Multi-Attribute Decision-Making in Industrial Engineering

Master the complexities of modern engineering management with this practical guide to multi-attribute decision-making, providing the advanced models and multi-criteria frameworks needed to resolve conflicting objectives and optimize industrial outcomes.

Multi-attribute decision-making (MADM) is a foundational area within contemporary decision science. Its ­theoretical frameworks and methodological approaches have been widely applied across disciplines such as industrial engineering, military affairs, economics, and management. This book provides a comprehensive and practical guide to this critical area in modern engineering management. Covering topics such as decision theory, multi-criteria analysis, and advanced decision-making models, the book explores how MADM techniques can be applied to solve real-world problems related to production planning, supply chain management, quality control, and operational efficiency. Whether dealing with conflicting objectives, limited resources, or complex trade-offs, this book serves as a valuable resource to enhance decision-making skills and optimize outcomes in industrial processes. With a clear focus on practical applications, it bridges the gap between theory and practice, making it ideal for both academic and professional use in the fields of industrial engineering and operations management.

Readers will find the volume:

• Covers key Multiple Attribute Decision-Making methods like AHP, TOPSIS, and VIKOR with real-world industrial applications;
• Provides step-by-step examples, making complex concepts easy to understand and apply;
• Enhances productivity and accuracy in process optimization and resource allocation;
• Includes case studies to bridge theory and practical implementation.

Audience

Academics, researchers, industrial engineers, operations researchers, supply chain analysts, project managers, and decision scientists who seek to enhance decision-making processes using structured multi-attribute methodologies.

Pranav Charkha, PhD is a Professor in the School of Engineering and Technology at Pimpri Chinchwad University, Pune, Maharashtra, India. He has published more than 40 research papers in international journals, five book chapters, four books, and five copyrights. His research focuses on supply chain management, additive manufacturing, and world-class manufacturing for Industry 4.0.

Vijayshri Mahobiya, PhD is the Head of the Mechanical Engineering Department at the Wainganaga College of Engineering and Management, Nagpur, Maharashtra, India. She has authored numerous papers in reputed international journals and holds two patents, showcasing her contributions to practical advancements in the field. Her research focus lies in the application of lean manufacturing principles to optimize testing laboratories.

Santosh Jaju, PhD is a Professor in the Department of Mechanical Engineering at the G.H. Raisoni College of Engineering, Nagpur, Maharashtra, India, with more than 22 years of teaching experience. He has to his credit more than 100 research papers published in national and international journals and conferences, one book, and six book chapters. His research focuses on quality cost, service quality, lean manufacturing, productivity improvement techniques, and industrial engineering.

Vinit Gupta, PhD is an Associate Professor at P.P. Savani University, Surat, Gujarat, India, with more than 14 years of experience. He has contributed several technical papers to prestigious peer-reviewed journals, published a book and several other book chapters, and is an active consultant to nearby industries. His major research areas include materials and material applications and mechanism design and control.

Sandip Kunar, PhD is an Associate Professor in the Department of Mechanical Engineering at Aditya Engineering College, Andhra Pradesh, India. He has published more than 60 research papers in various reputed international journals, national and international conference proceedings, 60 book chapters, 20 books, and five patents. His research interests include non-conventional machining processes, micromachining processes, advanced manufacturing technology, and industrial engineering.