吉林大学学报(工学版) ›› 2022, Vol. 52 ›› Issue (2): 338-344.doi: 10.13229/j.cnki.jdxbgxb20211147

• 车辆工程·机械工程 • 上一篇    

基于多属性群决策的加工中心故障模式风险分析

申桂香1,2(),郑君1,2,张英芝1,2(),宋杰1,2,李哲文1,2   

  1. 1.吉林大学 数控装备可靠性教育部重点实验室，长春 130022
    2.吉林大学 机械与航空航天工程学院，长春 130022
  • 收稿日期:2021-10-30 出版日期:2022-02-01 发布日期:2022-02-17
  • 通讯作者: 张英芝 E-mail:shengx@jlu.edu.cn;zhangyz@jlu.edu.cn
  • 作者简介:申桂香（1957-），女，教授，博士.研究方向：数控装备全寿命周期工程.E-mail：shengx@jlu.edu.cn
  • 基金资助:
    吉林大学博士研究生交叉学科科研计划项目(101832020DJX037);吉林省科技发展计划项目(20190302104GX)

Risk analysis of machining center failure mode based on multi⁃attribute group decision making

Gui-xiang SHEN1,2(),Jun ZHENG1,2,Ying-zhi ZHANG1,2(),Jie SONG1,2,Zhe-wen LI1,2   

  1. 1.Key Laboratory of CNC Equipment Reliability，Ministry of Education，Jilin University，Changchun 130022，China
    2.College of Mechanical and Aerospace Engineering，Jilin University，Changchun 130022，China
  • Received:2021-10-30 Online:2022-02-01 Published:2022-02-17
  • Contact: Ying-zhi ZHANG E-mail:shengx@jlu.edu.cn;zhangyz@jlu.edu.cn

RICH HTML

 1   

PDF (PC)

78

摘要：

针对传统数控机床故障模式及影响分析（FMEA）中存在专家权重与风险因子权重分配不合理以及风险系数（RPN）计算模型不够稳健的问题，提出一种基于多属性群决策的改进FMEA方法。首先，引入区间数表征机床故障模式风险因子；其次，考虑专家的主、客观权重，根据一致性原则，计算专家综合权重，并利用加权平均算子（WAA）确定故障模式综合评价矩阵；再次，采用区间数熵值法确定风险因子权重，利用改进风险优先数（IRPN）计算模型得到故障模式风险值；最后，结合区间数距离测度，采用最优最劣区间数改进的逼近理想解排序方法（TOPSIS）对故障模式进行风险排序。以某型加工中心为例进行方法应用，验证了方法的合理性和有效性。

关键词: 机床, 故障模式及影响分析, 多属性群决策, 改进风险优先数, 逼近理想解排序方法

Abstract:

Aiming at the problems existing in the traditional FMEA of CNC machine tools， such as the unreasonable distribution of expert weight and risk factor weight， and the insufficient robustness of the calculation model of risk coefficient（RPN）， an improved FMEA method based on multi-attribute group decision-making is proposed. Firstly， interval number is introduced to represent the risk factor of machine tool failure mode； Secondly， considering the subjective and objective weights of experts， according to the consistency principle， the comprehensive weights of experts are calculated， and the weighted average operator（WAA） is used to determine the comprehensive evaluation matrix of fault mode； Thirdly， the interval number entropy method is used to determine the weight of risk factors， and the improved risk priority number （IRPN） calculation model is used to obtain the failure mode risk value； Finally， combined with interval number distance measure， the optimal and worst interval number improved TOPSIS method is used to rank the risk of failure mode. Taking a machining center as an example， the rationality and effectiveness of the method are verified.

Key words: machine tool, failure mode and effect analysis, multi-attribute group decision-making, improved risk priority number, technique for order preference by similarity to an ideal solution

中图分类号: 

  • TG659

图1

多属性群决策改进FMEA方法流程图"

图2

专家综合权重迭代流程"

图3

专家权重迭代图"

图4

各专家与群体的偏离度"

图5

各专家间的偏离度"

表1

贴近度计算结果"

故障OPRESRIRPNFi
H1［5.4928，6.1592］［6.5194，7.4086］［5.9176，6.6743］0.5966
H2［3.4982，4.3731］［4.3769，5.0072］［3.8563，4.6384］0.0000
H3［8.2417，8.4395］［7.1791，7.9644］［7.7616，8.2294］1.0000
H4［3.7259，4.1042］［6.4459，6.7387］［4.7286，5.0917］0.0507
H5［3.8337，4.2242］［6.5900，7.2762］［4.8519，5.3507］0.0849

