HEKM: A High-End Equipment Knowledge Management System for Supporting Knowledge-Driven Decision-Making in New Product Development

Abstract

Pre-existing knowledge buried in high-end equipment manufacturing enterprises could be effectively 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. Nevertheless, a knowledge-based decision support system in high-end equipment domain is still not fully accomplished due to the complication of knowledge content, fragmentation of knowledge theme, heterogeneousness of knowledge format, and decentralization of knowledge storage. To address these issues, this paper develops a high-end equipment knowledge management system (HEKM) for supporting knowledge-driven decision-making in new product development. HEKM provides three steps for knowledge management and reuse. Firstly, knowledge resources are captured and structured through a standard knowledge description template. Then, OWL ontologies are employed to explicitly and unambiguously describe the concepts of the captured knowledge and also the relationships that hold between those concepts. Finally, the Personalized PageRank algorithm together with ontology reasoning approach is used to perform knowledge navigation, where decision-makers could acquire the most relevant knowledge for a given problem through knowledge query or customized active push. The feasibility and effectiveness of HEKM are demonstrated through three industrial application examples.