Product design is a highly involved, often ill-defined, complex and iterative process, and the needs and specifications of the required artifact get more refined only as the design process moves toward its goal. An effective computer support tool that helps the designer make better-informed decisions requires efficient knowledge representation schemes. In today's world, there is a virtual explosion in the amount of raw data available to the designer, and knowledge representation is critical in order to sift through this data and make sense of it. In addition, the need to stay competitive has shrunk product development time through the use of simultaneous and collaborative design processes, which depend on effective transfer of knowledge between teams. Finally, the awareness that decisions made early in the design process have a higher impact in terms of energy, cost, and sustainability, has resulted in the need to project knowledge typically required in the later stages of design to the earlier stages. Research in design rationale systems, product families, systems engineering, and ontology engineering has sought to capture knowledge from earlier product design decisions, from the breakdown of product functions and associated physical features, and from customer requirements and feedback reports. VR (Virtual reality) systems and multidisciplinary modeling have enabled the simulation of scenarios in the manufacture, assembly, and use of the product. This has helped capture vital knowledge from these stages of the product life and use it in design validation and testing. While there have been considerable and significant developments in knowledge capture and representation in product design, it is useful to sometimes review our position in the area, study the evolution of research in product design, and from past and current trends, try and foresee future developments. The goal of this paper is thus to review both our understanding of the field and the support tools that exist for the purpose, and identify the trends and possible directions research can evolve in the future.

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The evolution, challenges, and future of knowledge representation in product design systems

With the advent of the information and related emerging technologies, such as RFID, small size sensors and sensor networks or, more generally, product embedded information devices (PEID), a new generation of products called smart or intelligent products is available in the market. Although various definitions of intelligent products have been proposed, we introduce a new definition of the notion of Intelligent Product inspired by what happens in nature with us as human beings and the way we develop intelligence and knowledge. We see an intelligent product as a product system which contains sensing, memory, data processing, reasoning and communication capabilities at four intelligence levels. This future generations of Intelligent Products will need new Product Data Technologies allowing the seamless interoperability of systems and exchange of not only Static but of Dynamic Product Data as well. Actual standards for PDT cover only lowest intelligence of today’s products. In this context, we try to shape the actual state and a possible future of the Product Data Technologies from a Closed-Loop Product Lifecycle Management (C-L PLM) perspective. Our approach is founded in recent findings of the FP6 IP 507100 project PROMISE and follow-up research work. Standards of the STEP family, covering the product lifecycle to a certain extend (PLCS) as well as MIMOSA and ISO 15926 are discussed together with more recent technologies for the management of ID and sensor data such as EPCglobal, OGC-SWE and relevant PROMISE propositions for standards. Finally, the first efforts towards ontology based semantic standards for product lifecycle management and associated knowledge management and sharing are presented and discussed.

Closed-loop PLM for intelligent products in the era of the Internet of things

An ontology-based approach for Product Lifecycle Management

Developing multi-agent systems with a FIPA-compliant agent framework

..................................................................................................................... 2 Declaration ................................................................................................................. 3 List of Publications ..................................................................................................... 4 Table of

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A data-driven text mining and semantic network analysis for design information retrieval

This paper describes a preliminary attempt at using the Semantic Web paradigm, particularly the Web Ontology Language (OWL), for domain-specific engineering design knowledge representation in a multi-agent distributed design environment. Ontology-based modeling to the engineering design knowledge on the Semantic Web is proposed as a prelude to the meaningful agent communication and knowledge reuse for collaborative work among multidisciplinary organizations. Formal knowledge representation in OWL format extends traditional product modeling with capabilities of knowledge sharing and distributed problem solving, and is used as a content language within the FIPA-ACL (Agent Communication Language) messages in the proposed multi-agent system architecture. As an illustration, engineering design knowledge of automatic assembly systems for manufacturing electronic connectors, which contain a group of electro-mechanical components, is represented in OWL format, with its inherent structure-function-process relationships defined explicitly and formally, to facilitate semantic access and retrieval of electro-mechanical component information across different disciplines. The proposed approach is viewed as a promising knowledge-management method that facilitates the implementation of computer supported cooperative work (CSCW) in design of Semantic Web applications.

W. Y. Zhang

Papers

Exploring Semantic Web technologies for ontology-based modeling in collaborative engineering design