Despite the benefits offered by offsite construction, as a percentage, the offsite market is still relatively small. This phenomena is complex; but for brevity, includes a myriad of factors, not least: lack of awareness; supply chain challenges (capacity and knowledge); cultural perception; lack of viable business process models/solutions; and paucity of skills (design/manufacturing/construction). However, many governments are still promoting the offsite agenda through various conduits. Given this, a CIB Task Group (TG74) developed a research roadmap for new production and business models for the construction industry uptake. This paper summarises the work of TG74, where people, process and technology drivers were investigated for construction, manufacturing and design and mapped against three levels of priority and three timeframes. Results indicate that for people drivers, new skills are urgently needed in the design field within a 0–5 year timeframe (compared to a timeframe of 6–10 years for the manufacturing sector). Regarding process drivers, construction process was classed as high priority, followed by design process and manufacturing process. Finally, for technology drivers, construction technology was identified as being high priority, followed by design technology and manufacturing technology, all of which need to be addressed in the medium term. This study presents a roadmap for future uptake.

New offsite production and business models in construction: priorities for the future research agenda

This paper describes a new approach to automate the classification of solid models using machine learning techniques. Existing approaches, based on group technology, fixed matching algorithms or pre-defined feature sets, impose a priori categorization schemes on engineering data or require significant human labeling of design data. This paper describes a shape learning algorithm and a general technique for "teaching" the algorithm to identify new or hidden classifications that are relevant in many engineering applications. In this way, the core shape learning algorithm can be used to find a wide variety of model classifications based on user input and training data. This allows for great flexibility in search and data mining of engineering data.

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Automated learning of model classifications

A great challenge in information visualization today is to provide models and software that effectively integrate the graphics content of scenes with domain-specific knowledge so that the users can effectively query, interpret, personalize and manipulate the visualized information [1]. Moreover, it is important that the intelligent visualization applications are interoperable in the semantic web environment and thus, require that the models and software supporting them integrate state-of-the-art international standards for knowledge representation, graphics and multimedia. In this paper, we present a model, a methodology and a software framework for the semantic web (Intelligent 3D Visualization Platform - I3DVP) for the development of interoperable intelligent visualization applications that support the coupling of graphics and virtual reality scenes with domain knowledge of different domains. The graphics content and the semantics of the scenes are married into a consistent and cohesive ontological model while at the same time knowledge- based techniques for the querying, manipulation, and semantic personalization of the scenes are introduced. We also provide methods for knowledge driven information visualization and visualization- aided decision making based on inference by reasoning.

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Coupling Ontologies with Graphics Content for Knowledge Driven Visualization

In order to facilitate product realisation processes, presently, research is actively being carried out to develop methodologies and technologies to support geographically dispersed teams to organi...

State-of-the-art technologies and methodologies for collaborative product development systems

Information security and assurance are new frontiers for collaborative design. In this context, information assurance (IA) refers to methodologies to protect engineering information by ensuring its availability, confidentiality, integrity, non-repudiation, authentication, access control, etc. In collaborative design, IA techniques are needed to protect intellectual property, establish security privileges and create “need to know” protections on critical features. Aside from 3D watermarking, research on how to provide IA to distributed collaborative engineering teams is largely non-existent. This paper provides a framework for information assurance within collaborative design, based on a technique we call role-based viewing, in which information security relationships are roles assigned to users based on their permissions and privileges. Role-based viewing is achieved through integration of multi-resolution geometry and with the security model. In this way, 3D models are geometrically partitioned, and the partitioning is used to create multi-resolution mesh hierarchies that obscure, obfuscate, or remove sensitive material from the view of users without appropriate permissions. This approach is the basis for our prototype system FACADE (the Framework for Access-control in Computer-Aided Design Environments), a synchronous, multi-user collaborative modeling environment. In FACADE, groups of users worked in a shared 3D modeling environment in which each user viewing and modeling privileges are managed by a central access control mechanism. In this manner, individual actors see only the data they are allowed to see, at the level of detailed they are permitted to see it.

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Role-Based Viewing Envelopes for Information Protection in Collaborative Modeling

This article presents an approach to collaborative authoring of design semantics within a multiuser 3D environment. Our research unites ideas from traditional engineering design with recent work from the Semantic Web and knowledge engineering community. The system we present, Multiuser Groups for Conceptual Understanding and Prototyping (MUG), serves as our research platform. it lets a team of designers-collaborating over the Internet in a shared, multimodal, 3D workspace-model a 3D layout and semantically grounded behavioral description of a product or device.

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Y. Shapirstein

Papers

A collaborative 3D environment for authoring design semantics