H6

H7

H8

H9

H10

H11

H12

H13

H14

［3.7532，3.9995］

［4.1898，4.3029］

［3.8079，3.8709］

［5.4130，6.1102］

［4.6526，5.0433］

［3.6416，4.6526］

［3.5768，3.8921］

［4.5566，5.1622］

［4.5014，5.0735］

［6.3354，6.9485］

［4.8352，5.6408］

［6.8116，7.1112］

［5.8572，6.1702］

［5.1228，5.8277］

［4.5910，5.1108］

［6.1377，6.7498］

［6.5826，7.1726］

［7.0718，7.5394］

［4.7127，5.0850］

［4.4591，4.8404］

［4.9033，5.0426］

［5.6018，6.1363］

［4.8515，5.3705］

［4.0276，4.8465］

［4.5233，4.9447］

［5.3469，5.9558］

［5.4784，6.0269］

0.0488

0.0200

0.0645

0.3791

0.0868

0.0024

0.0271

0.2677

0.3148

图6

排序结果对比"

1 Peeters J F W, Basten R J I, Tinga T. Improving failure analysis efficiency by combining FTA and FMEA in a recursive manners[J]. Reliability Engineering & System Safety, 2018, 172(4): 36-44.
2 Wang Wei-zhong, Liu Xin-wang, Qin Yong, et al. A risk evaluation and prioritization for FMEA with prospect theory and choquet integral[J]. Safety Science, 2018, 110: 152-163.
3 韦可佳, 耿俊豹, 徐孙庆. 基于模糊理论与D-S证据理论的FMEA方法[J]. 系统工程与电子技术, 2019, 41(11): 2662-2668.
Wei Ke-jia, Geng Jun-bao, Xu Sun-qing. FMEA method based on fuzzy theory and D-S evidence theory[J]. Systems Engineering and Electronics, 2019, 41(11): 2662-2668.
4 王晓峰, 申桂香, 张英芝, 等. 基于改进危害度和DEMATEL方法的abc轴进给系统的故障排序[J]. 吉林大学学报: 工学版, 2012, 42(1): 122-127.
Wang Xiao-feng, Shen Gui-xiang,Zhang Ying-zhi,et al. Prioritizing failures of abc-axis feeding systems based on improved criticality and DEMALTEL method[J]. Journal of Jilin University(Engineering and Technology Edition), 2012, 42(1): 122-127.
5 Liu Hu-chen, Li Zhao-jun, Song Wen-yan, et al. Failure mode and effect analysis using cloud model theory and PROMETHEE method[J]. IEEE Transactions on Reliability, 2017, 66(4): 1058-1072.
6 Lo H W, Liou J J H, Chuang Y C, et al. A novel failure mode and effect analysis model for machine tool risk analysis[J]. Reliability Engineering & System Safety, 2019, 183: 173-183.
7 郑玉彬, 申桂香, 张英芝, 等. 基于贝叶斯网络的链式刀库系统重要度分析[J]. 吉林大学学报: 工学版, 2019, 49(2): 466-471.
Zheng Yu-bin, Shen Gui-xiang, Zhang Ying-zhi,et al. Importance analysis of chain-type tool magazine system based on Bayesian network[J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(2): 466-471.
8 王晓燕, 申桂香, 张英芝, 等. 基于DEMATEL方法的数控装备故障相关性分析[J]. 吉林大学学报: 工学版, 2012, 42(): 100-103.
Wang Xiao-yan, Shen Gui-xiang, Zhang Ying-zhi, et al. Analysis about failure correlation of CNC equipment base on DEMATEL[J]. Journal of Jilin University(Engineering and Technology Edition), 2012, 42(Sup.1): 100-103.
9 Jiang Guang-jun, Cai Shuang, Zhang Nan, et al. Reliability analysis of the starting and landing system of UAV by FMECA and FTA[J]. Journal of Industrial and Production Engineering, 2019, 36(8): 503-511.
10 Zhao Xiao-song, Chen Te-hung, Kun Zhang, et al. Applying an improved failure mode effect analysis method to evaluate the safety of a three-in-one machine tool[J]. Human Factors and Ergonomics in Manufacturing & Service Industries, 2020, 30(1): 71-82.
11 Liu Hu-chen, You Jian-xin, You Xiao-yue, et al. Evaluating the risk of healthcare failure modes using interval 2-tuple hybrid weighted distance measure[J]. Computers & Industrial Engineering, 2014, 78(12): 249-258.
