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INTRODUCTION

Design is the process by which human intellect, creativity, and passion are translated into useful artifacts. Engineering design is a subset of this broad design process in which performance and quality objectives and the underlying science are particularly important. Engineering design is a loosely structured, open-ended activity that includes problem definition, learning processes, representation, and decision making.

Engineering designers attempt to create solutions to satisfy particular specifications while complying with all constraints. When a satisfactory solution cannot be discerned, the designer must create new options. The traditional design approach has been one of deterministic problem solving, typically involving efforts to meet functional requirements subject to various technical and economic constraints.

In seeking a logical and rigorous structure to aid in developing a satisfactory design, or one that is acceptable to the customer or user of the product, a number of approaches have been proposed to organize, guide, and facilitate the design process. Examples include Taguchi’s theory of robust design, Deming’s principles of quality control, Quality Function Deployment, design for manufacture, and concurrent engineering. In some cases these approaches can lead to different and conflicting answers. It is important, therefore, that they be assessed individually and collectively to determine both their strengths and limitations for particular applications. A selection of these techniques is summarized in Chapter 4 and some of their limitations and advantages are noted.

PRIOR STUDIES

The National Research Council study Improving Engineering Design (NRC, 1991) reported that the best engineering design practices were not widely used in U.S. industry and that the key role of engineering designers in the product realization process was often not well understood by management. To reverse this trend the report recommended a complete rejuvenation of engineering design practice, education, and research, involving intense cooperation among industrial firms, universities, and government. The committee found that few of the recommendations have been implemented.

The 1991 study was authored at a time when the United States was losing market leadership to the “Asian tigers.” It reflected pessimism about the ability of the United States to compete in world markets and attributed some of the nation’s problems to poor design practices. A short decade later, the U.S. economy is leading the world, based in part on continuing annual productivity increases. Many observers credit this dominance largely to the leading position of the United States in the information age that has displaced the industrial age. Information technologies clearly have had, and will continue to have, a large impact on engineering design.

It is logical to ask whether proficiency in engineering design matters in this new economy. The committee’s answer is a resounding yes! The globalization of the economy and the associated competitive pressures to introduce new, better products faster and at lower cost make engineering design even more important.



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Theoretical Foundations for Decision Making in Engineering Design 1 INTRODUCTION Design is the process by which human intellect, creativity, and passion are translated into useful artifacts. Engineering design is a subset of this broad design process in which performance and quality objectives and the underlying science are particularly important. Engineering design is a loosely structured, open-ended activity that includes problem definition, learning processes, representation, and decision making. Engineering designers attempt to create solutions to satisfy particular specifications while complying with all constraints. When a satisfactory solution cannot be discerned, the designer must create new options. The traditional design approach has been one of deterministic problem solving, typically involving efforts to meet functional requirements subject to various technical and economic constraints. In seeking a logical and rigorous structure to aid in developing a satisfactory design, or one that is acceptable to the customer or user of the product, a number of approaches have been proposed to organize, guide, and facilitate the design process. Examples include Taguchi’s theory of robust design, Deming’s principles of quality control, Quality Function Deployment, design for manufacture, and concurrent engineering. In some cases these approaches can lead to different and conflicting answers. It is important, therefore, that they be assessed individually and collectively to determine both their strengths and limitations for particular applications. A selection of these techniques is summarized in Chapter 4 and some of their limitations and advantages are noted. PRIOR STUDIES The National Research Council study Improving Engineering Design (NRC, 1991) reported that the best engineering design practices were not widely used in U.S. industry and that the key role of engineering designers in the product realization process was often not well understood by management. To reverse this trend the report recommended a complete rejuvenation of engineering design practice, education, and research, involving intense cooperation among industrial firms, universities, and government. The committee found that few of the recommendations have been implemented. The 1991 study was authored at a time when the United States was losing market leadership to the “Asian tigers.” It reflected pessimism about the ability of the United States to compete in world markets and attributed some of the nation’s problems to poor design practices. A short decade later, the U.S. economy is leading the world, based in part on continuing annual productivity increases. Many observers credit this dominance largely to the leading position of the United States in the information age that has displaced the industrial age. Information technologies clearly have had, and will continue to have, a large impact on engineering design. It is logical to ask whether proficiency in engineering design matters in this new economy. The committee’s answer is a resounding yes! The globalization of the economy and the associated competitive pressures to introduce new, better products faster and at lower cost make engineering design even more important.

