Abstract: This paper addresses the difficulty of the previously developed Adaptive Response Surface Method (ARSM) for high-dimensional design problems. ARSM was developed to search for the global design optimum for computation-intensive design problems. This method utilizes Central Composite Design (CCD), which results in an exponentially increasing number of required design experiments. In addition, ARSM generates a complete new set of CCD points in a gradually reduced design space. These two factors greatly undermine the effciency of ARSM. In this work, Latin Hypercube Design (LHD) is utilized to generate saturated design experiments. Because of the use of LHD, historical design experiments can be inherited in later iterations. As a result, ARSM only requires a limited number of design experiments even for high-dimensional design problems. The improved ARSM is tested using a group of standard test problems and then applied to an engineering design problem. In both testing and design application, significant improvement in the efficiency of ARSM is realized. The improved ARSM demonstrates strong potential to be a practical global optimization tool for computation-intensive design problems. Inheriting LHD points, as a general sampling strategy, can be integrated into other approximation-based design optimization methodologies.

Abstract: Research was undertaken to understand how to provide the most appropriate support for novice designers in engineering design. However, how designers apply their experience and knowledge is not understood and further research in this area is required. This paper describes an observational study to understand how novice and experienced designers approach design tasks.

Abstract: Software engineering is a human task, and as such we must study what software engineers do and think. Understanding the normative practice of software engineering is the first step toward developing realistic solutions to better facilitate the engineering process. We conducted three studies using several data-gathering approaches to elucidate the patterns by which software engineers (SEs) use and update documentation. Our objective is to more accurately comprehend and model documentation use, usefulness, and maintenance, thus enabling better decision making and tool design by developers and project managers. Our results confirm the widely held belief that SEs typically do not update documentation as timely or completely as software process personnel and managers advocate. However, the results also reveal that out-of-date software documentation remains useful in many circumstances.

Abstract: Metamodeling techniques have been widely used in engineering design to improve efficiency in the simulation and optimization of design systems that involve computationally expensive simulation programs. Many existing applications are restricted to deterministic optimization. Very few studies have been conducted on studying the accuracy of using metamodels for optimization under uncertainty. In this paper, using a two-bar structure system design as an example, various metamodeling techniques are tested for different formulations of optimization under uncertainty. Observations are made on the applicability and accuracy of these techniques, the impact of sample size, and the optimization performance when different formulations are used to incorporate uncertainty. Some important issues for applying metamodels to optimization under uncertainty are discussed.

Abstract: The field of evolutionary robotics has demonstrated the ability to automatically design the morphology and controller of simple physical robots through synthetic evolutionary processes. However, it is not clear if variation-based search processes can attain the complexity of design necessary for practical engineering of robots. Here, we demonstrate an automatic design system that produces complex robots by exploiting the principles of regularity, modularity, hierarchy, and reuse. These techniques are already established principles of scaling in engineering design and have been observed in nature, but have not been broadly used in artificial evolution. We gain these advantages through the use of a generative representation, which combines a programmatic representation with an algorithmic process that compiles the representation into a detailed construction plan. This approach is shown to have two benefits: it can reuse components in regular and hierarchical ways, providing a systematic way to create more complex modules from simpler ones; and the evolved representations can capture intrinsic properties of the design space, so that variations in the representations move through the design space more effectively than equivalent-sized changes in a nongenerative representation. Using this system, we demonstrate for the first time the evolution and construction of modular, three-dimensional, physically locomoting robots, comprising many more components than previous work on body-brain evolution.

