Decision Making In Manufacturing Environment Using Graph Theory And Fuzzy Multiple Attribute Decision Making Methods

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 monograph is intended for an advanced undergraduate or graduate course as well as for researchers, who want a compilation of developments in this rapidly growing field of operations research. This is a sequel to our previous works: "Multiple Objective Decision Making--Methods and Applications: A state-of-the-Art Survey" (No.164 of the Lecture Notes); "Multiple Attribute Decision Making--Methods and Applications: A State-of-the-Art Survey" (No.186 of the Lecture Notes); and "Group Decision Making under Multiple Criteria--Methods and Applications" (No.281 of the Lecture Notes). In this monograph, the literature on methods of fuzzy Multiple Attribute Decision Making (MADM) has been reviewed thoroughly and critically, and classified systematically. This study provides readers with a capsule look into the existing methods, their characteristics, and applicability to the analysis of fuzzy MADM problems. The basic concepts and algorithms from the classical MADM methods have been used in the development of the fuzzy MADM methods. We give an overview of the classical MADM in Chapter II. Chapter III presents the basic concepts and mathematical operations of fuzzy set theory with simple numerical examples in a easy-to-read and easy-to-follow manner. Fuzzy MADM methods basically consist of two phases: (1) the aggregation of the performance scores with respect to all the attributes for each alternative, and (2) the rank ordering of the alternatives according to the aggregated scores.

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.

Advanced Modeling and Optimization of Manufacturing Processes presents a comprehensive review of the latest international research and development trends in the modeling and optimization of manufacturing processes, with a focus on machining. It uses examples of various manufacturing processes to demonstrate advanced modeling and optimization techniques. Both basic and advanced concepts are presented for various manufacturing processes, mathematical models, traditional and non-traditional optimization techniques, and real case studies. The results of the application of the proposed methods are also covered and the book highlights the most useful modeling and optimization strategies for achieving best process performance. In addition to covering the advanced modeling, optimization and environmental aspects of machining processes, Advanced Modeling and Optimization of Manufacturing Processes also covers the latest technological advances, including rapid prototyping and tooling, micromachining, and nano-finishing. Advanced Modeling and Optimization of Manufacturing Processes is written for designers and manufacturing engineers who are responsible for the technical aspects of product realization, as it presents new models and optimization techniques to make their work easier, more efficient, and more effective. It is also a useful text for practitioners, researchers, and advanced students in mechanical, industrial, and manufacturing engineering.

Engineering and design are often a necessary steps for an industry to become effective. Industry modeling can help to bridge the communication gap among engineers and system designers. Dynamic Methods and Process Advancements in Mechanical, Manufacturing, and Materials Engineering examines the principles of physics and materials science for analysis, design, manufacturing and maintenance of mechanical equipments and systems. Targeting researchers, practitioners, and academicians, this volume promotes innovative findings in mechanical, manufacturing and materials engineering.

The vast amount of information that must be considered to solve inherently ill-structured and complex strategic problems creates a need for tools and techniques to help decision-makers recognize the complexity of this process and develop a rational model for strategy evaluation. Decision Making Theories and Practices from Analysis to Strategy is a definitive focus on analytical strategic decision-making. This work is comprised of sophisticated tools and methodologies developed by researchers and vendors to improve decision making for business strategy. Extracting from a wide range of disciplines, including accounting, finance, information systems, international management, marketing, organizational management, operations research, production and operations management, and strategic management, this volume provides a conceptual and a utilitarian guide to decision making, perfect for both researchers and practicing professionals alike.

Materials Selection for Sustainability in the Built Environment: Environmental, Social and Economic Aspects presents the current state-of-the-art when it comes to the decision-making process for choosing construction materials to deliver sustainable construction projects. Aspects covered include the science of enhanced decision-making via operational research and machine learning techniques and how this can be implemented in various disciplines such as architecture, engineering and construction. To this end, the book discusses environmental, economic and social aspects in assessing construction materials and presents different tools and methods that can benefit and facilitate this process. Finally, the book reviews previous publications on construction material selection and presents essential discussions on the role professionals, researchers, contractors and governments play in making more sustainable decisions on the built environment. Presents a lifecycle management-based, systematic and integrated approach for sustainable construction materials selection Discusses the impact of materials selection, covering every aspect of sustainability (environmental, social and economic aspects) Looks at the concept of the circular economy Provides case studies on decision-making methods in combination with lifecycle sustainability assessments

This book describes applications of Jaya and Rao algorithms on real case studies concerning different renewable energy sources. In the last few decades, researchers have focused on renewable energy resources like solar energy, bio-energy, wave energy, ocean thermal energy, tidal energy, geothermal energy, and wind energy. This has resulted in the development of new techniques and tools that could harvest energy from renewable energy sources. Many researchers and scientists have focused on developing and optimizing the energy systems to extract and utilize renewable energy more efficiently. In this book, recently developed Jaya and Rao (Rao-1, Rao-2, and Rao-3) algorithms are introduced for single- and multi-objective optimization of selected renewable energy systems. The results of applications of the different versions of Jaya and Rao algorithms are compared with the other optimization techniques like GA, NSGA-II, PSO, MOPSO, ABC, etc., and the performance of the Jaya and Rao algorithms is highlighted compared to other optimization algorithms in the case of renewable energy systems. The book also includes the validation of different versions of the Jaya and Rao algorithms through the application to complex single- and multi-objective unconstrained benchmark functions. The algorithms and computer codes of different version of Jaya and Rao algorithms are included in the book that will be very much useful to readers in industry and academic research.