零件加工隐性工艺知识获取方法研究

doi:10.11996/JG.j.2095-302X.2024020399

图学学报 ›› 2024, Vol. 45 ›› Issue (2): 399-408.DOI: 10.11996/JG.j.2095-302X.2024020399

• 数字化设计与制造专刊 • 上一篇下一篇

零件加工隐性工艺知识获取方法研究

张一鸣¹(), 刘金锋¹(), 陈亚杰², 瞿鹏飞¹, 景旭文¹, 刘晓军³

1.江苏科技大学机械工程学院，江苏镇江 212028
2.上海船舶设备研究所，上海 200030
3.东南大学机械工程学院，江苏南京 211100

收稿日期:2023-09-06 修回日期:2023-12-24 出版日期:2024-04-30 发布日期:2024-04-30
通讯作者: 刘金锋(1987-)，男，副教授，博士。主要研究方向为数字化设计与制造等。E-mail：liujinfeng@just.edu.cn
作者简介:张一鸣(2000-)，男，硕士研究生。主要研究方向为数字化设计与制造等。E-mail：908891371@qq.com
基金资助:
国家自然科学基金资助项目(52075229);国家自然科学基金资助项目(52371324);江苏省高校自然科学研究重大项目(20KJA4600009)

Tacit process knowledge acquisition methods for the parts machining

ZHANG Yiming¹(), LIU Jinfeng¹(), CHEN Yajie², QU Pengfei¹, JING Xuwen¹, LIU Xiaojun³

1. School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang Jiangsu 212028, China
2. Shanghai Marine Equipment Research Institute, Shanghai 200030, China
3. School of Mechanical Engineering, Southeast University, Nanjing Jiangsu 211100, China

Received:2023-09-06 Revised:2023-12-24 Online:2024-04-30 Published:2024-04-30
Contact: LIU Jinfeng (1987-), associate professor, Ph.D. His main research interests cover digitial design and manufacturing, etc. E-mail：liujinfeng@just.edu.cn
About author:ZHANG Yiming (2000-), master student. His main research interests cover digitial design and manufacturing, etc. E-mail：908891371@qq.com
Supported by:
National Natural Science Foundation of China(52075229);National Natural Science Foundation of China(52371324);The Natural Science Foundation of the Jiangsu Higher Education Institutions of China(20KJA4600009)

摘要/Abstract

摘要：

随着制造业数字化工艺的深入应用，如何高效利用积累的工艺知识，已成为提升工艺设计效率与质量的关键，然而隐性工艺知识却存在难以获取、描述与转化的技术瓶颈，严重阻碍智能化工艺设计模式推广。为此，提出了一种复杂零件加工的隐性工艺知识获取方法。首先，利用等宽法对结构化工艺数据进行离散化处理，构建基于文本挖掘的隐性工艺知识获取流程，并通过产生式规则对隐性工艺知识表达；然后，基于案例推理和规则推理融合的知识推理方法，并采用最近邻算法实现隐性工艺知识的识别；最后，以船用柴油机缸盖类复杂加工零件为验证对象，对加工隐性工艺知识获取方法进行了有效验证。

关键词: 隐性知识, 产生式规则, 文本挖掘, 案例推理, 规则推理, 最近邻算法

Abstract:

With the widespread application of digital processes in the manufacturing industry, how to efficiently utilize the accumulated process knowledge has become the key to enhancing the efficiency and quality of process design. However, there are technical bottlenecks in acquiring, describing, and transforming tacit process knowledge, hindering the adoption of the intelligent process design mode. Therefore, a method of acquiring tacit process knowledge for processing complex parts was proposed. Firstly, the equal-width method was employed to discretize the structured process data, a text mining based tacit process knowledge acquisition process was constructed, and tacit process knowledge was expressed through production rules. Then, a knowledge reasoning method was proposed, which combined case-based reasoning and rule-based reasoning. The recognition of tacit process knowledge was achieved using the nearest neighbor algorithm. Finally, the method for acquiring processing tacit process knowledge was effectively validated using complex machining parts of marine diesel engine cylinder heads as the verification object.

Key words: tacit knowledge, production rule, text mining, case-based reasoning, rule-based reasoning, nearest neighbor algorithm

中图分类号:

TP391

张一鸣, 刘金锋, 陈亚杰, 瞿鹏飞, 景旭文, 刘晓军. 零件加工隐性工艺知识获取方法研究[J]. 图学学报, 2024, 45(2): 399-408.