Abstract: Co-evolutionary design has been developed as a computational model that assumes two parallel search spaces: the problem space and the solution space The design process iteratively searches each space using the other space as the basis for a fitness function when evaluating the alternatives Co-evolutionary design can also be developed as a cognitive model of design by characterizing the way in which designers iteratively search for a design solution, making revisions to the problem specification This paper presents the computational model of co-evolutionary design and then describes a protocol study of human designers looking for evidence of co-evolution of problem specifications and design solutions The study shows that co-evolutionary design is a good cognitive model of design and highlights the similarities and differences between the computational model and the cognitive model The results show that the two kinds of co-evolutionary design complement each other, having strengths in different aspects of the design process

Abstract: Self-Organizing Maps (SOMs) have been used to visualize tradeoffs of Pareto solutions in the objective function space for engineering design obtained by Evolutionary Computation. Furthermore, based on the codebook vectors of cluster-averaged values of respective design variables obtained from the SOM, the design variable space is mapped onto another SOM. The resulting SOM generates clusters of design variables, which indicate roles of the design variables for design improvements and tradeoffs. These processes can be considered as data mining of the engineering design. Data mining examples are given for supersonic wing design and supersonic wing-fuselage design.

Abstract: Our research is motivated by the need for developing an approach to demand modeling that is critical for assessing the profit a product can bring under the decision-based design framework. Even though demand modeling techniques exist in market research, little work exists on demand modeling that addresses the specific needs of engineering design, in particular, that facilitates engineering decision making. In this work, we enhance the use of discrete choice analysis to demand modeling in the context of decision-based design. The consideration of a hierarchy of product attributes is introduced to map customer desires to engineering design attributes related to engineering analyses. To improve the predictive capability of demand models, the Kano method is employed to provide econometric justification when selecting the shape of the customer utility function. A (passenger) vehicle engine case study, developed in collaboration with the market research firm, J. D. Power & Associates, and the Ford Motor Company, is used to demonstrate the proposed approaches.

Abstract: The primary hypothesis of this paper is that internal and external changes in design and manufacturing organizations affect the viability of boundary objects (representations, drawings, models – virtual and physical) and require changes in the underlying distributed cognitive models. Internal and external factors include new advances in technologies, insights into organizational processes, organizational restructuring and change of market focus. If the above hypothesis is true, then there are consequences for the methodologies of designing computational support systems for co-operative engineering work. We provide evidence by describing three empirical studies of engineering design we have performed in large organizations. We investigate how changing technologies disrupt the common grounds among interfaces and how this opens debate on the role of boundary objects, especially in the product visualization and analysis arena. We then argue that changes in market forces and other factors leading to changes in organizational structures often lead to erosion of common understanding of representations and prototypes, above all at the interfaces. We conclude by making the case that every structural and information flow change in engineering organizations is accompanied by the potential deterioration of the common ground. This requires the synthesis of new common grounds to accommodate the needs of new interfaces.

Abstract: An important bottleneck in model-based design of embedded systems is the cost of constructing models. This cost can be significantly decreased by increasing the reuse of existing model components in the design process. This paper describes a tool suite, which has been developed for component-based model synthesis. The DESERT tool suite can be interfaced to existing modeling and analysis environments and can be inserted in various, domain specific design flows. The modeling component of DESERT supports the modeling of design spaces and the automated search for designs that meet structural requirements. DESERT has been introduced in automotive applications and proved to be useful in increasing design productivity.

Abstract: This paper describes the integration of cognitive analysis into the early stages of design of a new, large-scale system--a next generation US Navy Surface combatant. Influencing complex system designs in ways cognizant of human-system integration principles requires work products that are timely and tightly coupled to other elements of the design process. Because analyses were conducted simultaneously with the design processes regarding ship functionality and staffing, it was necessary to select and adapt cognitive work analysis methods to fit the demands of a time pressured and information-limited design situation. Interviews were conducted and analyzed based on aspects of an abstraction hierarchy and control task models. An abstraction hierarchy, a series of cross-linked matrices, and a set of decision ladder models were developed to provide a principled mapping between system function decompositions produced by system engineering teams and cognitive tasks, information needs, automation requirements, and concepts for displays. Cross-referencing the matrices supported design traceability and facilitated the integration of cognitive analyses with functional analyses being performed by other design teams. Results fed into design recommendations with respect to level of automation, human roles and initial display prototypes for the ship combat command center. The case study illustrates the utility of cognitive work analysis models (specifically, abstraction hierarchies and decision-ladder models) in the design of large-scale, first-of-a-kind systems, and presents new design artifacts that link concepts used in cognitive analyses to those used in systems engineering for more effective integration within the systems engineering process.

