Collaborative Data Analytics for Industry 4.0: Challenges, Opportunities and Models

Author(s):  
Sanja Lazarova-Molnar ◽  
Nader Mohamed ◽  
Jameela Al-Jaroodi
Keyword(s):  
Author(s):  
Renan Bonnard ◽  
Márcio Da Silva Arantes ◽  
Rodolfo Lorbieski ◽  
Kléber Magno Maciel Vieira ◽  
Marcelo Canzian Nunes

2022 ◽  
pp. 406-428
Author(s):  
Lejla Banjanović-Mehmedović ◽  
Fahrudin Mehmedović

Intelligent manufacturing plays an important role in Industry 4.0. Key technologies such as artificial intelligence (AI), big data analytics (BDA), the internet of things (IoT), cyber-physical systems (CPSs), and cloud computing enable intelligent manufacturing systems (IMS). Artificial intelligence (AI) plays an essential role in IMS by providing typical features such as learning, reasoning, acting, modeling, intelligent interconnecting, and intelligent decision making. Artificial intelligence's impact on manufacturing is involved in Industry 4.0 through big data analytics, predictive maintenance, data-driven system modeling, control and optimization, human-robot collaboration, and smart machine communication. The recent advances in machine and deep learning algorithms combined with powerful computational hardware have opened new possibilities for technological progress in manufacturing, which led to improving and optimizing any business model.


2020 ◽  
Vol 25 (6) ◽  
pp. 2103-2104
Author(s):  
Jose Antonio Marmolejo-Saucedo ◽  
Félix Martínez-Rios ◽  
Roman Rodriguez-Aguilar

2020 ◽  
Author(s):  
Hendro Wicaksono

The presentation introduces the technologies associated with the fourth industrial revolution which rely on the concept of artificial intelligence. Data is the basis of functioning artificial intelligence technologies. The presentation also explains how data can revolutionize the business by providing global access to physical products through an industry 4.0 ecosystem. The ecosystem contains four pillars: smart product, smart process, smart resources (smart PPR), and data-driven services. Through these four pillars, the industry 4.0 can be implemented in different sectors. The presentation also provides some insights on the roles of linked data (knowledge graph) for data integration, data analytics, and machine learning in industry 4.0 ecosystem. Project examples in smart city, healthcare, and agriculture sectors are also described. Finally, the presentation discusses the implications of the introduced concepts on the Indonesian context.


Author(s):  
Soufhwee Abdul Rahman ◽  
◽  
Effendi Mohamad ◽  
Azrul Abdul Rahman ◽  
Ihwan Hamdala ◽  
...  

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