Manuscript Full Title: The Use of Machine Learning in Intelligent
Predictive Maintenance for Cyber-Physical Systems
Abstract
Cyber-physical systems (CPS) are thought to be among industry
4.0’s primary enablers. CPS technology bridges the gap between the
physical and cyber worlds by integrating knowledge from several fields.
An important use of Industry 4.0 is predictive maintenance (PdM), which
can use a CPS-based strategy in intelligent operations to reduce machine
downtime and related expenses. This paper discusses the application of
machine learning to intelligent maintenance of Cyber Physical systems.
As CPS become more complex and widespread across industries, maintaining
their reliability and performance is critical. This paper further
describes how machine learning algorithm can be used to predict system
failure, develop repair plans and further highlights the potential
significant improvements in CPS maintenance strategies.
