Whether you are an engineer facing decisions in product design, an instructor or student engaged in course work, or a researcher exploring new options and opportunities, you can turn to Decision Making in Engineering Design for: Foundations and fundamentals of making decisions in product design; Clear examples of effective application of Decision-Based Design; State-of-the-art theory and practice in Decision-Based Design; Thoughtful insights on validation, uncertainty, preferences, distributed design, demand modeling, and other issues; End-of-chapter exercise problems to facilitate learning. With this advanced text, you become current with research results on DBD developed since the inception of The Open Workshop on Decision-Based Design, a project funded by the National Science Foundation.
This book is a sequel to The Practice of Machine Design, and The Practice of Machine Design, Book 3 – Learning from Failure. It deals with what happens inside the human mind during such activities as design and production, and how we reach decisions. Unlike other regular machine design textbooks or handbooks that describe how to accomplish good designs, the present volume explains what the designer thinks when making design decisions. A design starts with a vague concept and gradually takes shapes as it proceeds, and during this process the mind extracts elements and makes selections and decisions, the results expressed in sketches, drawings, or sentences. This book aims at exposing the reader to the processes of element extraction, selection, and decision-making through real-life examples. Such a book has never been published before. An explicit description of the processes of making decisions, on the contrary, has been greatly needed by designers, and the managers of design groups have been much aware of such a lack. The non-existence of this type of book in the past is due to the following three reasons: the benefit of describing the mind process of design was never made clear, the method of such clarification was unknown, and no one ever invested the vast energy for producing such a manifestation. Under these circumstances, we the members of the “Practice of Machine Design Research Group” boldly tackled the problem of expressing the decision processes in design and have documented our findings in this book.
Multiple criteria decision making tools have been developing at an extremely rapid pace over the last few years. This work explores the nature of the pursuit, using the authors extensive experience in the field. With its clear, concise approach combining industrial examples and case studies, this book will be of interest to graduate students, practicing engineers, and project managers.
As the world becomes increasingly globalized, today's companies expect to hire engineers who are effective in a global business environment. Although you can find many books covering globalization, most of them are aimed at business, management, or social sciences. Developed with engineers in mind, Global Engineering: Design, Decision Making, and C
IIE/Joint Publishers Book of the Year Award 2016! Awarded for ‘an outstanding published book that focuses on a facet of industrial engineering, improves education, or furthers the profession’. Engineering Decision Making and Risk Management emphasizes practical issues and examples of decision making with applications in engineering design and management Featuring a blend of theoretical and analytical aspects, this book presents multiple perspectives on decision making to better understand and improve risk management processes and decision-making systems. Engineering Decision Making and Risk Management uniquely presents and discusses three perspectives on decision making: problem solving, the decision-making process, and decision-making systems. The author highlights formal techniques for group decision making and game theory and includes numerical examples to compare and contrast different quantitative techniques. The importance of initially selecting the most appropriate decision-making process is emphasized through practical examples and applications that illustrate a variety of useful processes. Presenting an approach for modeling and improving decision-making systems, Engineering Decision Making and Risk Management also features: Theoretically sound and practical tools for decision making under uncertainty, multi-criteria decision making, group decision making, the value of information, and risk management Practical examples from both historical and current events that illustrate both good and bad decision making and risk management processes End-of-chapter exercises for readers to apply specific learning objectives and practice relevant skills A supplementary website with instructional support material, including worked solutions to the exercises, lesson plans, in-class activities, slides, and spreadsheets An excellent textbook for upper-undergraduate and graduate students, Engineering Decision Making and Risk Management is appropriate for courses on decision analysis, decision making, and risk management within the fields of engineering design, operations research, business and management science, and industrial and systems engineering. The book is also an ideal reference for academics and practitioners in business and management science, operations research, engineering design, systems engineering, applied mathematics, and statistics.
This book presents an operational tool for decision making under uncertainty in any engineering design. It synthesizes classical decision making methods, such as multi-attribute utility theory, analytic hierarchy process with game theory and quantum decision theory. It demonstrates the implementation of the value driven design philosophy in the engineering design framework. Value, related to the designed system’s capabilities and lifecycle cost, is used to compare different alternatives through the appropriate value model. Game Theory as an optimization tool is used to successfully address the stakeholders’ preferences in a functional outcome-focused way. A Quantum-based Decision Making model is also developed to capture the complexity of human decision making related with risk attitude in the presence of ambiguity and uncertainty. Apart from rationality, the decision makers’ biases, emotions and subjective feelings are also captured in this model.
