Proceedings ArticleDOI
Big data challenges and opportunities in the hype of Industry 4.0
Maqbool Khan,Xiaotong Wu,Xiaolong Xu,Wanchun Dou +3 more
- pp 1-6
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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.read more
Citations
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Journal ArticleDOI
Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies
Sunil Luthra,Sachin Kumar Mangla +1 more
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.
Journal ArticleDOI
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).
Journal ArticleDOI
A Survey on Big Data Market: Pricing, Trading and Protection
TL;DR: This paper study a variety of data pricing models, categorize them into different groups, and conduct a comprehensive comparison of the pros and cons of these models, and focuses on the design of data trading platforms and schemes, supporting efficient, secure, and privacy-preserving data trading.
Journal ArticleDOI
Requirements of the Smart Factory System: A Survey and Perspective
TL;DR: In this paper, the authors highlight the perspectives that shape the smart factory and suggest approaches and technical support to enable the realization of those perspectives, and suggest a framework to analyze existing research and investigate the elements and features of smart factory systems.
Journal ArticleDOI
A predictive model for the maintenance of industrial machinery in the context of industry 4.0
Jose-Raul Ruiz-Sarmiento,Javier Monroy,Francisco-Angel Moreno,Cipriano Galindo,Jose-Maria Bonelo,Javier Gonzalez-Jimenez +5 more
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.
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TL;DR: In this article, the authors provide easy-to-understand access to the core ideas of Industrie 4.0 and describe the basic industrial requirements that need to be fulfilled for its success.
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