Susan Finger

A review of research in mechanical engineering design. Part I: Descriptive, prescriptive, and computer-based models of design processes

This is the first of a two part paper summarizing and reviewing research in mechanical engineering design theory and methodology. Part I includes: 1) descriptive models; 2) prescrptive models; and 3) computer-based models of design processes. Part II, which will appear in the next issue of this journal, will include: 4) languages, representations, and environments for design; 5) analysis in support of design; and 6) design for manufacture and the life-cycle. For each major area, we discuss the current topics of research and the state of the art, emphasizing recent significant advances. We also discuss the important open research issues in each area. The six categories are certainly not mutually exclusive nor even collectively exhaustive; however, some organization is necessary, and these categories have been effective in making sense of a body of research that is expending rapidly in many exciting and promising directions. The mechanical engineering design research community has made major advances over the last few years. The research community in mechanical engineering design has made significant progress not only in advancing our knowledge of design, but also in clarifying the research methods necessary to study design. Great progress is being made toward a better understanding of design, and hence toward better design tools.

A review of research in mechanical engineering design. Part II: Representations, analysis, and design for the life cycle

This is the second of a two-part paper summarizing and reviewing research in mechanical engineering design theory and methodology. Part I included 1) descriptive models; 2) prescriptive models; and 3) computer-based models of design processes. Part II includes: 4) languages, representations, and environments for design; 5) analysis in support of design; and 6) design for manufacture and the life cycle. For each area, we discuss the current topics of research and the state of the art, emphasizing recent significant advances. A final section is included that summarizes the six major areas and lists open research issues.

A Framework for Computational Design Synthesis: Model and Applications

The field of computational design synthesis has been an active area of research for almost half a century. Research advances in this field have increased the sophistication and complexity of the designs that can be synthesized, and advances in the speed and power of computers have increased the efficiency with which those designs can be generated. Some of the results of this research have begun to be used in industrial practice, yet many open issues and research challenges remain. This paper provides a model of the automated synthesis process as a context to discuss research in the area. The varied works of the authors are discussed as representative of the breadth of methods and results that exist under the field of computational design synthesis. Furthermore, some guidelines are presented to help researchers and designers find approaches to solving their particular design problems using computational design synthesis. DOI: 10.1115/1.2013289

Knowledge Intensive CAD

The ultimate goal of advanced computer-aided design technologies is to facilitate effective product design and manufacturing activities in industrial companies through the whole lifecycle of industrial products. A central means for achieving this long-term goal is turning various types of knowledge on industrial products, their manufacture, use, maintenance, and other life-cycle activities into a reusable resource for the company, and deploying the resulting life-cycle knowledge during product development and manufacture, particularly the early design stages. It is claimed that these two-knowledge capitalisation and knowledge deployment-are essential characteristics of a Knowledge-Intensive CAD environment. Based on this view, the paper will discuss some of the characteristics, issues, and challenges of knowledge-intensive CAD systems, and give a draft research agenda for future.

Rapid design and manufacture of wearable computers

dvances in computa-tional science and engi-neering have changedprofoundly both theartifacts we can realizeand the processes bywhich we realize them.This article looks at theimpact of these new technologies on the design ofwearable computers covering three main areas: newdesign tools and approaches, new manufacturingtechnologies, and new uses of information technolo-gies. We will show how we at the Engineering DesignResearch Center (EDRC) at Carnegie Mellon haveused the wearable computer project as a testbed inwhich to integrate research on rapid design and man-ufacturing. In our research, we have designed, manu-factured, and used our own tools as well as observingtheir use by others----where the tools include wearablecomputers, design analysis programs, and informa-tion organization tools. Through this process, wehave learned about design education and designpractice, and we have uncovered new issues fordesign research.

