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What Every Engineer Should Know About Risk Engineering and Management

By: John X. Wang (Author)

Ksh 6,480.00
Format :

Format(s): DRM PDF

ISBN-13: 9781000906578

Publisher: CRC Press

Imprint: CRC Press

Publication Date: July 31st, 2023

Language: English

Pages: 240

Physical Edition EAN: 9781032442105

More ebooks on Risk assessment

  • Description

  • Author Bio

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 "e;Risk Engineering"e; 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. FeaturesDiscusses Risk Engineering and how to deal with System Complexity and Engineering DynamicsHighlights how AI can present new and unique ways of failure that need to be addressedExtends the term "e;Risk Engineering"e; introduced by the first edition to Complex Systems in this new editionRelates Decision Tree which was explored in the first edition to Fault Diagnosis in the new editionIncludes new chapters on System Complexity, AI, and Causal Risk Assessment along with other chapters being updated to make the book more currentThe 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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