A selection method to support adaptive reuse of parametric finite element analysis (FEA) models is introduced in this paper. Adaptive reuse of engineering artifacts such as FEA models is common in product design, but difficult to automate because of the need to integrate new information. The proposed method factors reusability into selection by evaluating models based on comparative estimates of effort involved in adapting them for reuse to model a query problem. The method is developed for FEA models of component-based designs. FEA modeling of electronic chip packages is used to illustrate the method's usefulness. We conclude with a discussion on the method's advantages and limitations and highlight important issues for further research.

This paper presents a comparison of two previous and separate efforts to develop an ontology in the engineering design domain, together with an ontology proposal from which ontologies for a specific application may be derived. The research contrasts an empirical, user-centered approach to developing the ontology engineering design integrated taxonomies (EDIT) with a theoretical approach in which concepts and relations are elicited from engineering design theories design ontology (DO). The limitations and advantages of each approach are discussed. The research methodology adopted is to map the ontology through examining each of the concepts and relations contained within each of the ontologies DO and EDIT with respect to the other. The comparison process results in an examination of both ontologies, with a few changes resulting from this. The importance of the two different approaches, one that is theoretically sound and another that is applicable, is recognized and argued. Finally, the merged ontology for engineering design is proposed as a template ontology that can be tailored by researchers and practitioners for a specific context.

This paper presents our research on developing an ontology-based framework that can represent morphological characteristics related to assembly joints. Joints within the physical structure of an assembly are inevitable because of the limitations of component geometries and the associated, required engineering properties. Consequently, a framework is needed that can capture and propagate assembly design and joint information in a robust assembly model throughout the entire product development processes. The framework and model are based on an understanding of the morphological characteristics of an assembly and its different physical effects. The morphological characteristics are consequences of the principal physical processes and of the design intentions. Therefore, the morphological characteristics should be carefully represented while considering the geometry and topology of assembly joints. In this research, assembly joint topology is defined by a mereotopology, which is a region-based theory for the parts and associated concepts. This formal ontology can differentiate often ambiguous assembly and joining relations. Furthermore, the mereotopological definitions for assembly joints are implemented in Semantic Web Rule Language (SWRL) rules and Web Ontology Language triples. This process provides universality to the mereotopological definitions. Two geometrically and topologically similar joint pairs are presented to describe how the assembly joints can be defined in mereotopology and be transformed into SWRL rules. Web3D is also employed to support network-enabled sharing of assembly geometry. Finally, the proposed modeling framework is demonstrated using a real fixture assembly. This case study demonstrates the usability of the proposed framework for network-based design collaboration.

Industrial designers make sketches and physical models to start and develop ideas and concept designs. Such representations have advantages that they support fast, intuitive, rich, sensory exploration of solutions. Although existing tools and techniques provide adequate support where the shape of the product is concerned, the exploration of surface qualities such as material and printed graphics is supported to a much lesser extent. Moreover, there are no tools that have the fluency of sketching that allow combined exploration of shape, material, and their interactions. This paper evaluates Skin, an augmented reality tool designed to solve these two shortcomings. By projecting computer-generated images onto the shape model Skin allows for a “sketchy” tangible interaction where designers can explore surface qualities on a three-dimensional physical shape model. The tool was evaluated in three design situations in the domain of ceramics design. In each case, we found that the joint exploration of shape and surface provided creative benefits in the form of new solutions; in addition, a gain in efficiency was found in at least one case. The results show that joint exploration of shape and surface can be effectively supported with tangible augmented reality techniques and suggest that this can be put to practical use in industry today.

When designing a product, the earlier the potential risks can be identified, the more costs can be saved, as it is easier to modify a design in its early stages. Several methods exist to analyze the risk in a system, but all require a mature design. However, by applying the concept of “common interfaces” to a functional model and utilizing a historical knowledge base, it is possible to analyze chains of failures during the conceptual phase of product design. This paper presents a method based on these common interfaces to be used in conjunction with other methods such as risk in early design to allow a more complete risk analysis during the conceptual design phase. Finally, application of this method is demonstrated in a design setting by applying it to a thermal control subsystem.

Ontologies have been successfully applied as a semantic enabler of communication between both users and applications in fragmented, heterogeneous multinational business environments. In this paper we discuss the underlying principles, their current implementation status, and most importantly, their applicability to problems in the building information modeling domain. We introduce the development of an ontology for the building and construction sector based on the industry foundation classes. We discuss several approaches of lifting modeling information that is based on the express family of languages for data modeling onto a logically rigid and semantically enhanced ontological level encoded in the W3C Ontology Web Language. We exemplify the added value of such formal notation of building models by providing several examples where generic query and reasoning algorithms can be applied to problems that otherwise have to be manually hard-wired into applications for processing building information. Furthermore, we show how the underlying resource description framework and the set of technologies evolving around it can be tailored to the need of distributed collaborative work in the building and construction industry.

The use of tangible objects is paramount in industrial design. Throughout the design process physical prototypes are used to enable exploration, simulation, communication, and specification of designs. Although much is known about prototyping skills and technologies, the reasons why and how such models are employed in design practice are poorly understood. Advanced techniques and design media such as virtual and augmented prototyping are being introduced without insight as to their benefits. We believe that an augmented prototyping system, that is, employing augmented reality technology to combine physical and digital representations, could positively influence the design process. However, we lack knowledge on why and how it might facilitate design. This paper reports on case studies performed in different domains of industrial design. At each of three Dutch design offices, a project was followed with particular attention to physical prototyping and group activities. The projects encompassed information appliance design, automotive design, and interior design. Although the studies vary in many aspects (product domain, stakeholders, duration), the findings can be applied in conceptualizing advanced prototyping systems to support industrial design. Furthermore, the data reveal that the roles of a prototype in current practice are not necessarily utilitarian; for example, the prototype may serve as a conversation piece or as seducer. Based on so-called “hints,” bottlenecks and best practices concerning concept articulation are linked to usage scenarios for augmented tangible prototyping. The results point to modeling and communication scenarios. Detailed study of the cases indicates that communication activities, especially design reviews, would benefit most from interactive augmented prototyping.

We present an alternative video-making framework for children with tools that integrate video capture with movie production. We propose different forms of interaction with physical artifacts to capture storytelling. Play interactions as input to video editing systems assuage the interface complexities of film construction in commercial software. We aim to motivate young users in telling their stories, extracting meaning from their experiences by capturing supporting video to accompany their stories, and driving reflection on the outcomes of their movies. We report on our design process over the course of four research projects that span from a graphical user interface to a physical instantiation of video. We interface the digital and physical realms using tangible metaphors for digital data, providing a spontaneous and collaborative approach to video composition. We evaluate our systems during observations with 4- to 14-year-old users and analyze their different approaches to capturing, collecting, editing, and performing visual and sound clips.

Most past approaches to data mining have been based on association rules. However, the simple application of association rules usually only changes the user's problem from dealing with millions of data points to dealing with thousands of rules. Although this may somewhat reduce the scale of the problem, it is not a completely satisfactory solution. This paper presents a new data mining technique, called knowledge cohesion (KC), which takes into account a domain ontology and the user's interest in exploring certain data sets to extract knowledge, in the form of semantic nets, from large data sets. The KC method has been successfully applied to mine causal relations from oil platform accident reports. In a comparison with association rule techniques for the same domain, KC has shown a significant improvement in the extraction of relevant knowledge, using processing complexity and knowledge manageability as the evaluation criteria.