I am very pleased to have been appointed to be the new Editor of the AIEDAM journal: only the third in its 15 years of existence. My involvement with AIEDAM started early in the life of the journal, due to my professional interactions with Professor Clive Dym, its first Editor. Clive put the journal on a very sound footing, and set the high standards that the journal continues to uphold. That it has maintained such a high reputation in the fields that it covers is due to Professor William Birmingham, the second Editor. My goal is to continue with the policies developed by these two prior Editors, while striving to raise the journal's standards, reputation, and visibility even further.

Some historical and current trends in reflective practice (RP), artificial intelligence (AI), and engineering design (ED) are presented and compared. Human artistry, context, and connectionist approaches to knowledge are the common threads highlighted. ED is considered to be a type of RP and AI a part of RP. This is supported by an analysis of the transformation processes involved in each. AI and systems are presented as approaches for the formalization of RP at the technical and conceptual levels, respectively. Interconnectedness in a hierarchical fashion and purposeful process loops are defined as the key ingredients of a systems approach. AI techniques that could support a range of ED categories (case-based reasoning, decomposition, and transformation) are identified, as are the wider RP approaches that subsume those categories. The ED, AI, and RP categories are identified as spanning from routine to creative, connectionist to cognitivist, and intuitive to deliberate, respectively.

Although the human–computer interaction (HCI) community has been active for several years, very little attention has been devoted to supporting engineers. Engineers are unique computer users with particular needs. They are familiar with fields such as applied mathematics, applied sciences, simulation, project management, technical drawing, and design, as well as engineering law and economics. The nature of the engineering design process means that engineers usually operate within changing environments. Uncertainty relating to incomplete information adds to the complexity of the process especially since the engineer is legally responsible for decisions.

This paper describes the use of software agents within an interactive evolutionary conceptual design system. Several different agent classes are introduced (search agents, interface agents, and information agents) and their function within the system is explained. A preference modification agent is developed and an example is given illustrating the use of agents in preference modeling.

Product definition is widely accepted as one of the key factors to be considered in the early stage of product design and development. It has a direct impact on the success of a new product in the marketplace. Frequently, product definition is solicited through the voice of the customer (VoC). As such, an organization will obtain a prominent competitive edge over its competitors if it is able to effectively capture the genuine VoC or the requirements of a customer. Sorting techniques provide a means to elicit customer requirements. Although a number of sorting techniques were developed, few of them are able to handle the uncertainty and imprecision inherited from the VoC and subjective judgment because of their crisp decision making. An integrated approach is described, which is based on repeated single-criterion sorts and fuzzy evaluation, for the elicitation of customer requirements. The details of the integrated approach are presented. The approach is validated using a case study on the design of a wooden golf-club head. The details of the validation are discussed.

Managing and reusing knowledge in architecture, engineering, and construction firms can lead to greater competitive advantage, improved designs, and more effective management of constructed facilities. However, reuse often fails because knowledge is not captured; it is captured out of context, rendering it not reusable; or there are no formal mechanisms for finding and retrieving reusable knowledge. This paper presents ongoing research on design knowledge reuse that introduces the notion of knowledge in context from a corporate perspective. We argue that in order for knowledge to be reusable, the user should be able to see the rich context in which this knowledge was originally created and interact with it. We call a repository of such knowledge in context the corporate memory. We describe empirical observations of designers reusing knowledge from their personal design experiences. Based on these observations, we formalize two key activities in the process of knowledge reuse from a corporate repository: finding reusable items and understanding these items in context. We formalize six degrees of exploration that lead to understanding. We describe a prototype system, CoMem, that supports these activities. CoMem is distinguished from the document-centric state of practice solutions by its approach of “overview first, zoom and filter, and then details on demand.” In order to accomplish this approach we propose three metaphors: corporate map, fisheye lens, and storyteller. These metaphors and their implementation in CoMem are illustrated using an industry scenario.

A framework for a design tool based on shape grammars is presented as an effective means for supporting the early stages of design. The framework uses a shape grammar interpreter to implement parametric shape grammars, allowing the grammar to be used interactively by a designer or optimization routine. A shape grammar to design inner hood panels of vehicles is introduced as an example of a parametric engineering shape grammar, and it is used with the framework to create standard and novel designs made possible by rules that take advantage of shape emergence.

Knowledge management has recently become the focus of public attention in business and engineering. Because knowledge acquisition is situated in the upstream of knowledge management, capturing knowledge is an important step for enterprises to achieve successful knowledge management. We focus on how engineers solve their design problems under given design contexts and propose a novel model and methods to capture knowledge from engineering design processes. Our goal is to acquire know-how knowledge without disrupting the normal design process. A three-layer design process model is introduced to represent generic design processes, and a grammar and extended dynamic programming (GEDP) method is developed based on the process model. GEDP adopts the grammar approach and EDP to automatically identify meaningful clusters, called operations, from primitive design events. Our approach is evaluated through a case study of designing a double-reduction gear system.

