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Advanced Analytics for Industry 4.0 - Ali Soofastaei

Advanced Analytics for Industry 4.0

Traditional Industries

(Autor)

Buch | Hardcover
332 Seiten
2025
CRC Press (Verlag)
978-1-032-03344-0 (ISBN)
CHF 209,45 inkl. MwSt
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This volume covers the analytics revolution in Industry 4.0 for the mother industries like mining, oil & gas, steel and so forth. It fousses on use of advanced analytics and artificial intelligence to improve the business decisions aimed to increase the quality and quantity of mother industries' products.
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.

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.

Chapter 1: Navigating the Fourth Industrial Revolution: The Advent of Advanced Analytics in Traditional Industries Chapter 2: Transforming Mining Operations: Harnessing Advanced Analytics for Optimal Decision-Making Chapter 3: Designing Intelligence: Harnessing Soft Sensors and Advanced Analytics in Petroleum Refining for Industry 4.0 Chapter 4: Harnessing the Convergence of Information Technology and Operational Technology for Digital Transformation: An Integrated Framework for Effective Project Management, Skill Development, Team Coordination, and Collaboration in Manufacturing Industry Chapter 5: Harnessing Industrial Internet of Things: Enabling Artificial Intelligence and Machine Learning for Optimized Industrial and Manufacturing Processes Chapter 6: Digitizing the Palate: Exploring Opportunities for Digital Transformation in the Food Industry Chapter 7: Constructing Tomorrow: Exploring the Future of Construction in the Era of Industry 4.0 Chapter 8: Leveraging Advanced Analytics for Transforming Logistics: The Road to Logistics 4.0 Chapter 9: Revolutionizing Chemical Engineering 4.0: Artificial Intelligence Innovations and Machine Learning Chapter 10: Harvesting Tomorrow: The Future of Agriculture in Industry 4.0 Chapter 11: Artificial Intelligence in Insurance: Transforming Risk Management and Customer Experience

Erscheinungsdatum
Zusatzinfo 16 Tables, black and white; 61 Line drawings, black and white; 18 Halftones, black and white; 79 Illustrations, black and white
Verlagsort London
Sprache englisch
Maße 156 x 234 mm
Gewicht 720 g
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Technik Bauwesen
Technik Elektrotechnik / Energietechnik
ISBN-10 1-032-03344-4 / 1032033444
ISBN-13 978-1-032-03344-0 / 9781032033440
Zustand Neuware
Informationen gemäß Produktsicherheitsverordnung (GPSR)
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