Evaluation of Meta-Action Maintenance Effects for Electromechanical Products Based on IVIF-DANP
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摘要:
维修效果评估是机电产品维修保障能力的重要体现，也是维修管理的关键环节. 传统方法在处理高维数据和指标间相互影响时存在局限，难以准确反映维修效果. 针对这些问题，本文融合区间直觉模糊集(IVIFS)与决策试验-网络分析法 (DANP)，提出一种新的维修效果评估方法. 首先，结合机电产品元动作单元结构简单、易于故障诊断的特点，建立了多层次维修效果评价指标体系；其次，在区间直觉模糊环境下，运用决策与评价试验法(DEMATEL)分析指标间的相互影响，并结合网络分析法 (ANP)对指标进行赋权；然后，通过计算候选维修方案与理想方案的加权距离，实现维修效果的量化评估与排序；最后，以数控磨床蜗杆转动元动作单元为例，对3种维修方式进行综合评估排序，并通过变专家权重及不同方法对比分析，验证该方法的稳定性和可行性. 研究结果表明了该融合IVIF-DANP的评估模型可精准区分不同维修方案优劣.
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关键词:
- 元动作单元 /
- 维修效果 /
- 区间直觉模糊集 /
- DEMATEL-ANP /
- 多属性决策
Abstract:The evaluation of maintenance effects is an important reflection of the maintenance support capability of electromechanical products and a key aspect of maintenance management. Traditional methods are limited in handling high-dimensional data and interactions among indicators, making it difficult to accurately reflect maintenance effects. To solve these problems, a new method for evaluating maintenance effects that integrates interval-valued intuitionistic fuzzy sets (IVIFS) and the DEMATEL-based analytic network process (DANP) was proposed. A multi-level maintenance effect evaluation index system was established based on the simple structure and ease of fault diagnosis of electromechanical product meta-action units. In an interval-valued intuitionistic fuzzy environment, the decision-making trial and evaluation laboratory (DEMATEL) method was applied to analyze interdependencies among indicators, and the analytic network process (ANP) was used to determine their weights. Maintenance effects were quantitatively evaluated and ranked by calculating the weighted distances between candidate maintenance plans and the ideal plan. In a case study involving the worm rotation meta-action unit of a CNC grinding machine, three maintenance methods were comprehensively evaluated and ranked. The stability and feasibility of the method were verified by varying the weights assigned to experts and comparing different methods. The results show that the evaluation model integrating IVIF-DANP can accurately differentiate the relative merits of different maintenance plans.
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表 1 区间直觉模糊DEMATEL量表
Table 1. Interval-valued intuitionistic fuzzy DEMATEL scale
语言术语 表示 区间直觉模糊数（IVIFN） 无影响 N （[0，0.15],[0.7,0.85]） 影响程度很低 VL （[0.1，0.25],[0.6,0.75]） 影响程度低 L （[0.2，0.35],[0.5,0.65]） 影响程度一般 ML （[0.3，0.45],[0.4,0.55]） 影响程度中等 M （[0.5，0.5],[0.5,0.5]） 影响程度较高 MH （[0.4，0.55],[0.3,0.45]） 影响程度高 H （[0.5，0.65],[0.2,0.35]） 影响程度非常高 VH （[0.6，0.75],[0.1,0.25]） 影响程度极高 EH （[0.7，0.85],[0,0.15]） 
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表 2 专家权值分配表
Table 2. Expert weight distribution
因素 等级 得分 工作经验 超过20年 5 10～19年 4 5～9年 3 2～5年 2 2年以下 1 专业相关度 高 5 中高 4 中 3 中低 2 低 1
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表 3 指标间相对重要性评估量表
Table 3. Scale for evaluating relative importance among indicators
语言术语 表示 区间直觉模糊数（IVIFNs） 极低重要性 CLI （[0.1，0.25],[0.65,0.75]） 非常低重要性 VLI （[0.15，0.3],[0.6,0.7]） 低重要性 L （[0.2，0.35],[0.55,0.65]） 较低重要性 BL （[0.25，0.4],[0.5,0.6]） 同等重要性 I （[0.5，0.5],[0.5,0.5]） 较强重要性 AI （[0.5，0.6],[0.25,0.4]） 高重要性 HI （[0.55，0.65],[0.2,0.35]） 非常高重要性 VHI （[0.6，0.7],[0.15,0.3]） 极度重要性 CHI （[0.65，0.75],[0.1,0.25]）
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表 4 各评价指标评分
Table 4. Scoring table for evaluation indicators
