Edge Computing Architectures in Industry 4.0: A General Survey and Comparison

Sittón-Candanedo, Inés; Alonso, Ricardo S.; González, Sara Rodríguez; Coria, José Alberto García; Prieta, Fernando De la

doi:10.1007/978-3-030-20055-8_12

Cited by 47 publications

(28 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Data management and smart follow in equal measure, with 15 and 16 publications, respectively. In Bavaria, research referring to CPS predominates (30), followed by data management (17), human-machine interaction (16), and smart (7). In Baden Württemberg, the research society concentrates on data management (22).…”

Section: International Analysismentioning

confidence: 99%

“…Furthermore, we provide a comprehensive picture, while other reviews surrounding the research field Industry 4.0 have focused on special aspects of the term, such as: -edge computing [16]; -additive manufacturing/three-dimensional printing [17]; -cyber-physical production systems [18]; -construction industry [19]; -remanufacturing [20]; -environmentally-sustainable manufacturing [21,22]; -interactions with the energy system [23].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Generating Transparency in the Worldwide Use of the Terminology Industry 4.0

et al. 2019

View full text Add to dashboard Cite

In 2011, the concept of Industry 4.0 was introduced and later adopted by the German government, paving the way for a new industrial revolution in Germany. The high significance of this topic is reflected by the large number of corresponding publications. Additionally, the regional focus of research is widespread on a global level and often differs even at a national level. This paper generates transparency regarding the adoption of the concept of Industry 4.0 by analyzing the locations of main contributors within the research field on an international, European, and German-national level. Further, it examines the regionally different foci concerning the concept of Industry 4.0. Having identified four main aspects linked to Industry 4.0 within a pre-study, a quantitative literature research was conducted based on over 800 published papers. The results were further visualized with QGIS. Looking at the results, it can be concluded that the German research community is virtually the only user of the term Industry 4.0, while other institutions seem to link their research to other related concepts. On a German level, the majority of the analyzed studies originate from Southern and Western Germany. North Rhine-Westphalia and the Aachen/Jülich region, in particular, represent main contributors.

show abstract

Section: International Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Generating Transparency in the Worldwide Use of the Terminology Industry 4.0

et al. 2019

View full text Add to dashboard Cite

show abstract

“…To realize the full innovation potential of AI, it must be regarded as a cross-cutting concern for manufacturing IT systems. Current Industry 4.0 reference architectures do not properly integrate the needed building blocks such as new deployment paradigms (e.g., edge-based learning to reduce bandwidth load on the enterprise network), scalable data-processing pipelines and information models, and AI-enabled digital twins used for monitoring and optimizing business intelligence [ 24 , 25 , 26 ]. In addition, the availability of big data has been one of the most important enablers for the recent wave of AI innovations [ 27 ].…”

Section: Motivationmentioning

confidence: 99%

“…For the IT resource aspect, processing all raw data on a public cloud infrastructure is an unscalable solution for many manufacturing companies, either because there is too much sensor data to upload, the latency to the cloud is prohibitive or because the sensor data is too sensitive and the company does not want to expose this. Therefore, edge computing has been proposed and several reference architectures for edge computing in Industry 4.0 have been proposed [ 26 ], such as the far edge reference architecture that includes blockchain support ( ). The term edge computing covers various deployment options: from an on-premises datacenter to embedded computing, e.g., on AR glasses or on mobile robots.…”

Section: Realization Aspects Of Ai-based System Elementsmentioning

confidence: 99%

An Artificial Intelligence-Based Collaboration Approach in Industrial IoT Manufacturing: Key Concepts, Architectural Extensions and Potential Applications

Trakadas

Simoens

Gkonis

et al. 2020

Sensors

View full text Add to dashboard Cite

The digitization of manufacturing industry has led to leaner and more efficient production, under the Industry 4.0 concept. Nowadays, datasets collected from shop floor assets and information technology (IT) systems are used in data-driven analytics efforts to support more informed business intelligence decisions. However, these results are currently only used in isolated and dispersed parts of the production process. At the same time, full integration of artificial intelligence (AI) in all parts of manufacturing systems is currently lacking. In this context, the goal of this manuscript is to present a more holistic integration of AI by promoting collaboration. To this end, collaboration is understood as a multi-dimensional conceptual term that covers all important enablers for AI adoption in manufacturing contexts and is promoted in terms of business intelligence optimization, human-in-the-loop and secure federation across manufacturing sites. To address these challenges, the proposed architectural approach builds on three technical pillars: (1) components that extend the functionality of the existing layers in the Reference Architectural Model for Industry 4.0; (2) definition of new layers for collaboration by means of human-in-the-loop and federation; (3) security concerns with AI-powered mechanisms. In addition, system implementation aspects are discussed and potential applications in industrial environments, as well as business impacts, are presented.

show abstract

“…The variations depend on how individual business circles interpret this term [80]. In the United States, it is seen as the integration of people with things and things among themselves, combining the analysis of large data sets with the Internet of Things [81,82].…”

mentioning

confidence: 99%

Practical Application of the Industry 4.0 Concept in a Steel Company

2020

View full text Add to dashboard Cite

The primary aim of this paper was to present and analyze practical solutions of Industry 4.0 as applied in the Re Alloys company. The research question was whether the implementation of the digitization process based on Industry 4.0 resulted in changes to the organizational structure of the company and whether this brought about an improvement in the energy and material efficiency of the company. The research method used in the paper was the case study method. In view of the project’s results, we concluded that implementation of the new solution based on digitalization caused increased energy and material efficiency, often forced by external factors stemming from the operation of competitive markets. Technological changes also require the application of IT technologies and communication systems in managing production. Access to this information is also a chance to gain a competitive advantage.

show abstract

Edge Computing Architectures in Industry 4.0: A General Survey and Comparison

Cited by 47 publications

References 18 publications

Generating Transparency in the Worldwide Use of the Terminology Industry 4.0

Generating Transparency in the Worldwide Use of the Terminology Industry 4.0

An Artificial Intelligence-Based Collaboration Approach in Industrial IoT Manufacturing: Key Concepts, Architectural Extensions and Potential Applications

Practical Application of the Industry 4.0 Concept in a Steel Company

Contact Info

Product

Resources

About