A big data-centric architecture metamodel for Industry 4.0

Martínez, Patricia López; Dintén, Ricardo; Drake, José M.; Zorrilla, Marta E.

doi:10.1016/j.future.2021.06.020

Cited by 35 publications

(15 citation statements)

References 46 publications

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“…These systems are largely dedicated to manufacturing companies and through the use of distributed sensors communicating via a wireless network, they analyze data and support real-time decision making [89,90]. There are, however, meta-models, such as those proposed by Martinez et al [91], reflecting corporate and technical architectures that can be adapted to selected service enterprise processes. Systems created on the basis of these meta-models can be used in a service company for modeling service costs, contracting and supporting decisions made by people thanks to the use of big data analyzes.…”

Section: Discussionmentioning

confidence: 99%

The Digital Chasm between an Idea and Its Implementation in Industry 4.0—The Case Study of a Polish Service Company

Jasińska

2021

Sustainability

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Digitization in Industry 4.0 is a key trend in a modern company’s development. However, business practice shows that digitization can be associated not only with the prospect of development but with numerous limitations that a company may struggle with. The goal of this manuscript is to verify the existence and identify of the management gaps that lead to formation of digitization problems in companies under the conditions of Industry 4.0. Management gap is understood here as a set of discontinuities, identified within management functions, which result in specific problems in the implementation of digitization projects. In general, this aspect is omitted in the literature on the subject, which focuses on benefits of implementing Industry 4.0 technology. The chosen goal of the manuscript is part of the research trend related to the identification of general digitization problems and to a company’s development, taking into account the use of technological solutions, as well as to the scope of research on the problems of implementing ICT projects. The development of an enterprise is understood as the ability to improve an organization both in the face of internal challenges and the environmental with maintaining innovation potential. The research structure is based on the construction of a conceptual model of management gaps and its empirical verification. In the theoretical part, the chosen research method is analysis of literature from the last 20 years and in the practical part analysis of a business case supplemented with an in-depth interview conducted among the management of the analyzed company. In the theoretical part, the article defines basic concepts related to Industry 4.0 and digitization of companies. It presents the place and role of digitization and its impact on the blurring of boundaries of traditional management layers. Based on these considerations, a conceptual model is developed defining management gaps within which problems of digitization of enterprises are indicated. The practical part of the article presents an empirical verification of the existence of the formulated management gaps on the basis of a business case analysis. The case study describes a mass, geographically dispersed implementation of the application for 34,000 users, which is the result of the implementation of the digitization strategy. Conclusions were formulated in the last part of the manuscript. On the theoretical ground, the analysis confirms that the process of digitization in an enterprise under the conditions of Industry 4.0 is related to blurring the boundaries of operational, tactical and strategic management. The premises of the said blur are identifiable and appear in each of the above-mentioned layers. On the practical ground, the existence of reasons for blurring the boundaries of management is related to the need to adapt the organization to the new operating conditions related to Industry 4.0. The strategic activities should be targeted at determining the directions of company improvement, which should precede the efforts to implement advanced solutions in the field of Industry 4.0. This approach allows providing a sustainable company development with the possibility of creating short-term effects and maintaining a long-term growth perspective.

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Section: Discussionmentioning

confidence: 99%

The Digital Chasm between an Idea and Its Implementation in Industry 4.0—The Case Study of a Polish Service Company

Jasińska

2021

Sustainability

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“…Their software for ML model deployment with Acumos and ONAP platforms is separated into decoupled components that exchange data between themselves via Kafka streams. Similarly, Herrero et al [59] presents a data intensive platform for Industry 4.0 following the RAI4.0 reference architecture [77] where software and hardware components are modelled as streams producers and consumers. The nature of the data also plays a role when selecting streams as the system's data model.…”

Section: Data As a First Class Citizenmentioning

confidence: 99%

Real-world Machine Learning Systems: A survey from a Data-Oriented Architecture Perspective

Cabrera¹,

Paleyes²,

Thodoroff³

et al. 2023

Preprint

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With the upsurge of interest in artificial intelligence machine learning (ML) algorithms, originally developed in academic environments, are now being deployed as parts of real-life systems that deal with large amounts of heterogeneous, dynamic, and high-dimensional data. Deployment of ML methods in real life is prone to challenges across the whole system life-cycle from data management to systems deployment, monitoring, and maintenance. Data-Oriented Architecture (DOA) is an emerging software engineering paradigm that has the potential to mitigate these challenges by proposing a set of principles to create data-driven, loosely coupled, decentralised, and open systems. However DOA as a concept is not widespread yet, and there is no common understanding of how it can be realised in practice. This review addresses that problem by contextualising the principles that underpin the DOA paradigm through the ML system challenges. We explore the extent to which current architectures of ML-based real-world systems have implemented the DOA principles. We also formulate open research challenges and directions for further development of the DOA paradigm.

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“…Cloud computing technology integrates distributed computing, parallel computing, and grid computing, and is the commercial realization of these computing models [4]. Cloud computing provides powerful computing power and storage space for cloud computing users by concentrating computing resources and using hardware virtualization technology.…”

Section: Cloud Computingmentioning

confidence: 99%

Application of big data technology in business management

Xiang¹,

Hong²,

Peng³

2022

International Conference on Mechanisms and Robotics (ICMAR 2022)

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In the era of big data, data and information have become important resources. With a large amount of data and the ability to mine data and information, companies can occupy an important position in the market. In the face of the ever-changing economic and social environment, the existing business management system has many shortcomings. At present, most companies still use human-based business management systems, which have poor immediacy and high cost, and it is difficult to dig out potential information. In order to improve the existing business management system problems, it is necessary to use front-end information technology to build a more efficient business management big data analysis platform to enhance the core competitiveness of enterprises. The cloud computing-based business management big data analysis platform uses descriptive analysis, regular analysis and decision-making analysis methods to ensure university analysis of accounting big data and introduces a cloud computing security assurance framework into the security mechanism to ensure big data security and integrity.

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A big data-centric architecture metamodel for Industry 4.0

Cited by 35 publications

References 46 publications

The Digital Chasm between an Idea and Its Implementation in Industry 4.0—The Case Study of a Polish Service Company

The Digital Chasm between an Idea and Its Implementation in Industry 4.0—The Case Study of a Polish Service Company

Real-world Machine Learning Systems: A survey from a Data-Oriented Architecture Perspective

Application of big data technology in business management

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