12 王睿, 李延来, 朱江洪, 等. 考虑专家共识的改进FMEA风险评估方法[J]. 浙江大学学报: 工学版, 2018, 52(6): 1058-1067.
Wang Rui, Li Yan-lai, Zhu Jiang-hong, et al. Improved FMEA method for risk evaluation considering expert consensus[J]. Journal of Zhejiang University(Engineering Science), 2018, 52(6): 1058-1067.
13 聂文滨, 刘卫东, 汪建东, 等. 基于证据理论和矩阵相似度的工艺失效风险评估[J]. 计算机集成制造系统, 2016, 22(11): 2602-2612.
Nie Wen-bin, Liu Wei-dong, Wang Jian-dong, et al. Evaluation approach in process failure risk based on matrix similarity and evidence theory[J]. Computer Integrated Manufacturing Systems, 2016, 22(11): 2602-2612.
14 安相华, 蔡卫国, 宋晓杰. 基于云模型与协同决策的FMEA耦合评估方法[J]. 计算机集成制造系统, 2018, 24(5): 1179-1190.
An Xiang-hua, Cai Wei-guo, Song Xiao-jie. FMEA coupling evaluation method based on cloud model and collaborative decision[J]. Computer Integrated Manufacturing Systems, 2018, 24(5): 1179-1190.
15 王晓峰, 申桂香, 张英芝, 等. 基于群体决策和多种赋值方式的加工中心关键部件RPN分析[J]. 吉林大学学报: 工学版, 2011, 41(6): 630-635.
Wang Xiao-feng, Shen Gui-xiang, Zhang Ying-zhi, et al. Analysis on risk priority number of critical component of machining center based on group decision-making and various assignment ways[J]. Journal of Jilin University(Engineering and Technology Edition), 2011, 41(6): 630-635.
16 陈晓红, 刘益凡. 基于区间数群决策矩阵的专家权重确定方法及其算法实现[J]. 系统工程与电子技术, 2010, 32(10): 2128-2131.
Chen Xiao-hong, Liu Yi-fan. Expert weights determination method and realization algorithm based on interval numbers group decision matrices[J]. Systems Engineering and Electronics, 2010, 32(10): 2128-2131.
17 王珊珊. 语言模糊多属性群决策中群共识问题研究[D]. 成都: 西南石油大学理学院, 2019.
Wang Shan-shan. Research on group consensus in linguistic fuzzy multi-attribute group decision making[D]. Chengdu: College of Science, Southwest Petroleum University, 2019.
[1] 陈传海,王成功,杨兆军,刘志峰,田海龙. 数控机床可靠性建模研究现状及发展动态分析[J]. 吉林大学学报(工学版), 2022, 52(2): 253-266.
[2] 李国龙,陶小会,徐凯,李喆裕. 数控机床转台位置相关几何误差的快速测量与辨识[J]. 吉林大学学报(工学版), 2021, 51(2): 458-467.
[3] 蔡洪彬,史国权. 主动控制加工误差慢刀伺服车削轨迹生成方法[J]. 吉林大学学报(工学版), 2019, 49(4): 1221-1227.
[4] 郑玉彬, 杨斌, 王晓峰, 申桂香, 赵宪卓, 秦猛猛. 基于威布尔分布的电主轴加速寿命试验时间设计[J]. 吉林大学学报(工学版), 2018, 48(3): 767-772.
[5] 申桂香, 曾文彬, 张英芝, 吴茂坤, 郑玉彬. 最小故障率下数控组合机床平均维修时间确定[J]. 吉林大学学报(工学版), 2017, 47(5): 1519-1526.
[6] 张英芝, 刘津彤, 申桂香, 戚晓艳, 龙哲. 基于故障相关性分析的数控机床系统可靠性建模[J]. 吉林大学学报(工学版), 2017, 47(1): 169-173.
[7] 曲兴田, 赵永兵, 刘海忠, 王昕, 杨旭, 陈行德. 串并混联机床几何误差建模与实验[J]. 吉林大学学报(工学版), 2017, 47(1): 137-144.
[8] 孟书, 申桂香, 张英芝, 龙哲, 曾文彬. 基于时间相关的数控机床系统组件更换时间[J]. 吉林大学学报(工学版), 2016, 46(6): 1946-1952.
[9] 李洪洲, 杨兆军, 许彬彬, 王彦鹍, 贾玉辉, 侯超. 数控机床可靠性评估试验周期设计[J]. 吉林大学学报(工学版), 2016, 46(5): 1520-1527.
[10] 王健健, 冯平法, 张建富, 吴志军, 张国斌, 闫培龙. 卡盘定心精度建模及其保持特性与修复方法[J]. 吉林大学学报(工学版), 2016, 46(2): 487-493.
[11] 杨兆军, 杨川贵, 陈菲, 郝庆波, 郑志同, 王松. 基于PSO算法和SVR模型的加工中心可靠性模型参数估计[J]. 吉林大学学报(工学版), 2015, 45(3): 829-836.
[12] 王晓燕，申桂香，张英芝，孙曙光，戚晓艳，荣峰. 基于故障链的复杂系统故障相关系数建模[J]. 吉林大学学报(工学版), 2015, 45(2): 442-447.
[13] 赵帼娟, 张雷, 卢磊, 韩飞飞, 赵继. 四轴抛光平台综合误差建模及分析[J]. 吉林大学学报(工学版), 2014, 44(6): 1676-1683.
[14] 王继利, 杨兆军, 李国发, 朱晓翠. EM算法的多重威布尔可靠性建模[J]. 吉林大学学报(工学版), 2014, 44(4): 1010-1015.
[15] 杨兆军,王继利,李国发,张新戈. 冲压机床可靠性增长的模糊层次分析预测方法[J]. 吉林大学学报(工学版), 2014, 44(3): 686-691.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 《吉林大学学报(工学版)》编辑部
地址：长春市人民大街5988号　电话：+86-431-85095297　传真：+86-431-85094074　E-mail: xbgxb@jlu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发