The Inverse Gaussian Process as a Degradation Model

By Z. Ye, Nan Chen. Technometrics, 2014

511 citations recorded by the source corpus.

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How do heterogeneities in operating environments affect field failure predictions and test planning (2013, background): “In reliability engineering, the frailty is often called a random effect and also receives some applications, for example, see Stefanescu and Turnbull (2006), Lawless and Crowder (2010) and Ye and Chen (2014), among others.”
A Bidirectional LSTM Prognostics Method Under Multiple Operational Conditions (2019, background): “, physics-model-based approaches [8], statistical-based approaches [9]–[11], artificial intelligence (AI) approaches [12]–[14], and hybrid approaches [15].”
Stochastic modelling and analysis of degradation for highly reliable products (2015, background): “[49] for more details.”
Reliability Modeling for Systems with Multiple Degradation Processes Using Inverse Gaussian Process and Copulas (2014, background): “Ye andChen [6] attributed the reason of its unclear physical meanings to reliability engineers and prove that IG process is the limit of a compound Poisson process whose arrival rate goes to infinity while the jump size goes to zero in a certain way.”
Machinery health prognostics: A systematic review from data acquisition to RUL prediction (2018, background): “Based on the above study, Ye [275,276] and his co-authors [277] have conducted lots of work in this aspect.”