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David G. Ullman

Bio: David G. Ullman is an academic researcher from Oregon State University. The author has contributed to research in topics: Engineering design process & Decision support system. The author has an hindex of 21, co-authored 55 publications receiving 4026 citations. Previous affiliations of David G. Ullman include New Jersey Institute of Technology & University of Washington.


Papers
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Book
01 Mar 1992
TL;DR: In this article, the authors describe the design process and design problems and process of the development of a product and evaluate its performance and the effects of variations. And they present a belief map of 25 materials most commonly used in mechanical design.
Abstract: 1 Why Study the Design Process? 2 Describing Mechanical Design Problems and Process 3 Designers and Design Teams 4 The Design Process 5 Project Definition and Planning 6 Understanding the Problem and the Development of Engineering Specifications 7 Concept Generation 8 Concept Evaluation 9 The Product Design Phase 10 Product Generation 11 Product Evaluation for Performance and the Effects of Variation 12 Product Evaluation for Cost, Manufacture, Assembly, and other Measures 13 Launching and Supporting the Product Appendixes A Properties of 25 Materials Most Commonly Used in Mechanical Design B Normal Probability C The Factor of Safety as a Design Variable D Human Factors in Design E TRIZ F Belief Map Masters

2,076 citations

Journal ArticleDOI
TL;DR: Five hypotheses, focused on the types of drawings, their necessity in mechanical problem solving, and their relation to the external representation medium, are presented and supported.

405 citations

Journal ArticleDOI
TL;DR: The task/episode accumulation model (TEA model) of non-routine mechanical design was developed after detailed analysis of the audio and video protocols of five mechanical designers and is able to explain the behavior of designers at much finer level of detail than previous models.
Abstract: This paper describes the task/episode accumulation model (TEA model) of non-routine mechanical design, which was developed after detailed analysis of the audio and video protocols of five mechanical designers. The model is able to explain the behavior of designers at a much finer level of detail than previous models. The key features of the model are (a) the design is constructed by incrementally refining and patching an initial conceptual design, (b) design alternatives are not considered outside the boundaries of design episodes (which are short stretches of problem solving aimed at specific goals), (c) the design process is controlled locally, primarily at the level of individual episodes. Among the implications of the model are the following: (a) CAD tools should be extended to represent the state of the design at more abstract levels, (b) CAD tools should help the designer manage constraints, and (c) CAD tools should be designed to give cognitive support to the designer.

361 citations

Journal ArticleDOI
TL;DR: A taxonomy of the questions asked by the designers in this study and the conjectures they formed is presented and it is proposed that an intelligent CAD system be developed to capture, structure, and re-play this information.

128 citations

Journal ArticleDOI
TL;DR: This paper attempts to look at the gap between the needs of a mechanical engineer and what is currently available on CAD systems using a designer-centric approach.
Abstract: This paper details the progress toward the development of the ideal mechanical engineering design support system. It attempts to look at the gap between the needs of a mechanical engineer and what is currently available on CAD systems. Since the term CAD emphasizes that the computer is an aid to the human designer, this paper is designer-centric. It is based heavily on the activities performed by designers and the types of information developed by them. Seventeen goals for the ideal mechanical design support system are listed. These are directed at the types of information developed during the design process and the activities used to develop them. For each of the seventeen, background information, the current state-of-the-art, and opportunities for future development are itemized.

111 citations


Cited by
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Book
14 Sep 2011
TL;DR: The paper is intended to raise awareness of the far-reaching implications of the architecture of the product, to create a vocabulary for discussing and addressing the decisions and issues that are linked to product architecture, and to identify and discuss specific trade-offs associated with the choice of a product architecture.
Abstract: Product architecture is the scheme by which the function of a product is allocated to physical components. This paper further defines product architecture, provides a typology of product architectures, and articulates the potential linkages between the architecture of the product and five areas of managerial importance: (1) product change; (2) product variety; (3) component standardization; (4) product performance; and (5) product development management. The paper is conceptual and foundational, synthesizing fragments from several different disciplines, including software engineering, design theory, operations management and product development management. The paper is intended to raise awareness of the far-reaching implications of the architecture of the product, to create a vocabulary for discussing and addressing the decisions and issues that are linked to product architecture, and to identify and discuss specific trade-offs associated with the choice of a product architecture.

