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What Every Engineer Should Know about Risk Engineering and Management
Paperback
Series: What Every Engineer Should Know
Technology & EngineeringProbability & Statistics
ISBN13: 9781032439822
Publisher: CRC Press
Published: Jul 31 2023
Pages: 240
Weight: 0.83
Height: 0.56 Width: 6.14 Depth: 9.21
Language: English
Completely updated, this new edition uniquely explains how to assess and handle technical risk, schedule risk, and cost risk efficiently and effectively for complex systems that include Artificial Intelligence, Machine Learning, and Deep Learning. It enables engineering professionals to anticipate failures and highlight opportunities to turn failure into success through the systematic application of Risk Engineering. What Every Engineer Should Know About Risk Engineering and Management, Second Edition discusses Risk Engineering and how to deal with System Complexity and Engineering Dynamics, as it highlights how AI can present new and unique ways that failures can take place. The new edition extends the term Risk Engineering introduced by the first edition, to Complex Systems in the new edition. The book also relates Decision Tree which was explored in the first edition to Fault Diagnosis in the new edition and introduces new chapters on System Complexity, AI, and Causal Risk Assessment along with other chapter updates to make the book current.
Features
- Discusses Risk Engineering and how to deal with System Complexity and Engineering Dynamics
- Highlights how AI can present new and unique ways of failure that need to be addressed
- Extends the term Risk Engineering introduced by the first edition to Complex Systems in this new edition
- Relates Decision Tree which was explored in the first edition to Fault Diagnosis in the new edition
- Includes new chapters on System Complexity, AI, and Causal Risk Assessment along with other chapters being updated to make the book more current
The audience is the beginner with no background in Risk Engineering and can be used by new practitioners, undergraduates, and first-year graduate students.
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