- 276 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
About this book
Artificial intelligence (AI) in the form of machine learning and nature-inspired optimization algorithms are vastly used in material science. These techniques improve many quality metrics, such as reliability and ergonomics.
This book highlights the recent challenges in this field and helps readers to understand the subject and develop future works. It reviews the latest methods and applications of AI in material science. It covers a wide range of topics, including Material processing; Properties prediction; Conventional machining, such as turning, boring, grinding, and milling; non-conventional machining, such as electrical discharge machining, electrochemical machining, laser machining, plasma machining, ultrasonic machining, chemical machining, and water-jet machining; Machine tools, such as programming, design, and maintenance. AI techniques reviewed in the book include Machine learning, Fuzzy logic, Genetic algorithms, Particle swarm optimization, Cuckoo search, Grey wolf optimizer, and Ant colony optimization.
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Table of contents
- Cover Page
- Title Page
- Copyright Page
- Foreword
- Preface
- Contents
- 1 Artificial Intelligence Computational Intelligence and Opportunities
- 2 Urban Heat Island (UHI) Effect and its Mitigation Schemes in Built-up Areas with Artificial Intelligence Techniques
- 3 The Role of Artificial Intelligence in Advancing the Digitalization of Machining Processes
- 4 Evaluating Process Variability through the Implementation of Fuzzy Triangular Distribution in Dynamic Value Stream Mapping
- 5 Innovative Electrode Tool Manufacturing Methods for Electrode Discharge Machining
- 6 Implementation of AI in Manufacturing Industries: A Case Study
- 7 Constructional and Technological Approach to Improve the Mechanical Performance of Diesel Engines
- 8 Artificial Intelligence and Product Innovation: Expectations and Concerns
- 9 Artificial Intelligence and Game Theory in the Intensive Care Units
- 10 Application of AI in Material Science to Accelerate Material Innovation
- 11 Contributions of Machine Learning to Material Science: A Short Overview
- 12 The Use of Metaheuristics in Material Science: A Short Overview
- 13 Advances in Artificial Intelligence—Will Artificial Intelligence Support Transfusion Medicine Knowledge and Technology?
- Index
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