2,603 citations

Journal ArticleDOI
TL;DR: In this article, the purpose of engineering education is to train engineers who can design, and that design thinking is difficult to learn and difficult to teach, and the most popular pedagogical model for teaching design is Project-Based Learning (PBL).
Abstract: This paper is based on the premises that the purpose of engineering education is to graduate engineers who can design, and that design thinking is complex. The paper begins by briefly reviewing the history and role of design in the engineering curriculum. Several dimensions of design thinking are then detailed, explaining why design is hard to learn and harder still to teach, and outlining the research available on how well design thinking skills are learned. The currently most-favored pedagogical model for teaching design, project-based learning (PBL), is explored next, along with available assessment data on its success. Two contexts for PBL are emphasized: first-year cornerstone courses and globally dispersed PBL courses. Finally, the paper lists some of the open research questions that must be answered to identify the best pedagogical practices of improving design learning, after which it closes by making recommendations for research aimed at enhancing design learning.

2,159 citations

Journal ArticleDOI
TL;DR: This paper looks inside the "black box" of product development at the fundamentaldecisions that are made by intention or default, adopting the perspective ofproduct development as a deliberate business process involving hundreds of decisions, many of which can be usefully supported by knowledge and tools.
Abstract: This paper is a review of research in product development, which we define as the transformation of a market opportunity into a product available for sale. Our review is broad, encompassing work in the academic fields of marketing, operations management, and engineering design. The value of this breadth is in conveying the shape of the entire research landscape. We focus on product development projects within a single firm. We also devote our attention to the development of physical goods, although much of the work we describe applies to products of all kinds. We look inside the "black box" of product development at the fundamentaldecisions that are made by intention or default. In doing so, we adopt the perspective of product development as a deliberate business process involving hundreds of decisions, many of which can be usefully supported by knowledge and tools. We contrast this approach to prior reviews of the literature, which tend to examine the importance of environmental and contextual variables, such as market growth rate, the competitive environment, or the level of top-management support.

1,725 citations

08 Nov 2014
TL;DR: A knowledge representation schema for design called design prototypes is introduced and described to provide a suitable framework to distinguish routine, innovative, and creative design.
Abstract: A prevalent and pervasive view of designing is that it can be modeled using variables and decisions made about what values should be taken by these variables. The activity of designing is carried out with the expectation that the designed artifact will operate in the natural world and the social world. These worlds impose constraints on the variables and their values; so, design could be described as a goal-oriented, constrained, decision- making activity. However, design distinguish- es itself from other similarly described activities not only by its domain but also by additional necessary features. Designing involves exploration, exploring what variables might be appropriate. The process of explo- ration involves both goal variables and deci- sion variables. In addition, designing involves learning: Part of the exploration activity is learning about emerging features as a design proceeds. Finally, design activity occurs within two contexts: the context within which the designer operates and the context produced by the developing design itself. The designer’s perception of what the context is affects the implication of the context on the design. The context shifts as the designer’s perceptions change. Design activity can be now characterized as a goal-oriented, con- strained, decision-making, exploration, and learning activity that operates within a con- text that depends on the designer’s percep- tion of the context.

1,697 citations

Journal ArticleDOI
01 Jan 2006
TL;DR: This work reviews the state-of-the-art metamodel-based techniques from a practitioner's perspective according to the role of meetamodeling in supporting design optimization, including model approximation, design space exploration, problem formulation, and solving various types of optimization problems.
Abstract: Computation-intensive design problems are becoming increasingly common in manufacturing industries. The computation burden is often caused by expensive analysis and simulation processes in order to reach a comparable level of accuracy as physical testing data. To address such a challenge, approximation or metamodeling techniques are often used. Metamodeling techniques have been developed from many different disciplines including statistics, mathematics, computer science, and various engineering disciplines. These metamodels are initially developed as “surrogates” of the expensive simulation process in order to improve the overall computation efficiency. They are then found to be a valuable tool to support a wide scope of activities in modern engineering design, especially design optimization. This work reviews the state-of-the-art metamodel-based techniques from a practitioner’s perspective according to the role of metamodeling in supporting design optimization, including model approximation, design space exploration, problem formulation, and solving various types of optimization problems. Challenges and future development of metamodeling in support of engineering design is also analyzed and discussed.Copyright © 2006 by ASME

1,503 citations