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Item #:
210321831
Reliability Analysis and Modeling for Complex Systems (Advances in Reliability Science)
Item #:
210321831
XAF 129339
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This book bridges theory and practice, offering practical solutions for professionals navigating the intricate world of reliability engineering.
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What Stands Out
In-depth Insights
Explores advanced reliability science concepts, offering comprehensive insights for researchers and engineers dealing with complex systems, ensuring they tackle reliability issues effectively.
Practical Applications
Provides real-world applications and case studies, enabling professionals to apply theoretical models directly to industry challenges, enhancing problem-solving capabilities.
Latest Research
Incorporates cutting-edge research and methodologies, keeping readers updated on the most current trends and techniques in reliability analysis, ensuring relevance in a rapidly evolving field.
Product Details
| Publisher | Elsevier |
| Publication date | November 21, 2025 |
| Edition | 1st |
| Language | English |
| Print length | 384 pages |
| ISBN-10 | 0443336555 |
| ISBN-13 | 978-0443336553 |
| Item Weight | 1.38 pounds (630 grams) |
| Dimensions | 5.98 x 0.91 x 9.02 inches (15.2 x 2.3 x 22.9 cm) |
Who Should Buy?
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Engineers and Analysts
Ideal for professionals focusing on reliability engineering, improving system performance through advanced modeling techniques outlined in the book.
-
Academics and Researchers
Useful for students and researchers looking for in-depth knowledge on reliability analysis methodologies for complex systems.
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Quality Control Professionals
Beneficial for quality managers emphasizing product reliability and system robustness as part of their quality assurance processes.
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General Audience
Not suitable for casual readers; content is technical and requires background knowledge in reliability science.
Product Description
Reliability Analysis and Modeling for Complex Systems (Advances in Reliability Science)
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Features & Benefits
- Essential resource for engineers and technologists tackling modern challenges.
- Focuses on reliability assessment methods for complex systems like autonomous vehicles.
- Covers advanced probabilistic modeling and analysis techniques.
- Offers interdisciplinary perspectives, including human factors and cyber-physical systems.
- Includes real-world case studies for practical application of reliability analysis.
- Equips readers to manage dependability in today's interconnected technological landscape.
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