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Full Description
Drawing on contributions from various manufacturing fields, this book offers a comprehensive perspective by combining theoretical concepts with practical applications. It emphasizes future developments, the integration of technologies, and the crucial role of humans in manufacturing companies.
Production Management, Manufacturing, and Process Control presents cutting-edge strategies and innovations for creating people-centered manufacturing processes. It explores how culture influences cognition and behavior, providing readers with valuable insights into relevant theories. This book also explores risk management, human performance improvement, and the current challenges in quality and information systems management. Sustainable global manufacturing practices that balance global market access with strong domestic engineering ecosystems are covered in detail, and this book also addresses the optimization of production processes, including the use of machine learning for fault diagnosis.
This is an ideal read and a valuable resource for students, graduates, teachers, researchers, and professionals in industrial management, business management, safety fields, manufacturing, risk management, and quality management.
Contents
1. Creativity of Employee 4.0: Individual and Collective Roles of Personal and Contextual Factors. 2. Navigating Skills Shortages: Bridging Human Factors and Fashion Practice Research for Collaborative Innovation in UK Fashion Manufacturing. 3. Cultural Obstacles to Servitization in Japanese Manufacturing Industries. 4. Obsolescence Risk Management for Long‑Life Defense Projects. 5. Quality Management Systems: Implementation Based on Opportunity Life Cycle. 6. Speed Up Medical Device Innovation: Combining Agile, User Experience, and Human Factors Methodologies. 7. User Context of Enterprise Information Systems for Manufacturing. 8. Advanced Engineering Management Based on Intersectional R&D Challenges on Education: A Case Study for Product Classifications on Shoring Trends. 9. An Optimization Study for the Milling Process of Inconel 601 Superalloy. 10. Empirical Study of Machine Learning for Intelligent Bearing Fault Diagnosis.
