A Review on Knowledge Graph and Its Application Prospects to Intelligent Manufacturing

doi:10.3901/JME.2021.05.090

Abstract

Abstract: Data and knowledge are the basis for the deep integration of new-generation information technology and intelligent manufacturing. However, the storage of data and knowledge in the processes of product design, manufacturing, assembly and service is mostly based on relational database, which brings data redundancy and inefficiency of searching and reasoning. Recently, knowledge graph technology, based on the idea of semantic network, has developed rapidly. It can achieve the description of real-world things and their relationships, which provides a mean for the correlation representation of data and knowledge, and a solution of the relevance searching and reasoning problem in the area of intelligent manufacturing. Therefore, it plays an increasingly important role in the realization of intelligent manufacturing. In order to provide the theoretical support for the application of knowledge graph, a review about the research status of knowledge graph is provided. At the same time, three major applications of knowledge graph in the area of intelligent manufacturing are explored, including a total of 15 small application prospects. Among them, the differences compared with traditional methods, the knowledge graph technology to be introduced and the key technologies to be breakthrough are detailed. It is hoped that it can provide inspiration for researchers to further carry out study on the knowledge graph in the area of intelligent manufacturing, and provide reference for mechanical companies on the application of knowledge graph. Finally, a case about the lathe failure analysis is used to verify the superiority of the knowledge graph in the area of intelligent manufacturing.

Key words: knowledge graph, literature review, semantic network, intelligent manufacturing

CLC Number:

TP301

ZHANG Donghao, LIU Zhenyu, JIA Weiqiang, LIU Hui, TAN Jianrong. A Review on Knowledge Graph and Its Application Prospects to Intelligent Manufacturing[J]. Journal of Mechanical Engineering, 2021, 57(5): 90-113.

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