication facilities, machine-to-machine, data analytics and security mechanisms together through embedded technology [6].…”

Section: Introductionmentioning

confidence: 99%

Extracting Value from Industrial Alarms and Events: A Data-Driven Approach Based on Exploratory Data Analysis

Bezerra

Silva

Guedes

et al. 2019

Sensors

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Alarm and event logs are an immense but latent source of knowledge commonly undervalued in industry. Though, the current massive data-exchange, high efficiency and strong competitiveness landscape, boosted by Industry 4.0 and IIoT (Industrial Internet of Things) paradigms, does not accommodate such a data misuse and demands more incisive approaches when analyzing industrial data. Advances in Data Science and Big Data (or more precisely, Industrial Big Data) have been enabling novel approaches in data analysis which can be great allies in extracting hitherto hidden information from plant operation data. Coping with that, this work proposes the use of Exploratory Data Analysis (EDA) as a promising data-driven approach to pave industrial alarm and event analysis. This approach proved to be fully able to increase industrial perception by extracting insights and valuable information from real-world industrial data without making prior assumptions.

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Interoperability of the Time of Industry 4.0 and the Internet of Things

Cited by 57 publications

References 17 publications

Leveraging the Internet of Things and Blockchain Technology in Supply Chain Management

Leveraging the Internet of Things and Blockchain Technology in Supply Chain Management

Interoperability in Smart Manufacturing: Research Challenges

Extracting Value from Industrial Alarms and Events: A Data-Driven Approach Based on Exploratory Data Analysis

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