This paper investigates the use of typological knowledge in the visual modality through a computer framework that combines multidisciplinary technologies from computer science, that is, artificial intelligence, software engineering, database system, and programming language, to help provide solutions and services to building designers. The solving of design problems frequently involves visual thinking, which has to do with the intensive use of visual knowledge like pictures, images, and other types of visual displays. The recognized power of typological knowledge in design problem solving is applied to support the exploration of a diversity of possible design solutions represented in a pictorial mode. The innovative use of computer science technologies enables a smooth link of visual typological knowledge with the design goals. Within the framework, a core technology was designed to respond to a designer's specific needs through dynamic user viewpoint generation, so that design solutions are associated with relevant (retrieved) visual typologies from the knowledge base. This has been achieved in a two-way process, in which the designer establishes an interactive dialogue with an experimental computerized framework.

Conceptual design seeks to deliver design concepts that implement desired functions. Function and behavior are two dominant terms used in the research of this design phase. However, there are still some fundamental ambiguities and confusions over their representation, which have greatly hindered the interchange of research ideas and the development of design synthesis strategies. For conceptual design of mechanical products specifically, this paper attempts to clarify these ambiguities. It classifies function as purpose function and action function and relates them to the different levels of design hierarchy and abstraction. It distinguishes between semantic and syntactic representations of function and behavior and summarizes basic representation schemes. It also proposes an input–output action transformation scheme for semantic function representation and an input–output flow of action scheme for semantic behavior representation. Based on these discoveries, a refined framework is proposed for conceptual mechanical product design, where a function–decomposition–mapping process is elaborated to demonstrate the necessities and usefulness of the presented work.

Architects use sketching and diagramming in their design process to perform functional reasoning, formal arrangements, analogy transfer, structure mapping, and knowledge acquisition. This paper describes a research framework of the author's efforts in the studies of design drawings and the building of computational sketching tools to support the early conceptual design process in architecture. The first part of the paper discusses empirical studies conducted to determine or guess a designer's thought process from sketches and thus identifies domain-specific graphical symbols. It proposes a reasoning process framework of drawing marks, acts, and reacts. The second part of the paper illustrates how design support tools could be developed based on these concepts and describes the various applications of the study, such as indexing and retrieving of design drawings or images based on the recognition of geometric shapes and the spatial relationships among them.

Under the concept of a global economy, enterprises are assigning design and production environments around the world in different areas. A serious issue of information exchange emerges as companies use traditional hardware and very distinct software appropriate to their field of expertise. To overcome the problem of low productivity due to the interruption of information, the concept of simultaneous engineering and concurrent design becomes very significant. In this article an agent-based ship design system is developed to support cooperation in distributed ship design environments. Above all, the conflicts that occur while sharing knowledge in the system must be resolved. One approach is to adopt a case-based conflict resolution strategy formulated to resolve current conflict on the basis of similar previously resolved cases in agent-based collaborative design system environments. To do this, conflict cases that occur in the initial ship design stage are extracted. On the basis of the extracted cases, a case base is constructed. In addition, a conflict resolution handler located in the superagent called a facilitator, an agent to control other subagents, is developed to treat conflict problems effectively by case-based reasoning. The case-based conflict resolution strategy is evaluated by applying it to a collaborative design process in the initial ship design stage, especially the machinery outfitting design, the preliminary design, the hullform design, and the structural design. Through the help of the collaboration of the design agents, the facilitator, the conflict resolution handler, and the case-based system, a designer can make decisions based on similar previously resolved cases.

Probabilistic and stochastic algorithms have been used to solve many hard optimization problems since they can provide solutions to problems where often standard algorithms have failed. These algorithms basically search through a space of potential solutions using randomness as a major factor to make decisions. In this research, the knapsack problem (optimization problem) is solved using a genetic algorithm approach. Subsequently, comparisons are made with a greedy method and a heuristic algorithm. The knapsack problem is recognized to be NP-hard. Genetic algorithms are among search procedures based on natural selection and natural genetics. They randomly create an initial population of individuals. Then, they use genetic operators to yield new offspring. In this research, a genetic algorithm is used to solve the 0/1 knapsack problem. Special consideration is given to the penalty function where constant and self-adaptive penalty functions are adopted.

We describe an approach that uses causal and geometric reasoning to construct explanations for the purposes of the geometric features on the parts of a mechanical device. To identify the purpose of a feature, the device is simulated with and without the feature. The simulations are then translated into a “causal-process” representation, which allows qualitatively important differences to be identified. These differences reveal the behaviors caused and prevented by the feature and thus provide useful cues about the feature's purpose. A clear understanding of the feature's purpose, however, requires a detailed analysis of the causal connections between the caused and prevented behaviors. This presents a significant challenge because one has to understand how a behavior that normally takes place affects (or is affected by) another behavior that is normally absent. This article describes techniques for identifying such elusive relationships. These techniques employ a set of rules that can determine if one behavior enables or disables another that is spatially and temporally far away. They do so by geometrically examining the traces of the causal processes in the device's configuration space. Using the results of this analysis, our program can automatically generate text output describing how the feature performs its function.

