Industrial Big Data as a Result of IoT Adoption in Manufacturing
TLDR
This paper presents how the adoption of IoT in manufacturing, considering sensory systems and mobile devices, will generate industrial Big Data, and a developed IoT application is presented showing how real industrial data can be generated leading to Industrial Big Data.About:
This article is published in Procedia CIRP.The article was published on 2016-01-01 and is currently open access. It has received 327 citations till now. The article focuses on the topics: Big data.read more
Citations
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Data-driven smart manufacturing
TL;DR: The role of big data in supporting smart manufacturing is discussed, a historical perspective to data lifecycle in manufacturing is overviewed, and a conceptual framework proposed in the paper is proposed.
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Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison
Qinglin Qi,Fei Tao +1 more
TL;DR: The similarities and differences between big data and digital twin are compared from the general and data perspectives and how they can be integrated to promote smart manufacturing are discussed.
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Scanning the Industry 4.0: A Literature Review on Technologies for Manufacturing Systems
TL;DR: The Industry 4.0 environment is scanned on this paper, describing the so-called enabling technologies and systems over the manufacturing environment.
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A review of the meanings and the implications of the Industry 4.0 concept
Ana C. Pereira,Fernando Romero +1 more
TL;DR: In this paper, a literature review is made to understand the Industry 4.0 concept in its technological dimension, and to comprehend its impacts, which has consequences on industry, markets and economy, improving production processes and increasing productivity.
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The role of big data analytics in Internet of Things
Ejaz Ahmed,Ibrar Yaqoob,Ibrahim Abaker Targio Hashem,Imran Khan,Abdelmuttlib Ibrahim Abdalla Ahmed,Muhammad Imran,Athanasios V. Vasilakos +6 more
TL;DR: This paper explores the recent advances in big data analytics for IoT systems as well as the key requirements for managing big data and for enabling analytics in an IoT environment, and taxonomized the literature based on important parameters.
References
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The Internet of Things: A survey
TL;DR: This survey is directed to those who want to approach this complex discipline and contribute to its development, and finds that still major issues shall be faced by the research community.
Book
Big data: The next frontier for innovation, competition, and productivity
TL;DR: The amount of data in the authors' world has been exploding, and analyzing large data sets will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus, according to research by MGI and McKinsey.
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A review on machinery diagnostics and prognostics implementing condition-based maintenance
TL;DR: This paper attempts to summarise and review the recent research and developments in diagnostics and prognostics of mechanical systems implementing CBM with emphasis on models, algorithms and technologies for data processing and maintenance decision-making.
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Beyond the hype
Amir H. Gandomi,Murtaza Haider +1 more
TL;DR: The need to develop appropriate and efficient analytical methods to leverage massive volumes of heterogeneous data in unstructured text, audio, and video formats is highlighted and the need to devise new tools for predictive analytics for structured big data is reinforced.
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The rise of big data on cloud computing
Ibrahim Abaker Targio Hashem,Ibrar Yaqoob,Nor Badrul Anuar,Salimah Binti Mokhtar,Abdullah Gani,Samee U. Khan +5 more
TL;DR: The definition, characteristics, and classification of big data along with some discussions on cloud computing are introduced, and research challenges are investigated, with focus on scalability, availability, data integrity, data transformation, data quality, data heterogeneity, privacy, legal and regulatory issues, and governance.