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

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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"

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