基于知识的复杂产品装配工艺快速编制方法

翟思宽;刘检华;庄存波

兵工学报 ›› 2024, Vol. 45 ›› Issue (4) : 1332-1343.

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  • 主管：中国科学技术协会

    主编：许毅达

    ISSN 1000-1093

    　

  • 主办：中国兵工学会

    出版：《兵工学报》 编辑部

    CN 11-2176/TJ

《兵工学报》是我国国防科技领域最具影响力的学术期刊之一，创刊于1979年，目前被国内所有重要数据库收录，其综合评价指标近年来一直名列兵工技术类科技期刊的首位；《兵工学报》目前还被国际上著名的检索机构美国......
兵工学报 ›› 2024, Vol. 45 ›› Issue (4) : 1332-1343. DOI: 10.12382/bgxb.2022.1225
论文

基于知识的复杂产品装配工艺快速编制方法

  • 翟思宽1,2， 刘检华1， 庄存波1,2*()
作者信息 +

Knowledge-based Rapid Preparation Method for Complex Product Assembly Process

  • ZHAI Sikuan1,2, LIU Jianhua1, ZHUANG Cunbo 1,2*
Author information +
文章历史 +

摘要

针对复杂产品装配工艺设计过程中存在的编制效率低、质量波动大、自动化和智能化程度低等问题，提出一种面向语义的知识实例检索和复用的装配工艺快速编制方法。分析复杂产品装配工艺业务流程，建立基于知识检索层和知识实例层的双层装配工艺知识模型，从内容、类型、功能及应用方向对知识进行分类。在此基础上，针对已有的知识实例，提出基于Sentence-BERT句向量模型的工艺文档语义分析方法，结合余弦相似度算法给出了工艺知识的语义检索方法，实现知识在装配工艺设计流程中的快速复用。以某航天产品为例，开发航天产品装配工艺快速设计管理系统，构建装配工艺知识库，并在某制造企业上线运行，验证所提方法的可行性，使工艺编制效率大幅提升。

Abstract

Aiming at the problems of low preparation efficiency, high quality fluctuation and low automation and intelligence in the process of complex product assembly process design, a fast preparation method for assembly process with semantic-oriented knowledge instance retrieval and reuse is proposed. A two-layer assembly process knowledge model based on the knowledge retrieval layer and the knowledge instance layer is established by analyzing the assembly process of complex product, and the knowledge is classified in terms of content, type, function and application direction. On this basis, a process document semantic analysis method based on the Sentence-BERT sentence embeddings model is proposed for the existing knowledge instances. The semantic retrieval method of process knowledge is given combined with the cosine similarity algorithm, and the rapid reuse of knowledge in the design process of assembly process is realized. Taking aerospace products as an example, a rapid design management system of aerospace product assembly process is developed, and a knowledge base for the assembly process is constructed and put into operation in an aerospace enterprise to verify the feasibility of the proposed method, resulting in a significant increase in process preparation efficiency.

关键词

复杂产品 / 装配 / 知识模型 / 句向量 / 语义检索 / 知识库

Key words

complexproduct / assembly / knowledgemodel / sentenceembeddings / senmanticretrieval / knowledgebase

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翟思宽，刘检华，庄存波. 基于知识的复杂产品装配工艺快速编制方法. 兵工学报. 2024, 45(4): 1332-1343 https://doi.org/10.12382/bgxb.2022.1225
ZHAI Sikuan, LIU Jianhua, ZHUANG Cunbo. Knowledge-based Rapid Preparation Method for Complex Product Assembly Process. Acta Armamentarii. 2024, 45(4): 1332-1343 https://doi.org/10.12382/bgxb.2022.1225