Decision Making in Systems Engineering and Management is a comprehensive textbook that provides a logical process and analytical techniques for fact-based decision making for the most challenging systems problems. Grounded in systems thinking and based on sound systems engineering principles, the systems decisions process (SDP) leverages multiple objective decision analysis, multiple attribute value theory, and value-focused thinking to define the problem, measure stakeholder value, design creative solutions, explore the decision trade off space in the presence of uncertainty, and structure successful solution implementation. In addition to classical systems engineering problems, this approach has been successfully applied to a wide range of challenges including personnel recruiting, retention, and management; strategic policy analysis; facilities design and management; resource allocation; information assurance; security systems design; and other settings whose structure can be conceptualized as a system.
Building upon the fundamental principles of decision theory, Decision-Based Design: Integrating Consumer Preferences into Engineering Design presents an analytical approach to enterprise-driven Decision-Based Design (DBD) as a rigorous framework for decision making in engineering design. Once the related fundamentals of decision theory, economic analysis, and econometrics modelling are established, the remaining chapters describe the entire process, the associated analytical techniques, and the design case studies for integrating consumer preference modeling into the enterprise-driven DBD framework. Methods for identifying key attributes, optimal design of human appraisal experiments, data collection, data analysis, and demand model estimation are presented and illustrated using engineering design case studies. The scope of the chapters also provides: A rigorous framework of integrating the interests from both producer and consumers in engineering design, Analytical techniques of consumer choice modelling to forecast the impact of engineering decisions, Methods for synthesizing business and engineering models in multidisciplinary design environments, and Examples of effective application of Decision-Based Design supported by case studies. No matter whether you are an engineer facing decisions in consumer related product design, an instructor or student of engineering design, or a researcher exploring the role of decision making and consumer choice modelling in design, Decision-Based Design: Integrating Consumer Preferences into Engineering Design provides a reliable reference over a range of key topics.
Engineering Design, Planning and Management, Second Edition represents a compilation of essential resources, methods, materials and knowledge developed by the author and used over two decades. The book covers engineering design methodology through an interdisciplinary approach, with concise discussions and a visual format. It explores project management and creative design in the context of both established companies and entrepreneurial start-ups. Readers will discover the usefulness of the design process model through practical examples and applications from across engineering disciplines. Sections explain useful design techniques, including concept mapping and weighted decision matrices that are supported with extensive graphics, flowcharts and accompanying interactive templates. Discussions are organized around 12 chapters dealing with topics such design concepts and embodiments, decision-making, finance, budgets, purchasing, bidding, communication, meetings and presentations, reliability and system design, manufacturing design and mechanical design. - Covers all steps in the design process - Includes several chapters on project management, budgeting and teamwork, providing sufficient background to help readers effectively work with time and budget constraints - Provides flowcharts, checklists and other templates that are useful for implementing successful design methods - Presents examples and applications from several different engineering fields to show the general usefulness of the design process model
Multi-criteria Decision Analysis for Supporting the Selection of Engineering Materials in Product Design, Second Edition, provides readers with tactics they can use to optimally select materials to satisfy complex design problems when they are faced with the vast range of materials available. Current approaches to materials selection range from the use of intuition and experience, to more formalized computer-based methods, such as electronic databases with search engines to facilitate the materials selection process. Recently, multi-criteria decision-making (MCDM) methods have been applied to materials selection, demonstrating significant capability for tackling complex design problems. This book describes the rapidly growing field of MCDM and its application to materials selection. It aids readers in producing successful designs by improving the decision-making process. This new edition updates and expands previous key topics, including new chapters on materials selection in the context of design problem-solving and multiple objective decision-making, also presenting a significant amount of additional case studies that will aid in the learning process. - Describes the advantages of Quality Function Deployment (QFD) in the materials selection process through different case studies - Presents a methodology for multi-objective material design optimization that employs Design of Experiments coupled with Finite Element Analysis - Supplements existing quantitative methods of materials selection by allowing simultaneous consideration of design attributes, component configurations, and types of material - Provides a case study for simultaneous materials selection and geometrical optimization processes
