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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.
Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods presents the concepts and details of applications of MADM methods. A range of methods are covered including Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VIšekriterijumsko KOmpromisno Rangiranje (VIKOR), Data Envelopment Analysis (DEA), Preference Ranking METHod for Enrichment Evaluations (PROMETHEE), ELimination Et Choix Traduisant la Realité (ELECTRE), COmplex PRoportional ASsessment (COPRAS), Grey Relational Analysis (GRA), UTility Additive (UTA), and Ordered Weighted Averaging (OWA). The existing MADM methods are improved upon and three novel multiple attribute decision making methods for solving the decision making problems of the manufacturing environment are proposed. The concept of integrated weights is introduced in the proposed subjective and objective integrated weights (SOIW) method and the weighted Euclidean distance based approach (WEDBA) to consider both the decision maker’s subjective preferences as well as the distribution of the attributes data of the decision matrix. These methods, which use fuzzy logic to convert the qualitative attributes into the quantitative attributes, are supported by various real-world application examples. Also, computer codes for AHP, TOPSIS, DEA, PROMETHEE, ELECTRE, COPRAS, and SOIW methods are included. This comprehensive coverage makes Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods a key reference for the designers, manufacturing engineers, practitioners, managers, institutes involved in both design and manufacturing related projects. It is also an ideal study resource for applied research workers, academicians, and students in mechanical and industrial engineering.
This book introduces the step-by-step processes involved in using MCDM methods, starting from problem formulation, model development, and criteria weighting to the final ranking of the alternatives. The authors explain the different MCDM methods that can be used in specific manufacturing environments. The book explains the conceptual frameworks of how these methods are applied with special focus on their applicability and usefulness. The authors begin with an introduction to multi-criteria decision-making, followed by explanations of 29 MCDM methods and their applications. The final sections of the book describe helpful normalization techniques and criteria weight measurement techniques. The collection of diverse range of manufacturing applications and case studies presented here will aid readers in applying cutting-edge MCDM methods to their own manufacturing projects. As both a research and teaching tool, this book encourages critical and logical thinking when applying MCDM methods for solving complex manufacturing decision-making problems.
In real-life scenarios, service management involves complex decision-making processes usually affected by random or stochastic variables. Under such uncertain conditions, the development and use of robust and flexible strategies, algorithms, and methods can provide the quantitative information necessary to make better business decisions. Decision Making in Service Industries: A Practical Approach explores the challenges that must be faced to provide intelligent strategies for efficient management and decision making that will increase your organization’s competitiveness and profitability. The book provides insight and understanding into practical and methodological issues related to decision-making processes under uncertainty in service industries. It examines current and future trends regarding how these decision-making processes can be efficiently performed for better design of service systems by using probabilistic algorithms as well as hybrid and simulation-based approaches. Traditionally, many quantitative tools have been developed to make decisions in production companies. This book explores how to use these tools for making decisions inside service industries. Thus, the authors tackle strategic, tactical, and operational problems in service companies with the help of suitable quantitative models such as heuristic and metaheuristic algorithms, simulation, or queuing theory. Generally speaking, decision making is a hard task in business fields. Making the issue more complex, most service companies’ problems are related to the uncertainty of the service demand. This book sheds light on these types of decision problems. It provides studies that demonstrate the suitability of quantitative methods to make the right decisions. Consequently, this book presents the business analytics needed to make strategic decisions in service industries.
This book shows how graph theory and matrix approach, and fuzzy multiple attribute decision making methods can be used in manufacturing. It proposes a methodology that will make decision making in the manufacturing environment structured and systematic. The book uses case studies to present the applications of decision making methods in real manufacturing situations.
This book provides an overview of intelligent decision-making techniques and discusses their application in production and retail operations. Manufacturing and retail enterprises have stringent standards for using advanced and reliable techniques to improve decision-making processes, since these processes have significant effects on the performance of relevant operations and the entire supply chain. In recent years, researchers have been increasingly focusing attention on using intelligent techniques to solve various decision-making problems. The opening chapters provide an introduction to several commonly used intelligent techniques, such as genetic algorithm, harmony search, neural network and extreme learning machine. The book then explores the use of these techniques for handling various production and retail decision-making problems, such as production planning and scheduling, assembly line balancing, and sales forecasting.
This book describes the new perspective of naturalistic decision making. The point of departure is how people make decisions in complex, time-pressured, ambiguous, and changing environments. The purpose of this book is to present and elaborate on past models developed to explain this type of decision making. The central philosophy of the book is that classical decision theory has been unproductive since it is so heavily grounded in economics and mathematics. The contributors believe there is little to be learned from laboratory studies about how people actually handle difficult and interesting tasks; therefore, the book presents a critique of classical decision theory. The models of naturalistic decision making described by the contributors were derived to explain the behavior of firefighters, business people, jurors, nuclear power plant operators, and command-and-control officers. The models are unique in that they address the way people use experience to frame situations and adopt courses of action. The models explain the strengths of skilled decision makers. Naturalistic decision research requires the examination of field settings, and a section of the book covers methods for conducting meaningful research outside the laboratory. In addition, since his approach has applied value, the book covers issues of training and decision support systems.
Many regulations issued by the U.S. Environmental Protection Agency (EPA) are based on the results of computer models. Models help EPA explain environmental phenomena in settings where direct observations are limited or unavailable, and anticipate the effects of agency policies on the environment, human health and the economy. Given the critical role played by models, the EPA asked the National Research Council to assess scientific issues related to the agency's selection and use of models in its decisions. The book recommends a series of guidelines and principles for improving agency models and decision-making processes. The centerpiece of the book's recommended vision is a life-cycle approach to model evaluation which includes peer review, corroboration of results, and other activities. This will enhance the agency's ability to respond to requirements from a 2001 law on information quality and improve policy development and implementation.
Advanced Applications in Manufacturing Engineering presents the latest research and development in manufacturing engineering across a range of areas, treating manufacturing engineering on an international and transnational scale. It considers various tools, techniques, strategies and methods in manufacturing engineering applications. With the latest knowledge in technology for engineering design and manufacture, this book provides systematic and comprehensive coverage on a topic that is a key driver in rapid economic development, and that can lead to economic benefits and improvements to quality of life on a large-scale. - Presents the latest research and developments in manufacturing engineering - Covers a comprehensive spread of manufacturing engineering areas for different tasks - Discusses tools, techniques, strategies and methods in manufacturing engineering applications - Considers manufacturing engineering at an international and transnational scale - Enables the reader to learn advanced applications in manufacturing engineering
This proceedings volume contains select Green Building, Materials and Civil Engineering related papers from the 2016 International Conference on Green Building, Materials and Civil Engineering (GBMCE2016) which was held in Hong Kong, P.R. China, April 17-18, 2016. This volume of proceedings aims to provide a platform for researchers, engineers, academics as well as industrial professionals from all over the world to present their research results and development activities in the fields of Energy, Environment and Civil Engineering.