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2023, 02, v.55 1-9
Industrial Mechanism Modeling for Collaborative Production of Mass Customization
Email: tzy_hit@hit.edu.cn;
DOI: 10.13705/j.issn.1671-6841.2021511
Received:   2021-11-29
Received Year:   2021
Revised:   2022-05-07
Accepted:   2023-01-15
Accepted Year:   2023
Review Duration(Year):   2
Published:   2022-05-19
Publication Date:   2022-05-19
Online:   2022-05-19
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Abstract:

With the development of the industrial internet, countries around the world were carrying out a digital revolution around industrial manufacturing, accelerating the construction of a new industrial ecology characterized by intelligent production, personalized customization, and collaborative production. For many industrial mechanisms in industrial scenarios, both the expression and reasoning of them were difficult points in industrial internet research. The effective expression of industrial mechanism played a very important role in the construction of industrial mechanism base. Industrial mechanism contained multi-dimensional, fine-grained information such as capabilities and conditions, while traditional ontology modeling methods only described basic information in industrial scenarios, lacking the expression of capabilities, which was difficult to describe complex industrial scenarios. Aiming at above problems, a three-layer ontology modeling framework that could express industrial mechanisms was proposed, and a meta-model suitable for industrial mechanism modeling was defined, with a three-layer industrial mechanism model basing on it. The three-layer model contained composition views, capability views, and mode views for different industrial scenarios, as well as the operation set of the three-layer model. Based on this, the adaptation and application of the model in diversified industrial scenarios were completed. Finally, taking the knowledge in the field of home appliances as a case, the three-layer model′s expression of industrial mechanism and its application in personalized customization were introduced in detail.

References

[1] WANG Y,MA H S,YANG J H,et al.Industry 4.0:a way from mass customization to mass personalization production[J].Advances in manufacturing,2017,5(4):311-320.

[2] LI L.China′s manufacturing locus in 2025:with a comparison of “Made-in-China 2025” and “Industry 4.0”[J].Technological forecasting and social change,2018,135:66-74.

[3] OZTEMEL E,GURSEV S.Literature review of Industry 4.0 and related technologies[J].Journal of intelligent manufacturing,2020,31(1):127-182.

[4] RYCHTYCKYJ N,RAMAN V,SANKARANARAYANAN B,et al.Ontology re-engineering:a case study from the automotive industry[J].AI magazine,2017,38(1):49-60.

[5] YING W C,PEE L G,JIA S L.Social informatics of intelligent manufacturing ecosystems:a case study of KuteSmart[J].International journal of information management,2018,42:102-105.

[6] TIIHONEN J,FELFERNIG A.An introduction to personalization and mass customization[J].Journal of intelligent information systems,2017,49(1):1-7.

[7] BANERJEE A,DALAL R,MITTAL S,et al.Generating digital twin models using knowledge graphs for industrial production lines[C]//Proceedings of the 2017 ACM on Web Science Conference.New Tork:ACM Press,2017:425-430.

[8] ZHAO M X,WANG H,GUO J,et al.Construction of an industrial knowledge graph for unstructured Chinese text learning[J].Applied sciences,2019,9(13):2720.

[9] ZHANG F,LI Z Y,PENG D H,et al.RDF for temporal data management-a survey[J].Earth science informatics,2021,14(2):563-599.

[10] ALOBAIDI M,MALIK K M,SABRA S.Linked open data-based framework for automatic biomedical ontology generation[J].BMC bioinformatics,2018,19(1):319.

[11] CHEN J Y,HU P,JIMENEZ-RUIZ E,et al.OWL2Vec:embedding of OWL ontologies[J].Machine learning,2021,110(7):1813-1845.

[12] LI Z,WANG W M,LIU G,et al.Toward open manufacturing:a cross-enterprises knowledge and services exchange framework based on blockchain and edge computing[J].Industrial management & data systems,2018,118(9):303-320.

[13] 张晓丹,李静,张秋霞,等.语义Web本体语言OWL2研究[J].电子设计工程,2015,23(16):28-31.ZHANG X D,LI J,ZHANG Q X,et al.Research on semantic Web ontology language OWL2[J].Electronic design engineering,2015,23(16):28-31.

[14] VO M H L,HOANG Q.Transformation of UML class diagram into OWL Ontology[J].Journal of information and telecommunication,2020,4(1):1-16.

[15] 郭卫兵,臧莉娟.基于关联数据技术的机构知识库构建与服务[J].兵器装备工程学报,2020,41(12):275-280.GUO W B,ZANG L J.Construction and services of institutional repository based on linked data[J].Journal of ordnance equipment engineering,2020,41(12):275-280.

[16] WALEK B,FOJTIK V.A hybrid recommender system for recommending relevant movies using an expert system[J].Expert systems with applications,2020,158:113452.

[17] DELCAMBRE L M L,LIDDLE S W,PASTOR O,et al.A reference framework for conceptual modeling[C]//International Conference on Conceptual Modeling.Cham:Springer,2018:27-42.

[18] TOMASZEK S,SPEITH R,SCHüRR A.Virtual network embedding:ensuring correctness and optimality by construction using model transformation and integer linear programming techniques[J].Software and systems modeling,2021,20(4):1299-1332.

[19] 昝红英,窦华溢,贾玉祥,等.基于多来源文本的中文医学知识图谱的构建[J].郑州大学学报(理学版),2020,52(2):45-51.ZAN H Y,DOU H Y,JIA Y X,et al.Construction of Chinese medical knowledge graph based on multi-source corpus[J].Journal of Zhengzhou university (natural science edition),2020,52(2):45-51.

[20] 王宁,刘玮,兰剑.基于法院判决文书的法律知识图谱构建和补全[J].郑州大学学报(理学版),2021,53(3):23-29.WANG N,LIU W,LAN J.Construction and completion of legal knowledge graph based on court judgment documents[J].Journal of Zhengzhou university (natural science edition),2021,53(3):23-29.

[21] 张宇航,姚文娟,姜姗.个性化推荐系统综述[J].价值工程,2020,39(2):287-292.ZHANG Y H,YAO W J,JIANG S.Personalized recommendation system review[J].Value engineering,2020,39(2):287-292.

Basic Information:

DOI:10.13705/j.issn.1671-6841.2021511

China Classification Code:TP368.3;TP391.1

Citation Information:

[1]ZHANG Kai,TU Zhiying,LU Zhan ,et al.Industrial Mechanism Modeling for Collaborative Production of Mass Customization[J].Journal of Zhengzhou University(Natural Science Edition),2023,55(02):1-9.DOI:10.13705/j.issn.1671-6841.2021511.

Fund Information:

国家重点研发计划项目(2018YFB1702900); 山东省重点研发计划项目(2020CXGC010103)

Received:  

2021-11-29

Received Year:  

2021

Revised:  

2022-05-07

Accepted:  

2023-01-15

Accepted Year:  

2023

Review Duration(Year):  

2

Published:  

2022-05-19

Publication Date:  

2022-05-19

Online:  

2022-05-19

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