ZHANG Yiming, LIU Jinfeng, CHEN Yajie, QU Pengfei, JING Xuwen, LIU Xiaojun. Tacit process knowledge acquisition methods for the parts machining[J]. Journal of Graphics, 2024, 45(2): 399-408.

图/表 15

图1 复杂零件加工的隐性工艺知识获取流程

Fig. 1 The tacit process knowledge acquisition process of complex parts processing

图2 基于加工零件的工序卡片

Fig. 2 Process cards based on machined part

图3 基于XML格式的工艺信息半结构化表达

Fig. 3 Process information expression based on XML format

表1 工艺信息数据表现形式

Table 1 Process information and data presentation form

参数	序号
参数	1	2	3	4	5
工步名称	粗铣两端面	粗镗大头孔	铣工艺侧边	铣开连杆	精镗大头孔
材料	45#	45#	45#	45#	45#
精度等级	IT12	IT12	IT12		IT8
设备名称	X2020A	双轴组合机床	X22W	X22W	双轴组合机床
切削速度	1.98	0.2	0.78	2.27	1
进给量	0.2	0.2	0.1	0.012	0.2
切削深度	2.2	1.2	20	2.0	0.12
刀具	硬质合金铣刀	硬质合金镗刀	立铣刀	锯片铣刀	硬质合金镗刀
量具	游标卡尺	游标卡尺	游标卡尺		内径千分尺
夹具	专用夹具	专用夹具	专用夹具	专用夹具	专用夹具

图4 隐性工艺知识的获取流程

Fig. 4 The acquisition process of tacit process knowledge

图5 机加工艺文件分词

Fig. 5 Machine process file participle

图6 机加工艺文件参数转换

Fig. 6 Machine process file parameter conversion

图7 工步排列的层次工艺信息数值图

Fig. 7 The numerical diagram of hierarchical process information of the work step arrangement

图8 基于文本挖掘的隐性工艺知识

Fig. 8 Tacit process knowledge based on text mining

图9 CBR-RBR集成的知识推理流程图

Fig. 9 CBR-RBR integrated knowledge inference flow chart

图10 基于加工特征的层次结构模型

Fig. 10 Hierarchical structure model based on processing characteristics

图11 基于层次结构模型的判断矩阵

Fig. 11 Judgment matrix based on hierarchical structure model

图12 工艺卡片信息提取

Fig. 12 Process card information extraction

图13 缸盖工艺知识获取实例1 ((a)基于XML格式的工艺信息表达；(b)工艺信息库)

Fig. 13 Example of acquiring process knowledge of cylinder head 1 ((a) Process information expression based on XML format; (b) Process information database)

图14 缸盖工艺知识获取实例2 ((a)孔加工特征隐性工艺知识；(b)典型孔加工隐性工艺知识获取结果展示)

Fig. 14 Example of acquiring process knowledge of cylinder head 2 ((a) Tacit process knowledge of hole processing characteristics; (b) Tacit process knowledge acquisition results of typical hole processing)

