Engineering Decision Making and Risk Management

Jeffrey W. Herrmann

• Verlag: Wiley
• Jahr: 2015
• ISBN:
  9781118919378
• Auflage: 1
• Thema: Business
• Thema: Management

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 e mphasizes 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.

Chapter 1
Introduction to Engineering Decision Making

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Learning Objectives:

After studying this chapter, the reader will be able to do the following:

1. Identify and describe two types of decisions that engineers make (Section 1.2).
2. Classify the decisions that engineers make (Section 1.2).
3. Describe how optimization is related to decision making (Section 1.3).
4. Describe how problem solving is related to decision making (Section 1.4).
5. Explain why decision making is part of risk management (Section 1.5).
6. Identify problems that can occur in decision making (Section 1.6).
7. Identify the benefits of improving decision making (Section 1.7).
8. Describe a decision from three perspectives (Section 1.8).

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1.1 Introduction

Why should engineers study decision making? What is engineering decision making?

People have always made decisions, but analyzing decision-making processes and developing better decision-making methods are more recent activities. Our ability to analyze decisions has increased as mathematics, especially the theory of probability, has developed. In the 1700s, Daniel Bernoulli analyzed risky decisions and described how the relative values of alternatives depend on the preferences of the decision maker (Bernoulli, 1954). Ramsey (1964) developed a theory for decision making based on probability theory and utility. von Neumann and Morgenstern (1944) formalized the theory of expected utility and the analysis of multiplayer games, which is now known as game theory. Early works on game theory include Borel (1921), von Neumann (1928, 1959), and Hotelling (1929), who analyzed a game related to product differentiation. The works of Savage (1954), Raiffa (1968), Schlaifer (1969), Benjamin and Cornell (1970), and Keeney and Raiffa (1976) have been cited as influential early textbooks. Buchanan and O'Connell (2006) surveyed the history of decision making and the roles of intuition, risk, groups, and computing in decision making.

Now, what about engineering decision making? Scientists use their observations of natural phenomena to generate scientific knowledge, but engineers use their knowledge of the world to design products and systems that can perform needed functions while satisfying certain requirements.

To design a product or a system or to plan an activity, an engineer must make decisions. The engineer decides that a component will use a certain material, will have a certain shape, and will be made in a certain way. The engineer decides how the activity will be performed, who will do which tasks, and when they will be done. There are many possible choices, and the engineer must select one. This is the essence of decision making.

The process of making a decision, similar to cooking, transforms inputs into outputs. Cooking transforms ingredients such as pasta, ground beef, tomato sauce, spices, mozzarella, ricotta, and parmesan cheese into an appetizing dish such as lasagna. Decision making transforms information. The input information includes knowledge about physical phenomena, manufacturing processes, costs, customer requirements, regulations, and existing designs. Of course, there may be uncertainties about this information. The output is new information: a description of a design or a plan. That is, engineering decision making transforms existing information into new information.

Those engineers who improve their ability to make decisions should generate designs and plans that are more effective and more efficient. This will help the engineers and their organizations to be more productive, more successful, and more valuable. Because engineers are trained in mathematics, statistics, analysis, and modeling, they have the prerequisites to study and understand the techniques necessary to improve decision making. Because engineers have experience in designing, testing, and building objects and systems, they have the skills to apply these decision-making techniques to real-world problems.

Some of the techniques covered in this text can help a decision maker find the “best” alternative (the “right answer”). Studying decision making, however, should produce not only better answers but also new ways of thinking about decisions. Thinking more carefully about a decision will lead to better understanding even if no formal technique is applied. It can help one to choose an appropriate process and avoid decision-making errors. It can encourage one to consider how much information is really needed. It can lead one to see the potential problems with the available alternatives and find ways to reduce those risks.

Thinking about the merits of the alternatives, the criteria used to evaluate them, and the uncertainties involved can help engineers articulate and record the rationale for their decisions, which can help them justify their decisions to their peers and superiors and avoid errors during future redesigns. Recording design rationale can also support collaboration, design reuse, and training other engineers (Lee, 1997).

This text discusses three perspectives on decision making: (1) the problem-solving perspective, (2) the decision-making process perspective, and (3) the decision-making system perspective. These are discussed in detail in Section 1.8. The material included herein will cover important topics on decision making, present tools for helping engineers make better decisions, and provide examples to illustrate the concepts and techniques. The author hopes that students and engineers who study this material and apply these concepts and techniques will become better decision makers.

Studies of how decision makers make choices in practice have revealed that some decisions are made using simple heuristics (Gigerenzer et al., 1999), and others are made without considering multiple alternatives (cf. Klein et al., 2010). Improving decision making can go beyond the valuable insights that are gained by understanding these phenomena, however. The mathematical models used in the study of decision making are, like all models, approximations of what really happens. Still, they can be valuable if they are useful to those who need to make decisions. The text, therefore, includes a variety of models that have been generally useful.

In particular, this text describes multiattribute utility theory (MAUT), the analytic hierarchy process (AHP), models for representing risk preferences, and game theory models. As Luce and Raiffa (1957) noted, such models do not describe what all decision makers do, and they do not describe what decision makers should do in an absolute sense (in all cases). They do, however, attempt to say which alternative is the best way to achieve the decision maker's particular goals.

This section began with two questions and provided some answers. These answers, however, lead to additional questions that this text will address:

• What is the value of improving decision making?
• Which alternative is the best one?
• How should our group make a decision?
• How can one compare alternatives in the presence of uncertainty?
• How can we decide when we do not know what the other guy is going to do?
• Which decision-making process is the most appropriate?
• Should we gather more information before deciding?
• How can we reduce risk?
• How do organizations make decisions?
• How can we improve decision making in our organization?

1.2 Decision Making in Engineering Practice

In practice, engineers make many different types of decisions as they design products and systems. In general, the decisions that engineers make can be classified into two broad categories:

1. What should the design be? Design decisions determine the overall structure, shape, size, material, manufacturing process, and components of an object or a system. These generate information about the design itself and the requirements that it must satisfy. Design decisions may involve manufacturing processes and systems. Deciding that gear hobbing will be used to make the bull gear for a re...