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.
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.
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.
Covering the prediction of outcomes for engineering decisions through regression analysis, this succinct and practical reference presents statistical reasoning and interpretational techniques to aid in the decision making process when faced with engineering problems. The author emphasizes the use of spreadsheet simulations and decision trees as important tools in the practical application of decision making analyses and models to improve real-world engineering operations. He offers insight into the realities of high-stakes engineering decision making in the investigative and corporate sectors by optimizing engineering decision variables to maximize payoff.
"Systems engineering is an interdisciplinary field of engineering and engineering management that focuses on how to design, integrate, and manage complex systems over their life cycles. At its core, systems engineering utilizes systems thinking principles to organize this body of knowledge."--
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.
This book proposes a set of models to describe fuzzy multi-objective decision making (MODM), fuzzy multi-criteria decision making (MCDM), fuzzy group decision making (GDM) and fuzzy multi-objective group decision-making problems, respectively. It also gives a set of related methods (including algorithms) to solve these problems. One distinguishing feature of this book is that it provides two decision support systems software for readers to apply these proposed methods. A set of real-world applications and some new directions in this area are then described to further instruct readers how to use these methods and software in their practice.
This title is a guide, designed for engineering managers, to the theory and practice of how good decisions are made and why poor decisions occur. It is the result of many years of teaching and consultancy in organizational and social decision making and provides some of the most important concepts in managerial decision theory.
10.2.2 Individual decision-making skills -- 10.2.3 Group decision-making skills -- 10.2.4 Organizational-level attributes -- 10.3 Case studies to explore in teams -- 10.4 Case A: The team that wasn't -- 10.4.1 Background -- 10.4.2 Grand challenge -- 10.5 Case B: Disruptive innovation at Tonowanda -- 10.5.1 Background -- 10.5.2 Grand challenge -- 10.6 Case C: Die Cast Testing -- 10.6.1 Background -- 10.6.2 Grand challenge -- 10.7 Case D: Welcome to FR4 -- 10.7.1 Background -- 10.7.2 Grand challenge -- A: Problems and Problem-Solving -- A.1 Design process analogy -- A.2 Two basic categories of problems -- A.3 Organizational form -- A.4 Problem solution outcomes -- B: Mechanics of Accounting -- B.1 Learning objectives -- B.2 Accounting to support financial statements -- B.2.1 T-accounts -- B.2.2 Chart of accounts -- B.2.3 General journal -- B.2.4 General ledger -- B.2.5 Adjusting entries -- B.3 Problems to explore -- C: Reference Tables -- D: Index -- A -- B -- C -- D -- E -- F -- G -- H -- I -- K -- L -- M -- N -- O -- P -- R -- S -- T -- U -- V -- W
