Decision-Making Models and Applications in Manufacturing Environments - Rilegato

Rilegato

ISBN 10: 1774913550 ISBN 13: 9781774913550

Casa editrice: Apple Academic Press, 2024

Riassunto

Multi-criteria decision-making (MCDM) has gained vast popularity for its ability to help make decisions in the presence of various similar and conflicting choices.This new volume applies the MCDM theory to solving problems and challenges in manufacturing environments. It discusses using MCDM computational methods to evaluate and select the most optimal solution or method for real-world, real-time manufacutring engineering issues. It details the decision-making process in relation materials selection; identification, assessment, and evaluation of risk; sustainability assessment; selection of green suppliers; and more.

The chapter authors demonstrate the application of myriad MCDM techniques in decision-making, including MADM (multiple attribute decision-making), DEA (data envelopment analysis), fuzzy TOPSIS (technique for order preference by similarities to ideal solution), fuzzy-VIKOR (multicriteria optimization and compromise solution); MOORA (multi-objective optimization on the basis of ratio analysis), EWM (entropy weight method), (AHP) analytic hierarchy process, TODIM (TOmada de Decisao Interativa Multicriterio), and others. The volume illustrates these MCDM models in several industries and industrial processes, including for experimental analysis and optimization of drilling of glass fiber reinforced plastic, in the textile industries, for selection of refrigerants for domestic applications, and others.

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Informazioni sull?autore

Pushpdant Jain, PhD, is an Assistant Professor in the School of Mechanical Engineering at VIT Bhopal University, India. Prior to academia, he served in industry for six years. He has published research papers in international peer-reviewed journals and has published several book chapters. Dr. Jain has participated in international conferences, is an active member of the European Society of Bio-Mechanics and life member of the International Association of Engineers, Indian Institution of Industrial Engineering, and Indian Society for Technical Education. He was named Research Scholar of the Year (2018) by NIT Rourkela for his PhD work.

Kumar Abhishek, PhD, is an Assistant Professor in the Mechanical and Aero-Space Engineering Department at the National Institute of Infrastructure, Technology, Research and Management, Ahmedabad, India. His area of research mainly focuses on manufacturing and industrial engineering, modeling and optimization of production processes, and composite machining. He has many publications in reputed journals and international conference publications to his credit. He organizes a workshop every consecutive year titled MOOMESA―Multi Objective Optimization Methods for Engineering and Scientific Applications.

Prasenjit Chatterjee, PhD, is Dean (Research and Consultancy) at the MCKV Institute of Engineering, West Bengal, India. He has over 100 research papers published in international journals and peer-reviewed conferences. He has authored and edited more than 15 books on intelligent decision-making, supply chain management, optimization techniques, risk, and sustainability modelling. Dr. Chatterjee is the Editor-in-Chief of the Journal of Decision Analytics and Intelligent Computing as well as a series editor for several book series. Dr. Chatterjee is one of the developers of two multiple-criteria decision-making methods: Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) and Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (RAFSI).

Dettagli dell'edizione

• Editore: Apple Academic Press
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 10: 1774913550
• ISBN 13: 9781774913550
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 496
• Redattore: Jain Pushpdant, Abhishek Kumar, Chatterjee Prasenjit
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile