Si X.-S., Zhang Z.-X., Hu C.-H. Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications

Springer, 2017. — 436 p. — (Springer Series in Reliability Engineering). — ISBN 978-3-662-54028-2.This book introduces data-driven remaining useful life prognosis techniques, and shows how to utilize the condition monitoring data to predict the remaining useful life of stochastic degrading systems and to schedule maintenance and logistics plans. It is also the first book that describes the basic data-driven remaining useful life prognosis theory systematically and in detail.
The emphasis of the book is on the stochastic models, methods and applications employed in remaining useful life prognosis. It includes a wealth of degradation monitoring experiment data, practical prognosis methods for remaining useful life in various cases, and a series of applications incorporated into prognostic information in decision-making, such as maintenance-related decisions and ordering spare parts. It also highlights the latest advances in data-driven remaining useful life prognosis techniques, especially in the contexts of adaptive prognosis for linear stochastic degrading systems, nonlinear degradation modeling based prognosis, residual storage life prognosis, and prognostic information-based decision-making.Advances in Data-Driven RUL Prognosis Techniques
Planning Repeated Degradation Testing for Degrading Products
Specifying Measurement Errors for Required Lifetime Estimation Performance
An Adaptive Remaining Useful Life Estimation Approach with a Recursive Filter
An Exact and Closed-Form Solution to Degradation Path-Dependent RUL Estimation
Estimating RUL with Three-Source Variability in Degradation Modeling
RUL Estimation Based on a Nonlinear Diffusion Degradation Process
Prognostics for Age- and State-Dependent Nonlinear Degrading Systems
Adaptive Prognostic Approach via Nonlinear Degradation Modeling
Prognostics for Hidden and Age-Dependent Nonlinear Degrading Systems
Prognostics for Nonlinear Degrading Systems with Three-Source Variability
RSL Prediction Approach for Systems with Operation State Switches
Reliability Estimation Approach for PMS
A Real-Time Variable Cost-Based Maintenance Model
An Adaptive Spare Parts Demand Forecasting Method Based on Degradation Modeling
Variable Cost-Based Maintenance and Inventory Model