Buch, Englisch, 430 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 674 g
Stochastic Models, Methods and Applications
Buch, Englisch, 430 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 674 g
Reihe: Springer Series in Reliability Engineering
ISBN: 978-3-662-57173-6
Verlag: Springer
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Zuverlässigkeitstechnik
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
- Mathematik | Informatik Mathematik Stochastik Stochastische Prozesse
- Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
Weitere Infos & Material
From the Contents: Part I Introduction, Basic Concepts and Preliminaries.- Overview.- Advances in Data-Driven Remaining Useful Life Prognosis.- Part II Remaining Useful Life Prognosis for Linear Stochastic Degrading Systems.- Part III Remaining Useful Life Prognosis for Nonlinear Stochastic Degrading Systems.- Part IV Applications of Prognostics in Decision Making.- Variable Cost-based Maintenance Model from Prognostic Information.