语言术语 表示 区间直觉模糊数（IVIFNs） 几乎为0 CB （[0，0.15],[0.7,0.85]） 非常低 VB （[0.1，0.25],[0.6,0.75]） 低 B （[0.2，0.35],[0.5,0.65]） 较低 BA （[0.3，0.45],[0.4,0.55]） 中等 A （[0.5，0.5],[0.5,0.5]） 较高 AA （[0.4，0.55],[0.3,0.45]） 高 G （[0.5，0.65],[0.2,0.35]） 非常高 VG （[0.6，0.75],[0.1,0.25]） 几乎满分 CG （[0.7，0.85],[0,0.15]）
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表 5 3位专家成员权重信息
Table 5. Expert member weights
专家 $ \lambda_{i}^{2} $ $ \eta_{\mathrm{k}} $ $ \lambda_{i}^{\circ} $ 1 0.40 18 0.38 2 0.32 24 0.29 3 0.28 21 0.33
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表 6 专家对主指标之间影响关系评价
Table 6. Expert assessments of influence relationships among main indicators
主指标 C1 C2 C3 C4 C1 / M/M/ML ML/L/L H/MH/H C2 VL/VL/L / M/ML/MH H/MH/M C3 H/MH/MH M/ML/M / H/VH/VH C4 MH/MH/M M/MH/M H/M/H /
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表 7 C4内部依赖关系矩阵
Table 7. Internal dependency matrix under C4
指标 C41 C42 C43 C41 / M/M/ML H/H/M C42 M/L/L / H/M/H C43 M/ML/L ML/L/M /
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表 8 C3内部依赖关系矩阵
Table 8. Internal dependency matrix under C3
指标 C31 C32 C33 C34 C31 / M/ML/ML H/H/M M/M/MH C32 M/M/L / MH/MH/H M/ML/ML C33 ML/MH/M ML/L/M / L/L/ML C34 VH/MH/MH MH/MH/MH M/M/M /
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表 9 以C11为评价准则的判断矩阵
Table 9. Judgment matrix with C11 as evaluation criterion
C11 C41 C42 C43 C41 （[0.5,0.5],[0.5,0.5]） （[0.551，0.629],[0.239,0.371]） （[0.214，0.364],[0.536,0.636]） C42 （[0.239,0.371], [0.551，0.629]） （[0.5,0.5],[0.5,0.5]） （[0.623，0.723],[0.125,0.276]） C43 （[0.536,0.636], [0.214，0.364]） （[0.125,0.276], [0.623，0.723]） （[0.5,0.5],[0.5,0.5]）
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表 10 加权超矩阵
Table 10. Weighted supermatrix
指标 C11 C12 C21 C22 C23 C31 C32 C33 C34 C41 C42 C43 C11 0 0 0 0 0 0.141 0.131 0.083 0.135 0 0 0 C12 0 0 0 0 0 0.094 0.104 0.152 0.100 0 0 0 C21 0 0 0 0 0 0.078 0.115 0.137 0.102 0 0 0 C22 0 0 0 0 0 0.081 0.080 0.049 0.059 0 0 0 C23 0 0 0 0 0 0.077 0.040 0.049 0.074 0 0 0 C31 0 0 0 0 0 0.116 0.116 0 0.119 0.063 0.053 0.055 C32 0 0 0 0 0 0 0 0 0 0.088 0.105 0.079 C33 0 0 0 0 0 0.124 0.124 0 0.121 0.138 0.150 0.163 C34 0 0 0 0 0 0 0 0 0 0.173 0.135 0.165 C41 0.342 0.491 0.130 0.334 0.585 0.148 0.092 0.139 0.106 0 0 0 C42 0.363 0.334 0.366 0.339 0.207 0.054 0.090 0.102 0.102 0.239 0 0 C43 0.295 0.176 0.504 0.327 0.207 0.088 0.108 0.049 0.083 0.292 0.530 0.530
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表 11 各评价指标在不同维修方式下的评分
Table 11. Scores of evaluation indicators under different maintenance methods
指标 a b c C11 B/BA/BA VB/B/B VB/VG/VG C12 CB/BA/B A/A/A B/CB/B C21 VB/B/CB VG/A/AA AA/A/G C22 A/BA/AA VG/VG/AA A/A/VG C23 BA/AA/VG VB/VB/B AA/AA/B C31 A/A/A AA/G/A A/A/G C32 A/G/A A/G/A B/VG/A C33 BA/BA/BA BA/A/A A/G/G C34 A/AA/AA CG/G/G A/G/BA C41 VG/G/AA AA/VG/G CG/VG/VG C42 BA/A/AA G/A/BA VG/G/G C43 G/A/A G/VG/VG G/CG/CG
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表 12 改变专家权重场景
Table 12. Scenarios with varying expert weights
场景 专家1 专家2 专家3 S1 0.45 0.28 0.27 S2 0.27 0.45 0.28 S3 0.28 0.27 0.45 S4 0.333 0.333 0.333
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表 13 不同模糊环境维修方案评分排序
Table 13. Scores and rankings of maintenance plans under different fuzzy environments
方案 1-9 标度DANP 三角模糊数DANP IVIF-DANP 评分 排序 评分 排序 评分 排序 a 7.233 1 （0.412, 0.576, 0.698） 3 0.451 3 b 6.713 3 （0.634, 0.789, 0.921） 1 0.374 2 c 6.927 2 （0.527, 0.689, 0.813） 2 0.338 1
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