Abstract: This paper is concerned with approximations for expensive function evaluation – the expensive functions arising in an engineering design context The problem of reducing the computational cost of generating sufficient learning samples is addressed Several approaches of using a priori knowledge to achieve computational economy are presented In all these, the results of a cheap model are treated as knowledge to be incorporated in the training process Several approaches are described here: in particular, we focus on neural based systems This approach is then developed as a new knowledge-based kriging model which is shown to be as accurate as neural based alternatives while being much easier to train Examples from the domain of structural optimization are given to demonstrate the approach

Abstract: Apparatus and methods for integrated circuit (IC) design, including management of the configuration, design parameters, and functionality of a design in which custom instructions or other design elements may be controlled by the designer. In one exemplary embodiment, a computer program rendered in an object-oriented language implementing the aforementioned methods for designing user-customized digital processors is disclosed. Design iteration, component encapsulation, use of human-readable file formats, extensible dynamic GUIs and tool sets, and other features are employed to enhance the functionality and accessibility of the program. Components within the design environment comprise encapsulated objects which contain information relating to interfaces with other components in the design, hierarchy, and other facets of the design process.

Abstract: The decision sciences have emerged over the past 300 years with contributions from many highly recognized individuals. Yet, by and large, these results have not been incorporated into engineering design decision methods, nor have these methods been validated. The result is that design decision methods commonly exhibit undesirable behaviors that are clearly evident when one knows what to look for. Indications of bad behavior are presented, and a framework for validation of engineering design alternative selection methods is suggested.

Abstract: Many companies find it difficult to maintain commonality and economies of scale in products with strict customer design requirements that may vary greatly from contract-to-contract or piece-to-piece. These strict and varied requirements typically result in highly customized products that are costly to manufacture, involve small production runs, and require long delivery times. In this paper, we discuss how the strategic incorporation of product platforms into the design process can leverage the design effort of individually customized products. The example involves the design of cross-sections for yokes used to mount valve actuators in the nuclear power industry. Through this example we demonstrate the process of creating a market segmentation grid, choosing a targeted segment, creating a product platform for the yoke cross-section, and subsequently defining the yoke product family using the product platform concept exploration method. The end result is a platform-based product family that will improve response to customer requests, reduce design and manufacturing costs, and improve time to market for companies that make small production runs of highly customized products.

Abstract: Optimization principles are often used in engineering design activities for finding solutions which cannot be bettered. The use of a single objective for design usually results in only one optimum solution, whereas the consideration of multiple conflicting objectives results in a number of trade-off Pareto-optimal solutions. Investigating the Pareto-optimal solutions for any similarity or relationship among their design variables may provide vital design principles, which may not be possible to obtain by any other means. This paper illustrates the concept of optimization in the presence of multiple conflicting objectives and then presents one multi-objective optimization algorithm based on evolutionary algorithms. Thereafter, a number of engineering design optimization case studies are presented to first find a set of Pareto-optimal solutions and then analyze them to unveil important design principles which would be of great importance to a designer. The breadth of case studies considered in this paper an...

