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IET Collaborative Intelligent Manufacturing - John Wiley & Sons Inc | 2024 Impact Factor: 3.1 | Cite Score: 5.2 | Q2

iet-collaborative-intelligent-manufacturing.jpg

IET Collaborative Intelligent Manufacturing - John Wiley & Sons Inc | 2024 Impact Factor: 3.1 | Cite Score: 5.2 | Q2

  • About this Journal:
  • IET Collaborative Intelligent Manufacturing is an international open-access journal dedicated to the latest advancements and applications in intelligent manufacturing systems.Collaborative intelligent manufacturing finds its root in the need to develop efficient and adaptive production and distribution systems that can simultaneously meet the expectations of ever-changing market demands. A fully Gold Open Access journal, IET Collaborative Intelligent Manufacturing, aims to attract papers on methodologies and techniques for the application of intelligence, data science and emerging information and communication technologies in the design, modeling, simulation, planning, and optimisation of product, process, production, assembly, supply chain and logistics.
  • The journal focuses on collaborative technologies, artificial intelligence, data analytics, and automation that drive the transformation of manufacturing processes towards Industry 4.0 and beyond.
  • It serves as a platform for researchers, engineers, and industry practitioners to share novel theories, methodologies, and case studies that promote smart, connected, and adaptive production environments.
  • The journal encourages interdisciplinary research addressing challenges in digital manufacturing, robotics, cyber-physical systems, and human-machine collaboration.

  • Editor-in-Chief:  Liang Gao

  • Scope of the Journal:
  • Collaborative robotics and intelligent automation systems.
  • Industrial Internet of Things (IIoT) and cyber-physical manufacturing systems.
  • Artificial intelligence and machine learning in manufacturing.
  • Smart factories, digital twins, and predictive maintenance.
  • Human-robot collaboration and cognitive manufacturing systems.
  • Data-driven decision making and real-time production optimization.
  • Sustainable, flexible, and adaptive manufacturing processes.
  • Latest Research Topics for PhD in Artificial Intelligence
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  • Print ISSN:  25168398

    Electronic ISSN:  

  • Abstracting and Indexing:  SCOPUS, Emerging Sources Citation Index

  • Imapct Factor 2024:  3.1

  • Subject Area and Category:  Artificial Intelligence, Computer Science Applications, Hardware and Architecture

  • Publication Frequency:  

  • H Index:  17

  • Best Quartile:

    Q1:  

    Q2:  Artificial Intelligence

    Q3:  

    Q4:  

  • Cite Score:  5.2

  • SNIP:  0.939

  • Journal Rank(SJR):  0.693