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.

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.

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.

DECISION MAKING IN SYSTEMS ENGINEERING AND MANAGEMENT A thoroughly updated overview of systems engineering management and decision making In the newly revised third edition of Decision Making in Systems Engineering and Management, the authors deliver a comprehensive and authoritative overview of the systems decision process, systems thinking, and qualitative and quantitative multi-criteria value modeling directly supporting decision making throughout the system lifecycle. This book offers readers major new updates that cover recently developed system modeling and analysis techniques and quantitative and qualitative approaches in the field, including effective techniques for addressing uncertainty. In addition to Excel, six new open-source software applications have been added to illustrate key topics, including SIPmath Modeler Tools, Cambridge Advanced Modeller, SystemiTool2.0, and Gephi 0.9.2. The authors have reshaped the book’s organization and presentation to better support educators engaged in remote learning. New appendices have been added to present extensions for a new realization analysis technique and getting started steps for each of the major software applications. Updated illustrative examples support modern system decision making skills and highlight applications in hardware, organizations, policy, logistic supply chains, and architecture. Readers will also find: Thorough introductions to working with systems, the systems engineering perspective, and systems thinking In-depth presentations of applied systems thinking, including holism, element dependencies, expansive and contractive thinking, and concepts of structure, classification, and boundaries Comprehensive explorations of system representations leading to analysis In-depth discussions of supporting system decisions, including the system decision process (SDP), tradespace methods, multi-criteria value modeling, working with stakeholders, and the system environment Perfect for undergraduate and graduate students studying systems engineering and systems engineering management, Decision Making in Systems Engineering and Management will also earn a place in the libraries of practicing system engineers and researchers with an interest in the topic.

Recognized as a powerful tool for dealing with uncertainty, Markov modeling can enhance your ability to analyze complex production and service systems. However, most books on Markov chains or decision processes are often either highly theoretical, with few examples, or highly prescriptive, with little justification for the steps of the algorithms u

This book focuses on decision-making problems in engineering. It investigates the ranking aggregation problem and the related features, such as input/output data, simplification hypotheses, importance hierarchy of experts. In addition to a well-structured overview of several interesting, consolidated methodological approaches, it presents innovative approaches that can also be applied profitably in other fields. The fascinating selection of topics included is based on research that has been developed in the past twenty years. The descriptions are supported by figures, tables, flowcharts, diagrams, examples and practical case studies. The book is an ideal resource for engineering academics, practitioners, technicians and students, who do not necessarily have an in-depth knowledge of decision-making. It is also a thought-provoking read for engineers and academics looking for innovative ways to improve engineering processes in a variety of fields, such as conceptual design, quality improvement, reliability engineering. “Today, rankings are exercised in all spheres of life, products are ranked on Amazon and similar platforms; services such as restaurants and hotels on platforms such as TripAdvisor; and other services such as lectures or even medical treatment on different specialized platforms. We often make our daily decisions based on these rankings. The quality of our decisions depends on our ability to select appropriate methods to fit the context and needs. We need to be familiar with the theory and practice of these methods to make them useful. To this purpose, this book is an important addition to the bookshelves of academics and professionals, not only from engineering. The connection between theory and practice is weaved throughout the book, making it useful for practitioners also.” Prof. Yoram Reich, Full Professor and Head of Systems Engineering research Initiative at Tel Aviv University (Israel), Editor-in-Chief of “Research in Engineering Design”