Engineering design under uncertainty and health prognostics
By: Hu, Chao.
Contributor(s): Youn, Byeng D | Wang, Pingfeng.
Series: Springer series in reliability engineering / edited by Hoang Pham. Publisher: Switerland Springer 2019Description: xi, 342p.ISBN: 9783319925721.Subject(s): Health managementDDC classification: 621.381028 | H86e Summary: This book presents state-of-the-art probabilistic methods for the reliability analysis and design of engineering products and processes. It seeks to facilitate practical application of probabilistic analysis and design by providing an authoritative, in-depth, and practical description of what probabilistic analysis and design is and how it can be implemented. The text is packed with many practical engineering examples (e.g., electric power transmission systems, aircraft power generating systems, and mechanical transmission systems) and exercise problems. It is an up-to-date, fully illustrated reference suitable for both undergraduate and graduate engineering students, researchers, and professional engineers who are interested in exploring the fundamentals, implementation, and applications of probabilistic analysis and design methods.| Item type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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Books
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PK Kelkar Library, IIT Kanpur | General Stacks | 621.381028 H86e (Browse shelf) | Available | A183987 |
This book presents state-of-the-art probabilistic methods for the reliability analysis and design of engineering products and processes. It seeks to facilitate practical application of probabilistic analysis and design by providing an authoritative, in-depth, and practical description of what probabilistic analysis and design is and how it can be implemented. The text is packed with many practical engineering examples (e.g., electric power transmission systems, aircraft power generating systems, and mechanical transmission systems) and exercise problems. It is an up-to-date, fully illustrated reference suitable for both undergraduate and graduate engineering students, researchers, and professional engineers who are interested in exploring the fundamentals, implementation, and applications of probabilistic analysis and design methods.
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