@article{0ca3dcc2c88c4caeab721ba903fb971d,
title = "Residual-life distributions from component degradation signals: A Bayesian approach",
abstract = "Real-time condition monitoring is becoming an important tool in maintenance decision-making. Condition monitoring is the process of collecting real-time sensor information from a functioning device in order to reason about the health of the device. To make effective use of condition information, it is useful to characterize a device degradation signal, a quantity computed from condition information that captures the current state of the device and provides information on how that condition is likely to evolve in the future. If properly modeled, the degradation signal can be used to compute a residual-life distribution for the device being monitored, which can then be used in decision models. In this work, we develop Bayesian updating methods that use real-time condition monitoring information to update the stochastic parameters of exponential degradation models. We use these degradation models to develop a closed-form residual-life distribution for the monitored device. Finally, we apply these degradation and residual-life models to degradation signals obtained through the accelerated testing of bearings.",
author = "Gebraeel, {Nagi Z.} and Lawley, {Mark A.} and Rong Li and Ryan, {Jennifer K.}",
note = "Funding Information: Mark Lawley is an Associate Professor of Industrial Engineering at Purdue University. He has held manufacturing engineering positions with the Westinghouse Electric Corporation and Emerson Electric Company. In these positions, he worked on projects involving tooling design, quality control, robotics, metrology, programmable control, CNC, and simulation technologies. He is the author of over 50 technical papers in manufacturing systems design and control and has won two best paper awards. He is an Associate Editor for IEEE Transactions on Automation Science and Engineering. His research has been supported by the National Science Foundation, Union Pacific, Consilium Software, and General Motors. He received a Ph.D. in Mechanical Engineering from the University of Illinois at Urbana Champaign in 1995 and is a registered professional engineer in the State of Alabama. Funding Information: Jennifer K. Ryan is an Assistant Professor in the Department of Management at the Mendoza College of Business at the University of Notre Dame. She has been a faculty member at Notre Dame since August 2004. Previously, she was a faculty member in the School of Industrial Engineering at Purdue University. She holds a B.A. in Mathematics and the Social Sciences from Dartmouth College (1990), and an M.S. (1995) and Ph.D. (1997) from the Department of Industrial Engineering and Management Sciences at Northwestern University. She has held positions with Sears, Roebuck and Co., Tucker Alan, Inc., American Medical Association and Lewin-ICF. Her current research interests are in the area of inventory and supply chain management. She is particularly interested in measuring the value of information sharing and coordination efforts in supply chain management. In addition, her research considers the impact of product variety on inventory and supply chain management. She has received several National Science Foundation grants, including an NSF Career grant.",
year = "2005",
month = jun,
doi = "10.1080/07408170590929018",
language = "English (US)",
volume = "37",
pages = "543--557",
journal = "IISE Transactions",
issn = "2472-5854",
publisher = "Taylor and Francis Ltd.",
number = "6",
}