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Advanced Analytics for Industry 4.0

Traditional Industries

Ali Soofastaei (The University of Queensland, Australia)

$252

Hardback

Forthcoming
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English
CRC Press
17 July 2025
The evolution of modern technology has affected all the industry dimensions. Mother industries play a critical role in providing the precursor materials for other industries, and a small improvement in these can make a big change in others. This book covers the analytics revolution in Industry 4.0 for the mother industries, such as mining, oil and gas, and steel. It focuses on the use of advanced analytics and artificial intelligence to improve the business decisions aimed at increasing the quality and quantity of mother industries' products. It helps to design and implement their digital transformation strategies in these industries.

Key Features:

Provides a concise overview of state of the art for mother industries' executives and managers. Highlights and describes critical opportunity areas for industry operations optimization. Explains how to implement advanced data analytics through case studies and examples. Provides approaches and methods to improve data-driven decision-making. Brings experience and learning in digital transformation from adjacent sectors.

This book is aimed at researchers, professionals, and graduate students in data science, manufacturing, automation, and computer engineering.
By:  
Imprint:   CRC Press
Country of Publication:   United Kingdom
Dimensions:   Height: 234mm,  Width: 156mm, 
ISBN:   9781032033440
ISBN 10:   1032033444
Pages:   332
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Hardback
Publisher's Status:   Forthcoming

Ali Soofastaei is the global projects leader at Vale Artificial Intelligence Centre.Vale is a multinational corporation engaged in metals and mining. It is one of the world’s foremost producers of iron ore and the largest producer of nickel. Dr. Soofastaei leads innovative industrial projects in artificial intelligence (AI) applications to improve safety, productivity, and energy efficiency and reduce maintenance costs. He completed his Ph.D. at the University of Queensland in the field of AI applications in mining engineering, where he led a revolution in the use of deep learning and AI methods to increase energy efficiency, reduce operation and maintenance costs, and reduce greenhouse gas emissions in surface mines.

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