参考文献 17

[1]	田桂中, 朱钰萍, 刘金锋, 等. 面向机加工艺智能生成的工艺知识建模与管理方法[J]. 计算机集成制造系统, 2019, 25(7): 1695-1705.
	TIAN G Z, ZHU Y P, LIU J F, et al. Modeling and management of process knowledge for intelligent generating of machining process planning[J]. Computer Integrated Manufacturing Systems, 2019, 25(7): 1695-1705 (in Chinese).
[2]	王勃, 杜宝瑞, 赵璐. 面向飞机智能制造的工艺智能决策与知识库技术[J]. 智能制造, 2016(6): 26-30.
	WANG B, DU B R, ZHAO L. Process intelligent decision-making and knowledge base technology for aircraft intelligent manufacturing[J]. Intelligent Manufacturing, 2016(6): 26-30 (in Chinese).
[3]	ALI M, ALI R, ALI KHAN W, et al. A data-driven knowledge acquisition system: an end-to-end knowledge engineering process for generating production rules[J]. IEEE Access, 2018, 6: 15587-15607. DOI URL
[4]	LV S P, KIM H, ZHENG B B, et al. A review of data mining with big data towards its applications in the electronics industry[J]. Applied Sciences, 2018, 8(4): 582. DOI URL
[5]	肖振红, 李妍. 隐性知识对企业竞争优势作用机理的实证研究[J]. 哈尔滨工程大学学报, 2014, 35(2): 256-260.
	XIAO Z H, LI Y. Empirical study on the tacit knowledge to sustainable competitive advantage of the enterprise mechanism[J]. Journal of Harbin Engineering University, 2014, 35(2): 256-260 (in Chinese).
[6]	孟涛, 焦捷, 田园. 基于SECI模型的虚拟企业知识创造研究[J]. 清华大学学报: 自然科学版, 2015, 55(4): 462-469.
	MENG T, JIAO J, TIAN Y. Research on knowledge creation of virtual enterprises based on SECI model[J]. Journal of Tsinghua University: Science and Technology, 2015, 55(4): 462-469 (in Chinese).
[7]	张建民, 周俊. 隐性知识在产品概念设计中的应用[J]. 轻工机械, 2017, 35(2): 96-102.
	ZHANG J M, ZHOU J. Application of product conceptual design based on tacit knowledge[J]. Light Industry Machinery, 2017, 35(2): 96-102 (in Chinese).
[8]	陈友玲, 肖莹姣. 面向产品设计的隐性知识获取关键技术研究[J]. 科技进步与对策, 2011, 28(19): 121-124.
	CHEN Y L, XIAO Y J. Research on key technologies of tacit knowledge acquisition for product design[J]. Science & Technology Progress and Policy, 2011, 28(19): 121-124 (in Chinese).
[9]	罗仕鉴, 朱上上, 应放天, 等. 产品设计中的用户隐性知识研究现状与进展[J]. 计算机集成制造系统, 2010, 16(4): 673-688.
	LUO S J, ZHU S S, YING F T, et al. Statues and progress of research on users’ tacit knowledge in product design[J]. Computer Integrated Manufacturing Systems, 2010, 16(4): 673-688 (in Chinese).
[10]	刘征, 鲁娜, 孙凌云. 面向概念设计过程的隐性知识获取方法[J]. 机械工程学报, 2011, 47(14): 184-191.
	LIU Z, LU N, SUN L Y. Tacit knowledge acquisition method for the process of concept design[J]. Journal of Mechanical Engineering, 2011, 47(14): 184-191 (in Chinese).
[11]	张喜征, 陈博, 傅荣. 基于案例的隐性知识挖掘研究[J]. 情报杂志, 2006, 25(7): 8-9.
	ZHANG X Z, CHEN B, FU R. Study on tactic knowledge mining based on the cases[J]. Journal of Information, 2006, 25(7): 8-9 (in Chinese).
[12]	王伟, 黄宇星, 余鸿敏. 基于CART决策树的冲压成形仿真数据挖掘[J]. 工程科学学报, 2018, 40(11): 1373-1379.
	WANG W, HUANG Y X, YU H M. Data mining of deep drawing simulation results based on CART decision tree theory[J]. Chinese Journal of Engineering, 2018, 40(11): 1373-1379 (in Chinese).
[13]	刘献礼, 孙庆贞, 岳彩旭, 等. 基于数据挖掘技术的钛合金铣削工艺参数优化[J]. 计算机集成制造系统, 2022, 28(8): 2440-2448.
	LIU X L, SUN Q Z, YUE C X, et al. Optimization of milling process parameters of titanium alloy based on data mining technology[J]. Computer Integrated Manufacturing Systems, 2022, 28(8): 2440-2448 (in Chinese).
[14]	SHI Y, ZHANG Y C, XIA K S, et al. A critical review of feature recognition techniques[J]. Computer-Aided Design and Applications, 2020, 17(5): 861-899. DOI URL
[15]	郭渊, 许泽银, 白琨. 基于智能化数据挖掘获取知识的工艺规划系统研究[J]. 制造技术与机床, 2017(4): 37-43.
	GUO Y, XU Z Y, BAI K. Research on the process planning system based on intelligent data mining[J]. Manufacturing Technology & Machine Tool, 2017(4): 37-43 (in Chinese).
[16]	曲明, 郝红卫. CBR与RBR相结合的实时专家系统设计与实现[J]. 计算机工程, 2004, 30(18): 144-145, 156.
	QU M, HAO H W. Design and implementation of real-time expert system combining CBR and RBR[J]. Computer Engineering, 2004, 30(18): 144-145, 156 (in Chinese).
[17]	黄新波, 刘成, 张烨, 等. CBR和RBR融合的牵引变压器运维策略[J]. 电力自动化设备, 2020, 40(3): 194-200.
	HUANG X B, LIU C, ZHANG Y, et al. Operation and maintenance strategy of traction transformer based on CBR and RBR[J]. Electric Power Automation Equipment, 2020, 40(3): 194-200 (in Chinese).

零件加工隐性工艺知识获取方法研究

Tacit process knowledge acquisition methods for the parts machining

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