Product development involves multiple phases. Design review (DR) is an essential activity formally conducted to ensure a smooth transition from one phase to another. Such a formal DR is usually a multicriteria decision problem, involving multiple disciplines. This paper proposes a systematic framework for DR using fuzzy set theory. This fuzzy approach to DR is considered particularly relevant for several reasons. First, information available at early design phases is often incomplete and imprecise. Second, the relationships between the product design parameters and the review criteria cannot usually be exactly expressed by mathematical functions due to the enormous complexity. Third, DR is frequently carried out using subjective expert judgments with some degree of uncertainty. The DR is defined as the reverse mapping between the design parameter domain and design requirement (review criterion) domain, as compared with Suh's theory of axiomatic design. Fuzzy sets are extensively introduced in the definitions of the domains and the mapping process to deal with imprecision, uncertainty, and incompleteness. A simple case study is used to demonstrate the resulting fuzzy set theory of axiomatic DR.

Solid models are the critical data elements in modern computer-aided design environments, because they describe the shape and form of manufactured artifacts. Their growing ubiquity has created new problems in how to effectively manage the many models that are now stored in the digital libraries for large design and manufacturing enterprises. Existing techniques from the engineering literature and industrial practice, such as group technology, rely on human-supervised encodings and classification; techniques from the multimedia database and computer graphics/vision communities often ignore the manufacturing attributes that are most significant in the classification of models. This paper presents our approach to comparing the manufacturing similarity assessments of solid models of mechanical parts based on machining features. Our technical approach is threefold: perform machining feature extraction, construct a model dependency graph (MDG) from the set of machining features, and partition the models in a database using a measure of similarity based on the MDGs. We introduce two heuristic search techniques for comparing MDGs and present empirical experiments to validate our approach using our testbed, the National Design Repository.

This paper proposes a new logical framework for vehicle route-sequence planning of passenger travel requests. Each request is a fetch-and-send service task associated with two request-locations, namely, a source and a destination. The proposed framework is developed using propositional linear time temporal logic of Manna and Pnueli. The novelty lies in the use of the formal language for both the specification and theorem-proving analysis of precedence constraints among the location visits that are inherent in route sequences. In the framework, legal route sequences—each of which visits every request location once and only once in the precedence order of fetch-and-send associated with every such request—is formalized and justified, forming a basis upon which the link between a basic precedence constraint and the corresponding canonical forbidden-state formula is formally established. Over a given base route plan, a simple procedure to generate a feasible subplan based on a specification of the forbidden-state canonical form is also given. An example demonstrates how temporal logic analysis and the proposed procedure can be applied to select a final (feasible) subplan based on additional precedence constraints.

Engineering conceptual design can be defined as that phase of the product development process during which the designer takes a specification for a product to be designed and generates many broad solutions to it. This paper presents a constraint-based approach to supporting interactive conceptual design. The approach is based on an expressive and general technique for modeling: the design knowledge that a designer can exploit during a design project; the life-cycle environment that the final product faces; the design specification that defines the set of requirements the product must satisfy; and the structure of the various schemes that are developed by the designer. A computational reasoning environment based on constraint filtering is proposed as the basis of an interactive design support tool. Using such a tool, human designers can be assisted in interactively developing and evaluating a set of schemes that satisfy the various constraints imposed on the design.

Earlier research on product family design (PFD) often highlights isolated and successful empirical studies with a limited attempt to explore the modeling and design support issues surrounding this economically important class of engineering design problems. This paper proposes a graph rewriting system to organize product family data according to the underpinning logic and to model product derivation mechanisms for PFD. It represents the structural and behavioral aspects of product families as family graphs and related graph operations, respectively. The derivation of product variants becomes a graph rewriting process, in which family graphs are transformed to variant graphs by applying appropriate graph rewriting rules. The system is developed in the language of programmed graph rewriting systems or PROGRES, which supports the specification of hierarchical graph schema and parametric rewriting rules. A meta model is defined for family graphs to factor out those entities common to all product families. A generic model is defined to describe all specific entities relevant to particular families. An instance model describes all product variants for individual customer orders. A prototype of a graph-based PFD system for office chairs is also developed. The system can provide an interactive environment for customers to make choices among product offerings. It also facilitates design automation of product families and enhances interactions and negotiations among sales, design, and manufacturing.

Nearly all software products have rigid and predefined interfaces. Users are usually unable to modify or customize features beyond cosmetic aspects. Interface adaptability is important because aspects such as user preferences and task sequences vary widely in engineering, even within specialized domains. A methodology for the creation of adaptable user interfaces using model composition is presented in this paper. User interfaces are generated dynamically through the composition of model fragments that are stored in a fragment library. When fragments are linked to models of physical behavior, interface model composition applications are likely to be easier to extend and maintain than traditional graphical user interfaces. A prototype system within the domain of bridge diagnosis illustrates the potential for practical applications.