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.
Section I. Advance Trends in Industrial Engineering. 1: Literature Review on Balanced and Unbalanced Industrial Assignment Problems. 2. Systems for Detecting Intruders In Internet of Things Environments Using The Cloud: A Survey. 3. Utilizing Advanced Machine Learning to Improve Network Security in Industries Against Changing Cyber Threats. 4. Big Data Analytics and FinTech (FT) in BFSI Industries: Emerging Trends. 5. Internet of Things Products: Management of Youth’s Purchase Intention. 6. Artificial Intelligence and its Futuristic Approach in Industries. 7. Analysis On A Resource –Based Population Model With Caputo Fractional Derivative. 8. Selection of Teaching Pedagogy for Engineering Classroom Learning from Instructor’s Viewpoints using Fuzzy TOPSIS approach: A Case Study of Selected Higher Education Institutions in Northern India. Section II: Advance Trends in Industrial Management. 9. A bibliometric analysis and management of big data and machine learning research: current trends and future directions. 10. Water Scarcity And Its Management Strategies In India. 11. Group Search Optimization and Neural Network Based Security and Management of Digital Data. 12. Building A Smart Contract Based Escrow Platform for Management of Crowd-Funding and Public/Private Tenders on Block-Chain. 13. Analysis of Water Quality for Sustainable Resource Management Using Machine Learning Techniques. 14. Management of Crop Recommendation System using Predictive Analytics. 15. Analysis of Creditworthiness and Risk Assessment Management for Enterprises Using Machine Learning. 16. Intersection of Artificial Intelligence in Agriculture Sector Management: A Critical Analysis. 17. A Study on Management of Employee Perception Towards The Role of Artificial Intelligence Tools in Promoting Employee Engagement: An Empirical Study of the Banking Sector in Kumaun Region.
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