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Proceedings ArticleDOI

Big data challenges and opportunities in the hype of Industry 4.0

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TLDR
Challenges and opportunities of industrial big data are revealed in the context of Industry 4.0 with a different perspective to help the researchers to threshold these modern systems of Industry 5.0 in designing big data algorithms and techniques.
Abstract
The world of industrial automation technology is at the outset of a new era of innovation with the hype of Industry 4.0. Global modern industrial system converges the power of machines, computing, analytics, connectivity, cyber-physical systems, Internet of things, automation, cloud system and data exchange. Industry 4.0 is a revolution towards the digital world of digital factories and smart products. Big data is an integration of multi-disciplinary technologies and facilitates customer by bringing incredible services to a click. Internet of things connected the world of machines by adding communication capability in every device to connect to other devices or access the Internet. Big Data inflict a new horizon of opportunities in these systems. In this paper, challenges and opportunities of industrial big data are revealed in the context of Industry 4.0 with a different perspective. The current study helps the researchers to threshold these modern systems of Industry 4.0 in designing big data algorithms and techniques.

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Citations
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Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies

TL;DR: In this paper, the authors identify key challenges to Industry 4.0 initiatives and analyze the identified key challenges in order to prioritize them for effective Industry4.0 concepts for supply chain sustainability in emerging economies.
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Assessing challenges for implementing Industry 4.0: Implications for process safety and environmental protection

TL;DR: In this paper, the authors identified a set of challenges (framework) for implementing Industry 4.0 in manufacturing industries and evaluated them using a novel multi-criteria decision-making method named Best-Worst method (BWM).
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Requirements of the Smart Factory System: A Survey and Perspective

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A predictive model for the maintenance of industrial machinery in the context of industry 4.0

TL;DR: A predictive model based on a Bayesian Filter, a tool from the Machine Learning field, to estimate and predict the gradual degradation of such machinery, permitting the operators to make informed decisions regarding maintenance operations is described.
References
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Industrie 4.0: Hit or Hype? [Industry Forum]

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Journal ArticleDOI

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