Cloud manufacturing (CMfg) is emerging as an advanced service-oriented manufacturing model for the manufacturing industry. It is changing the way manufacturing enterprises organize production activities in that tangible and intangible manufacturing resources encapsulated as virtualized manufacturing services are provided to customers. In this background, CMfg task semantic modeling and description is proposed to address different challenges such as matching with manufacturing services. Firstly, some of the essential features of CMfg tasks are briefly discussed and classification as well as the modeling requirements of CMfg tasks is also investigated, and then this paper proposes the modeling framework of CMfg task to solve the general CMfg task ontology (GCMT_Ontology) construction and the task sub-ontology matching from GCMT_Ontology. In GCMT_Ontology construction process, the original CMfg task ontology (OCMT_Ontology) is built from the CMfg task description model, and then an ontology learning approach is advanced to perfect the GCMT_Ontology with graph-based semantic similarity algorithm. In task sub-ontology matching process, semantic feature values of concepts are calculated to extend the semantic content of the task document, and the extended concepts are input to find the sub-ontology by computing minimum connected sub-graph. Finally, the proposed framework is realized in a prototype system, and an example of cement grinding mill assembling task is carried out in a group enterprise to illustrate the application. The results show that the proposed method improves enterprise collaboration and interoperation effectively.

Manufacturing task semantic modeling and description in cloud manufacturing system

Pre-existing knowledge buried in manufacturing enterprises can be reused to help decision-makers develop good judgements to make decisions about the problems in new product development, which in turn speeds up and improves the quality of product innovation. This paper presents a graph-based approach to knowledge reuse for supporting knowledge-driven decision-making in new product development. The paper first illustrates the iterative process of knowledge-driven decision-making in new product development. Then, a novel framework is proposed to facilitate this process, where knowledge maps and knowledge navigation are involved. Here, OWL ontologies are employed to construct knowledge maps, which appropriately capture and organise knowledge resources generated at various stages of product lifecycle; the Personalised PageRank algorithm is used to perform knowledge navigation, which finds the most relevant knowledge in knowledge maps for a given problem in new product development. Finally, the feasibility and ...

Graph-based knowledge reuse for supporting knowledge-driven decision-making in new product development

Knowledge Based Engineering (KBE) is a research area for product design that involves complex and iterative processes based on methodologies and technologies for capture and reuse of product knowledge Although KBE has been proposed to support product development for the last decade, it is still far to complete As this is an attractive research area for the past decade many approaches are developed based on parametric, function based, web-based, case-based, ontology technologies for enhancing the capabilities of KBE This paper is an effort to collect and review existing literature on KBE evolution, approaches and methodologies The evolution of the KBE definition is also briefly discussed along with the current limitation and future trends of KBE The objective of the review paper is to identify the foundation and research issues of KBE in the light of parametric, function based, web-oriented modeling

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Knowledge Based Engineering: Notion, Approaches and Future Trends

This paper presents a framework for developing engineering design ontologies within the aerospace industry. The aim of this approach is to strengthen the modularity and reuse of engineering design ontologies to support knowledge management initiatives within the aerospace industry. Successful development and effective utilisation of engineering ontologies strongly depends on the method/framework used to develop them. Ensuring modularity in ontology design is essential for engineering design activities due to the complexity of knowledge that is required to be brought together to support the product design decision-making process. The proposed approach adopts best practices from previous ontology development methods, but focuses on encouraging modular architectural ontology design. The framework is comprised of three phases namely: (1) Ontology design and development; (2) Ontology validation and (3) Implementation of ontology structure. A qualitative research methodology is employed which is composed of fou...

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2014.965352

A framework for developing engineering design ontologies within the aerospace industry

A knowledge graph method for hazardous chemical management: Ontology design and entity identification

Ontology-based semantic retrieval for engineering domain knowledge

In this paper, we propose a knowledge retrieval framework based on semantically annotated engineering ontology generated from domain documents. Particularly, we propose a scheme for build relations between ontology and domain documents. First, we build anthologies in engineering domain. Next, we transform the keywords into domain ontology concepts, and then find the synonyms of these keywords which are used as real queries to directly input into the query system. The semantic-based knowledge search and retrieval is then performed by ontology mapping and comparison. Using the semantic network of ontology, this system not only can conduct keyword-based retrieval, but also can understand the queries and answer questions by fuzzy inference based on domain ontology.

Xiaofeng Chen

Papers

Ontology-based semantic retrieval for engineering domain knowledge

A semantic retrieval framework for engineering domain knowledge