Abstract: In an effort to improve customization for today’s highly competitive global marketplace, many companies are utilizing product families to increase variety, shorten lead-times, and reduce costs. The key to a successful product family is the product platform from which it is derived either by adding, removing, or substituting one or more modules to the platform or by scaling the platform in one or more dimensions to target specific market niches. This nascent field of engineering design research has matured rapidly in the past decade, and this paper provides an extensive review of the research activity that has occurred during that time to facilitate product platform design and optimization. Techniques for identifying platform leveraging strategies within a product family are reviewed along with optimization-based approaches to help automate the design of a product platform and its corresponding family of products. Examples from both industry and academia are presented throughout the paper to highlight the benefits of platform-based product development, and the paper concludes with a discussion of promising research directions to help bridge the gap between planning and managing families of products and designing and manufacturing them.Copyright © 2003 by ASME

Abstract: The migration to using ultra deep submicron (UDSM) process, 0.25 /spl mu/m or below, necessitates new design methodologies and EDA tools to address the new design challenges. One of the main challenges is noise. All different types of deep submicron such as cross talk, leakage, supply noise and process variations are obstacles in the way of achieving the desired level of noise immunity without giving up the improvement achieved in performance and energy efficiency. This article describes research directions and various levels of design abstraction to handle the interconnect challenges. These directions include approaches to adopt new analytical methods for interconnects, physical design levels and finally ways to face these challenges early in a higher level of the design process.

Abstract: Numerous design methods exist but models and tools used by these design methods do not realize a complete coherence between customers' needs, professionals' needs and solutions that can be found. So, in this paper we will examine the functional analysis method that was specifically developed to allow needs to be taken into account during the design stages. We will present our interpretation of that method and how it could serve to assure this coherence. We will put forward a design activities model, integrating into the design process the needs of those involved in the product life-cycle. Our observations relative to the implementation of the functional analysis method will lead us to supplement this initial model and suggest tools to help designers.

Abstract: This paper explores the experiences of engineering, design and construction organizations (EDOs) in developing innovative approaches to performance measurement in their design activities. It contrasts experiences of these firms with those of manufacturing organizations. It finds that performance measurement of engineering design activities is poorly understood in many industries, including construction. The development of new performance measures can provide a new opportunity for innovation in engineering, design and construction firms. At present, the measures used to assess design in construction are based on the financial performance of a project rather than other important objectives of the design process, such as quality and buildability. In manufacturing industries, firms rely on measures of new product development, but these indicators also say little about the measurement of engineering design activities, that is, those on‐going and continuous. To realize the innovative potential of design and per...

Abstract: Rapid manufacturing (RM) employs similar technologies and processes to rapid prototyping (RP), hence resulting in a tool-less manufacturing process. This is achieved by assuming that RP machines have been converted to proper manufacturing machines. The current approaches to the design process, product development cycle and manufacturing considerations at the design stage within a concurrent engineering environment are closely examined. An attempt is then made to investigate the effect of the RM processes on the design process and product development cycle. This is further expanded to consider the impact of RM on rules and guidelines that have been established for design for manufacturing (DFM). This paper is limited to a comparison of RM with regards to injection moulding as RM is most likely to compete with this process in the first instance. This is the first research work to investigate the impact of RM on the design process.

Abstract: This paper presents a new application of Failure Modes and Effects Analysis (FMEA) on product development processes. Our research develops error-proofing methods for product development processes to prevent serious design errors that compromise project features, time, or cost. Design process FMEA categorizes design errors in six areas: knowledge, analysis, communication, execution, change, and organization errors. The paper explains the method, illustrates it with an example, and discusses its effectiveness. The paper concludes with the proposed work to address the existing lack of a systematic approach to design process error-proofing.Copyright © 2003 by ASME

Abstract: "Human Behaviour in Design" adresses important aspects of creative engineering design. The main topics are the interaction between two complementary modalities - "image" and "concept", internal and external components of design thinking, and design strategies - both for individual designers and design teams. The goal is to improve and evaluate tools and methods that support design. Although this book is the outcome of an international workshop held in March 2003, it is more than just a collection of its contributions. The papers are arranged into three main topics: Individual Thinking and Acting; Interaction between Individuals; Methods, Tools and Prerequisites. There are summaries of the discussions of the respective topics written by the chairpersons, conclusions, and an outlook to future issues in design research.