Atsiliepimai
Aprašymas
Metal Additive Manufacturing: Recent Progress on Processing and Advancement presents an extensive exploration and in-depth analysis of the principles, techniques, advancements, and applications of metal additive manufacturing. It aims to bridge the knowledge gap between fundamental principles and the latest advancements in the field.
The book also covers simulation tools and techniques used to predict and optimize the outcomes of metal additive manufacturing processes.
Key features of the book include:
· A comprehensive discussion on optimizing process parameters, including techniques for enhancing production efficiency and product quality
· In-depth case studies showcasing real-world applications of metal additive manufacturing across various industries, such as aerospace, automotive, and healthcare
· Coverage of the integration of artificial intelligence, machine learning, and deep learning for process monitoring, control, and optimization in metal additive manufacturing
· A discussion of data-driven modelling for metal additive manufacturing, including predictive modelling using machine learning algorithms
· An explanation of sustainable manufacturing practices and the environmental benefits of metal additive manufacturing, including waste reduction and energy efficiency
The book is primarily written for senior undergraduates, graduate students, and academic researchers in manufacturing engineering, industrial engineering, production engineering, mechanical engineering, aerospace engineering, and materials science.
Metal Additive Manufacturing: Recent Progress on Processing and Advancement presents an extensive exploration and in-depth analysis of the principles, techniques, advancements, and applications of metal additive manufacturing. It aims to bridge the knowledge gap between fundamental principles and the latest advancements in the field.
The book also covers simulation tools and techniques used to predict and optimize the outcomes of metal additive manufacturing processes.
Key features of the book include:
· A comprehensive discussion on optimizing process parameters, including techniques for enhancing production efficiency and product quality
· In-depth case studies showcasing real-world applications of metal additive manufacturing across various industries, such as aerospace, automotive, and healthcare
· Coverage of the integration of artificial intelligence, machine learning, and deep learning for process monitoring, control, and optimization in metal additive manufacturing
· A discussion of data-driven modelling for metal additive manufacturing, including predictive modelling using machine learning algorithms
· An explanation of sustainable manufacturing practices and the environmental benefits of metal additive manufacturing, including waste reduction and energy efficiency
The book is primarily written for senior undergraduates, graduate students, and academic researchers in manufacturing engineering, industrial engineering, production engineering, mechanical engineering, aerospace engineering, and materials science.
Atsiliepimai