Machine Learning for Industry 4.0 [From the Guest Editors]

Mengchu Zhou, Yan Qiao, Bin Liu, Birgit Vogel-Heuser, Heeyoung Kim

Research output: Contribution to journalReview articlepeer-review


The Fourth Industrial Revolution, also known as Industry 4.0, marks the technological shift from traditional manufacturing systems to smart cyberphysical systems. It leads to an improvement in overall productivity and a reduction in environmental impact and promotes sustainable economic development. Industry 4.0 has been driven by emerging technologies such as the Internet of Things (IoT), also called the Industrial Internet of Things; digital twins; artificial intelligence; cloud computing; and edge/fog computing [1], [2], [3], [4], [5]. It is a hot topic in both academia and industry. The implementation of IoT connects physical assets to cybernetworks and captures a significant amount of data. These data, often 'big', are then fed to AI-based mission-critical systems to perform production monitoring, quality inspection, fault root cause analysis, quality prediction, and process control. The proper adoption of relevant Industry 4.0 technologies should lead to significant efficiency improvements and cost reductions in various industrial sectors.

Original languageEnglish (US)
Pages (from-to)8-9
Number of pages2
JournalIEEE Robotics and Automation Magazine
Issue number2
StatePublished - Jun 1 2023

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


Dive into the research topics of 'Machine Learning for Industry 4.0 [From the Guest Editors]'. Together they form a unique fingerprint.

Cite this