参考文献

［1］尚育如,富大欣,李川生,等. 航天工艺基础知识培训教材(下)[M]. 北京:中国宇航出版社, 2005.
SHANG Y R, FU D X, LI C S, et al. Training materials for basic knowledge of aerospace technology (below) [M]. Beijing: China Aerospace Press, 2005. (in Chinese)
[2]叶剑辉,刘少丽,刘检华,等．基于流程的复杂产品装配车间现场监控技术[J].计算机集成制造系统, 2017,23(7): 1469-1480.
YE J H, LIU S L, LIU J H, et al. Process-based on-site monitoring technology for complex product assembly workshops[J]. Computer Integrated Manufacturing Systems, 2017,23(7):1469-1480. (in Chinese)
[3]ZHOUW, LI S Q, HUANG Y Q, et al. Simulation-based planning of a kind of complex product general assembly line[J]. Procedia Cirp, 2018, 76: 25-30.
[4]宋邓强,周彬,申兴旺,等.面向船舶分段制造过程的动态知识图谱建模方法[J].上海交通大学学报,2021,55(5):544- 556.
SONG D Q, ZHOU B, SHEN X W, et al. A dynamic knowledge mapping modeling approach for ship segment manufacturing process[J]. Journal of Shanghai Jiaotong University,2021,55(5): 544-556. (in Chinese)
[5]代风,翟翔,施国强,等.面向航天产品研制的知识网络本体建模方法[J].浙江大学学报(工学版),2018,52(10):2023- 2034.
DAI F, ZHAI X, SHI G Q, et al. A knowledge network ontology modeling approach for aerospace product development[J]. Journal of Zhejiang University (Engineering Edition),2018,52(10): 2023-2034.(in Chinese)
[6]刘检华,孙清超,程晖, 等.产品装配技术的研究现状、技术内涵及发展趋势[J].机械工程学报, 2018, 54(11): 2-28.
LIU J H, SUN Q C, CHENG H, et al. Research status technical connotation and development trend of product assembly technology[J]. Journal of Mechanical Engineering, 2018, 54(11):2-28. (in Chinese)
[7]宋海薇,左敦稳,薛善良,等. 基于工艺相似性的总装工艺快速设计技术研究[J]. 中国制造业信息化, 2009, 38(21): 29-31,35.
SONG H W, ZUO D W, XUE S L, et al. Research on rapid design technology of assembly process based on process similarity[J]. China Manufacturing Informatization, 2009, 38(21): 29- 31,35. (in Chinese)
[8]王裴岩,张桂平,翟顺龙,等. 基于多核学习的装配工艺过程重用[J]. 计算机集成制造系统,2018,24(7):1850-1857.
WANG P Y, ZHANG G P, ZHAI S L, et al. Multi-core learning-based reuse of assembly processes[J]. Computer Integrated Manufacturing Systems,2018,24(7):1850-1857. (in Chinese)
[9]孟倩,刘检华,唐承统,等.基于流程的复杂产品结构化装配工艺设计技术研究与应用[J].计算机集成制造系统,2014,20(2): 301-312.
MENG Q, LIU J H, TANG C T, et al. Research and application of process-based structured assembly process design technology for complex products[J]. Computer Integrated Manufacturing Systems,2014,20(2):301-312. (in Chinese)
[10]丘宏俊,陶华,高晓兵,等.飞机装配工艺设计知识本体[J].西北工业大学学报, 2007, 25(1): 32-36.
QIU H J, TAO H, GAO X B, et al. Ontology for Aircraft Assembly Process Planning Knowledge [J]. Journal of Northwestern Polytechnical University, 2007, 25(1): 32-36. (in Chinese)
[11]刘艺涵,茅健,郑武.面向智能装配的工艺知识管理方法[J].计算机制造集成系统, 2023, 29(8):2513-2523.
LIU Y H MAO J, ZHENG W. A process knowledge management approach for intelligent assembly [J]. Computerized Manufacturing Integrated Systems, 2023, 29(8)： 2513-2523. (in Chinese)
[12]ZHOUB, BAO J S, CHEN Z Y, et al. KGAssembly: knowledge graph-driven assembly process generation and evaluation for complex components[J]. International Journal of Computer Integrated Manufacturing, 2022, 35(10/11): 1151-1171.
[13]顾星海,鲍劲松,吕超凡. 基于知识图谱的装配语义信息建模[J]. 航空制造技术,2021,64(4):74-81.
GU X H, BAO J S, L C F. Semantic information modeling of assembly based on knowledge graph[J]. Aerospace Manufacturing Technology,2021,64(4):74-81. (in Chinese)
[14]WANGW M, PENG X, ZHU G N, et al. Dynamic representation of fuzzy knowledge based on fuzzy petri net and genetic-particle swarm optimization[J]. Expert Systems with Applications, 2014, 41(4): 1369-1376.
[15]WANG R, NELLIPPALLIL A B, WANG G, et al. A process knowledge representation approach for decision support in design of complex engineered systems[J]. Advanced Engineering Informatics, 2021, 48: 101257.
[16]ALOMRAN F N A, TREUDE C. Choosing an NLP library for analyzing software documentation: a systematic literature review and a series of experiments[C]∥Proceedings of 2017 IEEE/ACM 14th international conference on mining software repositories (MSR). Buenos Aires, Argentina :IEEE, 2017: 187-197.
[17]ZHANG Y J, XU Z T, ZHANG T. Fusion of multiple features for Chinese named entity recognition based on CRF model[J]. Lecture Notes in Computer Science, 2008, 4993: 95-106.
[18]SUN S C, YUN J, LIN H F, et al. Granular transfer learning using type-2 fuzzy HMM for text sequence recognition[J]. Neurocomputing, 2016, 214: 126-133.
[19]XING Y P, XIAO C B, WU Y F, et al. A convolutional neural network for aspect-level sentiment classification[J]. International Journal of Pattern Recognition and Artificial Intellgence, 2019, 33(14): 1959046.
[20]WU Y Z, LIU Q, CHEN R R, et al. A group recommendation system of network document resource based on knowledge graph and LSTM in edge computing[J]. Security and Communication Networks, 2020, 2020: 8843803.
[21]DEVLIN J, CHANG M W, LEE K, et al. BERT: pre-training of deep bidirectional transformers for language understanding[C]∥Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1. Minneapolis, MN, US: Association for Computational Linguistics,2019: 4171–4186.
[22]PAVANKUMAR M R, JAYAGOPAL P. Context-sensitive lexicon for imbalanced text sentiment classification using bidirectional LSTM[J]. Journal of Intelligent Manufacturing, 2023, 34(5): 2123-2132.
[23]ZHANGM S, YU N, FU G H. A simple and effective neural model for joint word segmentation and POS tagging[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2018, 26(9): 1528-1538.
[24]REIMERSN, GUREVYCH I. Sentence-BERT: sentence embeddings using siamese BERT-networks[C]∥Proceedings of the 2019 Congerence on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing. Hong Kong, China: Association for Computational Linguistics, 2019:3982-3992.br>br>

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