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Emerging trends in Industrial Engineering and Management (IEM) refer to the new and transformative developments, practices, and technologies that are currently gaining prominence in the field of industrial engineering and management. Trends in Industrial Engineering and Management can encompasses a wide range of topics such as utilization of Industry 4.0 strategies like Industrial Internet of Things, artificial Intelligence, theoretical, numerical, computational approaches to model the methods and process of IEM.
This book:
Provides a comprehensive discussion of industrial engineering and management. Includes principles of continuous improvement, encouraging readers to adopt a mind-set of on-going optimization and innovation in industrial engineering and management. Presents multi-objective optimization, stochastic optimization, and metaheuristic optimization algorithms for solving complex optimization problems in industrial engineering. Aligns with the needs of various industries, addressing specific challenges faced by manufacturing, healthcare, logistics, service, and other sectors. Highlights the importance of using digital technological tools like the Internet of Things, Industrial Internet of Things, big data, and artificial intelligence in practices of industrial management to enhance competitiveness, decision-making, and operations efficiency.
It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of industrial engineering, production engineering, mechanical engineering, operation management, industrial management, quality engineering, and engineering management.
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Emerging trends in Industrial Engineering and Management (IEM) refer to the new and transformative developments, practices, and technologies that are currently gaining prominence in the field of industrial engineering and management. Trends in Industrial Engineering and Management can encompasses a wide range of topics such as utilization of Industry 4.0 strategies like Industrial Internet of Things, artificial Intelligence, theoretical, numerical, computational approaches to model the methods and process of IEM.
This book:
Provides a comprehensive discussion of industrial engineering and management. Includes principles of continuous improvement, encouraging readers to adopt a mind-set of on-going optimization and innovation in industrial engineering and management. Presents multi-objective optimization, stochastic optimization, and metaheuristic optimization algorithms for solving complex optimization problems in industrial engineering. Aligns with the needs of various industries, addressing specific challenges faced by manufacturing, healthcare, logistics, service, and other sectors. Highlights the importance of using digital technological tools like the Internet of Things, Industrial Internet of Things, big data, and artificial intelligence in practices of industrial management to enhance competitiveness, decision-making, and operations efficiency.
It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of industrial engineering, production engineering, mechanical engineering, operation management, industrial management, quality engineering, and engineering management.