Bayesian computer-aided experimental design of heterogeneous scaffolds for tissue engineering

This paper presents a Bayesian methodology for computer-aided experimental design of heterogeneous scaffolds for tissue engineering applications. These heterogeneous scaffolds have spatial distributions of growth factors designed to induce and direct the growth of new tissue as the scaffolds degrade. While early scaffold designs have been essentially homogenous, new solid freeform fabrication (SFF) processes enable the fabrication of more complex, biologically inspired heterogeneous designs with controlled spatial distributions of growth factors and scaffold microstructures. SFF processes dramatically expand the number of design possibilities and significantly increase the experimental burden placed on tissue engineers in terms of time and cost. Therefore, we use a multi-stage Bayesian surrogate modeling methodology (MBSM) to build surrogate models that describe the relationship between the design parameters and the therapeutic response. This methodology is well suited for the early stages of the design process because we do not have accurate models of tissue growth, yet the success of our design depends on understanding the effect of the spatial distribution of growth factors on tissue growth. The MBSM process can guide experimental design more efficiently than traditional factorial methods. Using a simulated computer model of bone tissue regeneration, we demonstrate the advantages of Bayesian versus factorial methods for designing heterogeneous fibrin scaffolds with spatial distributions of growth factors enabled by a new SFF process.

Bayesian Surrogates Applied to Conceptual Stages of the Engineering Design Process

During the conceptual design stages, designers often have incomplete knowledge about the interactions among design parameters. We are developing a methodology that will enable designers to create models with levels of detail and accuracy that correspond to the current state of the design process. Thus, designers can create a rough surrogate model when only a few data points are available and then refine the model as the design progresses and more information becomes available. These surrogates represent the system response when limited information is available and when few realizations of experiments or numerical simulations are possible. This paper presents a covariance-based approach for building multistage surrogates in the conceptual design stages when bounds for the response are not available a priori. We test the methodology using a one-dimensional analytical function and a heat transfer problem with an analytical solution, in order to obtain error measurements. We then illustrate the use of the methodology in a thermal design problem for wearable computers. The surrogate model enables the designer to understand the relationships among the design parameters.

Models and abstractions in design

Abstract The use of abstractions and models helps designers to focus on interesting characteristics of a design and to simplify the complex relationship among behaviour and form. Designers create and utilize incomplete models which capture limited aspects of the designs behaviour. A designer might, for example, create a kinematic model, a stress model, or a geometric model at different stages in the design process. Designers create these abstract models of incomplete designs to test design decisions and to provide a framework for making design refinements The quality of the completed design depends on the ability of the designer to select useful abstractions, to use them to model the performance of the design, and to use the results of the evaluation to guide further design refinements. We review the evidence for the uses and effectiveness of abstractions in the design process. Based on these findings, we review how abstractions can be created and used during the design process.

A framework for representing design intent

Abstract This paper presents a framework for interactively capturing the history of a design process. This history includes not only ‘how’ but also ‘why’ the design evolves as its does. We discuss the components of this framework and the representation of the design history. An example in the domain of spatial layouts for small buildings demonstrates how the design history may be used to explain design decisions and to support changes to the design.

Concurrent design happens at the interfaces

Concurrent engineering is often viewed either from a technical point of view ― that is, as a problem that can be solved by creating and integrating computer-based tools - or from an organizational point of view ― that is, as a problem that can be solved by creating and reorganizing teams of designers. In this paper we argue that concurrent engineering requires both technical and organizational solutions, and we call the result concurrent design. We believe that the essence of concurrent design is the myriad of interactions that occur at the interfaces among all of the members of a design team and all their tools. Solving either the technical or organizational problems by assuming away the interactions will not solve the problems of concurrent design. In this paper we present two case studies of concurrent design in practice that have changed our assumptions about design and which have changed our research agenda. We also present the evolution of concurrent design research at the Carnegie Mellon Engineering Design Research Center. In our research, we have designed, manufactured, and used our own tools as well as observed their use by others-where the tools include mobile computers, design analysis programs, and information organization tools. Through this process, we have learned about design education and design practice, and we have uncovered new issues for design research. We see the interactions among design research, practice, and education as essential to understanding concurrent design