Component reliability plays a pivotal role in industrial systems, which are evolving with
larger complexity and higher dimensionality of data. It is insufficient to ensure reliability and …

The reliability estimation of engineered components is fundamental for many optimization
policies in a production process. The main goal of this paper is to study how machine …

To monitor the degradation status of units and prevent unexpected failures in engineering
systems, health index (HI)-based data fusion technologies have been rapidly developed by …

Prognostic and Health Management (PHM) systems are some of the main protagonists of
the Industry 4.0 revolution. Efficiently detecting whether an industrial component has …

Fault prognosis is mainly referred to the estimation of the operating time before a failure
occurs, which is vital for ensuring the stability, safety and long lifetime of degrading industrial …

Accurate prognostics are crucially important to prevent unexpected failures in industrial and
service systems. This process aims to monitor the degradation status of units and predict …

Reliability Analysis and Asset Management of Engineering Systems explains methods that
can be used to evaluate reliability and availability of complex systems, including simulation …

To perform the reliability analysis of complex and large-scale systems, Bayesian network
(BN) can be useful as it facilitates modelling the causal relationship between multiple types …

Reliability assessment refers to the process of evaluating reliability of components or
systems during their lifespan or prior to their implementation. In the manufacturing industry …

Reliability analysis of cyber-physical systems have benefitted substantially from the
introduction of a range of technology enablers. Internet of things (IoT), advanced computing …