… In this chapter, Machine Learning solutions for Cyber-Physical Systems (CPSs) in a Smart
Factory are outlined using productions plants as an example. The increasing complexity of …

… While existing frameworks for process monitoring currently only consider discrete IoT sensors
deployed in the smart factory [26], we propose to extend the process analysis with video-…

… due to high complexity and uncertainty of smart factory. Thus, it is … smart factory and systematic
management is emphasized, there is insufficient research. In this paper, machine learning …

… Weka machine learning program. Hence, the honeypot combined machine learning model
… to be highly feasible to apply in the security network of smart factory to detect botnet attacks. …

… The steel plate factory process usually contains seven steps to produce a steel plate using
a … The steel plate smart factory in this paper has only one rolling mill stand, which performs …

… In the machine learning approach for RTS, a set of training … However, the machine learning
approach employed for … RTS for smart factories by employing deep learning algorithms. …

… Inspired by these challenges, this research provides a hybrid machine learning approach
combining unsupervised learning and semi-supervised learning. The approach and result in …

… found four smart factory … smart factories and offers HMI recommendations for users, designers,
and researchers. These findings provide insights into the design of HMIs in smart factories. …

… , machine learning is seeing adoption in many ways and is now playing a central role in smart
Factory predictive … and supervised machine learning are used in predictive maintenance: …

… smart factory. However, most firms still lack insight into the challenges and resources for
implementing smart factory… that have been done for smart factory, and further provides guidance …