An ontology-based knowledge framework for engineering material selection

Abstract

Engineering material selection intensively depends on domain knowledge.In the face of the large number and wide variety of engineering materials, it is very necessary to research and develop an open, shared, and scalable knowledge framework for implementing domain-oriented and knowledge-based material selection. In this paper, the fundamental concepts and relationships involved in all aspects of material selection are analyzed in detail. A novel ontology-based knowledge framework is presented. The ontology-based Semantic Web technology is introduced into the semantic representation of material selection knowledge. The implicit material selection knowledge is represented as a set of labeled instances and RDF instance graphs in terms of the concept model, which provides a formal approach to organizing the captured material selection knowledge. A knowledge retrieval and reasoning approach integrating ontology concepts, instances, knowledge rules, and semantic queries encoded with Query-enhanced Web Rule Language (SQWRL) is proposed. The presented knowledge framework can provide powerful knowledge services for material selection. Finally, based on this knowledge framework, a case study on constructing a mold material selection knowledge system is provided. This work is a new attempt to build an open and shared knowledge framework for engineering material selection. IntroductionWith the development of technologies, the available set of engineering materials is rapidly growing in both type and number. It is estimated that there are more than 80,000 engineering materials available in the world, and new materials are emerging constantly [1]. Engineering materials are usually coupled with series of manufacturing processes. It is estimated that there are at least 1000 different manufacturing processes that can convert engineering materials into desired products[1]. In the material selection process, design engineers have to take into account a large number of factors, such as physical properties, mechanical properties, thermal properties, material cost, and impact on the environment. Hence, the vast number of materials and processes and the complex relationships between the different selection parameters often make the selection of materials for a given component a difficult task [2].Information on engineering materials presents in two categories: data and knowledge. Data is defined as the result of measurements that can be presented as numerical values, whereas knowledge represents the connections between the items of data [3].As the materials involve a large amount of data, it is necessary to employ database information systems to effectively manage, retrieve, and update the material data. A large number of material databases have been built, most of which can be accessed online [4]. Due to their data-oriented representation mode, the material databases still lack a knowledge inference mechanism and are not able to associate the data with facts.Material selection is a highly knowledge-intensive activity, involving knowle...

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