Computational Intelligence based Optimization of Manufacturing Process for Sustainable Materials

Title: Computational Intelligence based Optimization of Manufacturing Process for Sustainable Materials
Author: , Deepak Sinwar, Vijander Singh, Vijaypal Singh Dhaka
ISBN: 103219104X / 9781032191041
Format: Hard Cover
Pages: 210
Publisher: CRC Press
Year: 2023
Availability: 2 to 3 weeks.

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The text comprehensively discusses computational models including artificial neural networks, agent-based models, and decision field theory for reliability engineering. It will serve as an ideal reference text for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, computer engineering, and materials science.

  • Discusses the development of sustainable materials using metaheuristic approaches.
  • Covers computational models such as agent-based models, ontology, and decision field theory for reliability engineering.
  • Presents swarm intelligence methods such as ant colony optimization, particle swarm optimization, and grey wolf optimization for solving the manufacturing process.
  • Include case studies for industrial optimizations.
  • Explores the use of computational optimization for reliability and maintainability theory.

The text covers swarm intelligence techniques including ant colony optimization, particle swarm optimization, cuckoo search, and genetic algorithms for solving complex industrial problems of the manufacturing industry as well as predicting reliability, maintainability, and availability of several industrial components.

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Preface

Chapter 1 : Introduction to Computational Intelligence for Sustainable Materials
Chapter 2 : Artificial Intelligence and IoT Assisted Sustainable Manufacturing for Industry 4.0
Chapter 3 : Image Analysis Approaches for the Fault Detection to the Quality Assurance in Manufacturing Industries
Chapter 4 : Manufacturing Data Performance Prediction and Optimization
Chapter 5 : Data-Driven Optimization on the Workability and Strength Properties of M-30 Grade Concrete using MOORA
Chapter 6 : Green Energy Harvesting using High Entropy Thermoelectric Alloys
Chapter 7 : Augmented and Virtual Reality Incorporation in the Manufacturing Industry 4.0
Chapter 8 : Modeling and Optimization of Process Parameter for Fatigue Strength Improvement by Selective Laser Melting of AlSi10Mg
Chapter 9 : Role of Artificial Intelligence in Apparel Industry in the context of Industry 4.0 and Industry 5.0
Chapter 10 : Swarm Intelligence-based Automotive Manufacturing

Index