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Theoretical Foundations for Decision Making in Engineering Design Recently, the importance of engineering design Was re-emphasized by Wm A.Wulf, president of the National Academy of Engineering (Wulf, 1998), and by the Accreditation Board for Engineering and Technology in its standards (see Appendix A), which require an increased emphasis on design in engineering curricula. The National Science Foundation (NSF) has been actively working to address various issues in the engineering design area. In 1996, it sponsored a workshop entitled “Research Opportunities in Engineering Design” to determine research priorities in engineering design by examining industry and education needs and to formulate recommendations for the NSF’s Engineering Design Program (NSF, 1996). The NSF funds an on-line decision-based design open workshop to engage design theory researchers in a dialogue to establish a common foundation for research and educational endeavors (<http://dbd.eng.buffalo.edu/>). The NSF also sponsored Gordon Research Conferences in 1998 and 2000 on theoretical foundations for product design and manufacturing (GRC, 1998, 2000). THE CHANGING NATURE OF ENGINEERING DESIGN In the past it was too often sufficient to design, produce, and market designs based mostly on lore, empiricisms, and extrapolations. Many industrial processes and products remained essentially unchanged as long as the companies were profitable and the industries were unchallenged. In today’s economy the globalization of business and markets, the changing nature of world trade regulations and business operations, and the impacts of information technology on business have fundamentally changed the economy and are having a profound effect on engineering practice. To be competitive in today’s global marketplace, incremental changes and empirical methods are inadequate. Products must be developed and introduced to markets faster, with unprecedented demands for high performance and low cost. Strategic changes in existing industries are required to counter the salary differences between the workers in this country who produce exports and those across the globe who produce imports. Furthermore, new and unprecedented demands on the performance and operation of new and emerging technologies and the major innovations required for industries to be competitive on a global scale have surpassed the existing general knowledge from which such designs can be made. There is little or no experience on which to base such technological advances. Thus, there exists a chasm between existing empirically developed systems and possible innovations. Engineers today do have extraordinary tools and resources including computers, remarkable materials, and advanced engineering environments at their disposal. Much deeper understanding of the industrial processes is required, however, before those resources can be put to good use. The result, a new and essential tool for engineering practice also known as Research for Design (R4D), can be used to develop knowledge bases that enable innovative, reliable, cost-effective, and efficient designs. Design is a complex process involving aspects ranging from product quality to life-cycle analysis, but first and foremost, the physicochemical phenomena or behavior of the system elements, must be understood to make the innovations required and to assure functional performance of the design. The research in R4D is focused and directed to provide the designers the specific information they require in real time. It differs from the R in R&D, which usually means basic scientific research. R4D focuses on the people-made world to expand the knowledge base from which advances in design and production can be made. It is often multi-disciplinary and addresses the functional characteristics of large systems that consist of intricate components. Every company must have an ever increasing, relevant engineering knowledge base and the technologies and the people for translating that base into products rapidly and efficiently.

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Theoretical Foundations for Decision Making in Engineering Design R4D requires researchers to be in continual contact with designers and systems engineers in order to identify, define, and obtain the precise information required for the development of cutting-edge technologies. Recent technological advances in distributed networking, telecommunications, multi-user computer applications, and interactive virtual reality (called “advanced engineering environments” [NRC, 1999]) not only enable disparate communities to interact in real time but also allow seamless integration of research, development, and application cycles to bring about efficient interactions and rapid progress. Major advances in engineering design are based on increased computational power and communication (information technology). High-fidelity models of complex systems and advanced visualization techniques, as reported in Advanced Engineering Environments: Achieving the Vision, Phase 1 (NRC, 1999), provide powerful new tools to today’s designers. But stunning graphics and improved models are not sufficient to design increasingly complex systems; methodologies to make sound design decisions are required. CURRENT STUDY The National Science Foundation asked the Board on Manufacturing and Engineering Design to examine theories and techniques for decision making under conditions of risk, uncertainty, and conflicting human values. This report reviews existing tools and theories and identifies opportunities to establish a more rigorous fundamental basis for decision making in engineering design. The specific tasks were as follows: Identify approaches to decision making in other fields, such as operations research, economics, and management sciences, that address issues of risk and value. This will include a review of the state of the art and the extent of validation of these approaches. The committee is also charged to investigate the pertinence and validity of these approaches for building an improved decision-making framework for engineering design that can rigorously deal with probability, preferences, and risk in the manufacturing climate of 2020. Identify the strengths and limitations of tools currently used in engineering design as they relate to decision making and issues of risk and Values in the increasingly complex manufacturing climate described in Visionary Manufacturing Challenges for 2020 (NRC, 1998) and other recent studies. This will include such methodologies as design for manufacture, Taguchi’s theory of robust design, Quality Function Deployment, and concurrent engineering. Prepare recommendations for future development, validation, and application of these tools in order to improve design decision-making capability in a logical and rational manner. Address the implications of adopting these techniques for engineering practices and for the engineering curriculum. Recommend core competencies in mathematics and engineering necessary for improved decision making by design practitioners. Chapter 2 places the role of decision making in the context of engineering design by discussing decision processes and tools used in different frames or environments. Chapter 3 describes many elements or aspects of the applied decision theory or decision analysis. Chapter 4 briefly discusses approaches, tools, and theories used and proposed to aid designers. Chapter 5 concludes with the committee’s recommendations.

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Theoretical Foundations for Decision Making in Engineering Design REFERENCES Gordon Research Conference. 1998. Theoretical Foundations for Product Design and Manufacturability , June 7–12, Hennicker, N.H. Gordon Research Conference. 2000. Theoretical Foundations for Product Design and Manufacturing, June 11–16, Plymouth, N.H. National Research Council. 1991. Improving Engineering Design. Washington, D.C.: National Academy Press. National Research Council. 1998. Visionary Manufacturing Challenges for 2020. Washington, D.C.: National Academy Press. National Research Council. 1999. Advanced Engineering Environments, Phase 1. Washington, D.C.: National Academy Press. National Science Foundation. 1996. Research Opportunities in Engineering Design. NSF Strategic Planning Workshop Final Report. Washington D.C.: National Science Foundation. Wulf, W.A. 1998. The urgency of engineering education reform. The Bridge 28(1):4–8.