Research on comprehensive evaluation of six properties of equipment product with relevant attributes based on DEMATEL-ANP-ELECTRE

doi:10.23919/JSEE.2026.000007

Abstract

Abstract:

The comprehensive evaluation of six properties for equipment product is an important basis for their quality control, and their correlative relationship among six properties will affect their quality level. To understand their correlative relationship among six properties, this paper firstly combines group evaluation with decision-making trial and evaluation laboratory (DEMATEL) model, and develops the optimization model based on group consensus to form six influent relationship matrices. Secondly, group consensus matrix is used to design super network hierarchy matrix, and the weights of six properties with relevant environment is also proposed. Thirdly, the elimination and choice translating reality (ELECTRE) model is used to make comprehensive evaluation, and an example is used to compare the results under two kinds of conditions, and illustrate the effect of the weights of six properties on the priority of equipment products.

Key words: six properties, decision-making trial and evaluation laboratory, elimination and choice translating reality, relevant

Jian QIN, Wenhui MEI. Research on comprehensive evaluation of six properties of equipment product with relevant attributes based on DEMATEL-ANP-ELECTRE[J]. Journal of Systems Engineering and Electronics, 2026, 37(1): 318-326.

Figures/Tables 3

References 30

1	ZHENG J, WANG Y M, ZHANG K, et al A heterogeneous multi-attribute case retrieval method for emergency decision making based on bidirectional projection and TODIM. Expert Systems with Applications, 2022, 203, 117382. doi: 10.1016/j.eswa.2022.117382
2	PENG L S, ZHOU X Z, ZHAO J J, et al Three-way multi-attribute decision making under incomplete mixed environments using probabilistic similarity. Information Sciences, 2022, 614, 413- 463. doi: 10.1016/j.ins.2022.10.038
3	LI C C, DONG Y C, LIANG H M, et al Data-driven method to learning personalized individual semantics to support linguistic multi-attribute decision making. Omega, 2022, 111, 102642. doi: 10.1016/j.omega.2022.102642
4	REZAEI M Prioritization of biodiesel development policies under hybrid uncertainties: a possibilistic stochastic multi-attribute decision-making approach. Energy, 2022, 260, 125074. doi: 10.1016/j.energy.2022.125074
5	WANG J J, MA X L, XU Z S, et al A three-way decision method with prospect theory to multi-attribute decision-making and its applications under hesitant fuzzy environments. Applied Soft Computing, 2022, 126, 109283. doi: 10.1016/j.asoc.2022.109283
6	ZHANG C, DING J J, ZHAN J M, et al Incomplete three-way multi-attribute group decision making based on adjustable multi granulation Pythagorean fuzzy probabilistic rough sets. International Journal of Approximate Reasoning, 2022, 147, 40- 59. doi: 10.1016/j.ijar.2022.05.004
7	SUN B Z, ZHANG X R, QI CH, et al Neighborhood relation-based variable precision multigranulation Pythagorean fuzzy rough set approach for multi-attribute group decision making. International Journal of Approximate Reasoning, 2022, 15, 11- 20. doi: 10.1016/j.ijar.2022.09.002
8	RAO C J, GAO M Y, WEN J H, et al multi-attribute group decision making method with dual comprehensive clouds under information environment of dual uncertain Z-numbers. Information Sciences, 2022, 602, 106- 127. doi: 10.1016/j.ins.2022.04.031
9	TIAN X L, LI W Q, XU Z S, et al An endo-confidence-based consensus with hierarchical clustering and automatic feedback in multi-attribute large-scale group decision-making. Information Sciences, 2022, 608, 1702- 1730. doi: 10.1016/j.ins.2022.07.042
10	HUANG T, TANG X A, ZHAO S Y, et al Linguistic information-based granular computing based on a tournament selection operator-guided PSO for supporting multi-attribute group decision-making with distributed linguistic preference relations. Information Sciences, 2022, 610, 488- 507. doi: 10.1016/j.ins.2022.07.050
11	GITINAVARD H, MOUSAVI S M, VAHDANI B Soft computing based on hierarchical evaluation approach and criteria interdependencies for energy decision-making problems: a case study. Energy, 2017, 118, 556- 567.
12	KOJADINOVIC I. Minimum variance capacity identification. European Journal of Operational Research, 2007, 177: 498–514
13	WU J Z , YANG S L, ZHANG Q, et al. 2-additive capacity identification methods from multicriteria correlation preference information. IEEE Trans. on Fuzzy Systems, 2015, 23(6): 2094−2103.
14	LUIZ F A M G, MARIA A S M, FRANCISCO F C, et al. Criteria interactions in multiple criteria decision aiding: A Choquet formulation for the TODIM method, Procedia Computer Science, 2013, 17: 324−331.
15	MENG F Y, ZHANG Q Induced continuous Choquet integral operators and their application to group decision making. Computers & Industrial Engineering, 2014, 68, 42- 53. doi: 10.1016/j.cie.2013.11.013
16	SAVIZ M, MIRZA M S, LUCE C Determination of the fuzzy measures for multicriteria and optimal design of a building façade using Choquet integrals. Journal of Building Engineering, 2019, 26, 100877. doi: 10.1016/j.jobe.2019.100877
17	MEHDI D, AHMADI M, EBRAHIMI E, et al A probabilistic hesitant fuzzy Choquet integral-based TODIM method for multi-attribute group decision-making. Expert Systems with Applications, 2022, 191, 116266. doi: 10.1016/j.eswa.2021.116266
18	BUYUKOZKAN G A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers. Expert Systems with Applications, 2012, 39, 3000- 3011. doi: 10.1016/j.eswa.2011.08.162
19	ADIL B. Development of an interval type-2 fuzzy sets based hierarchical MADM model by combining DEMATEL and TOPSIS. Expert Systems with Applications, 2017, 70: 37−51.
20	MARCO S, BERND M Z, ALEXANDER P, et al. Visualizing interdependencies among sustainability criteria to support multicriteria decision-making processes in building design. Procedia CIRP, 2018, 69: 200 – 205.
21	LIU X H, DENG Q W, GONG G L, et al Evaluating the interactions of multi-dimensional value for sustainable product-service system with grey DEMATEL-ANP approach. Journal of Manufacturing Systems, 2021, 60, 449- 458. doi: 10.1016/j.jmsy.2021.07.006
22	MOHANDES S R, HALEH S, FAZELI A, et al Causal analysis of accidents on construction sites: a hybrid fuzzy Delphi and DEMATEL approach. Safety Science, 2022, 151, 105730. doi: 10.1016/j.ssci.2022.105730
23	GUO J, XIANG P C, WANG X, et al Predicting and managing megaproject gray rhino risks with IF-ANP and DEMATEL based on panel data. Expert Systems with Applications, 2022, 208, 118243. doi: 10.1016/j.eswa.2022.118243
24	TSAI P H, WANG Y W, KAO H S Applying DEMATEL-ANP approach to explore the intention to hold roadside wedding banquets in Penghu: a consumers’ perspective. Evaluation and Program Planning, 2022, 95, 102172. doi: 10.1016/j.evalprogplan.2022.102172
25	HU K H An exploration of the key determinants for the application of AI-enabled higher education based on a hybrid soft-computing technique and a DEMATEL approach. Expert Systems with Applications, 2023, 212, 118762. doi: 10.1016/j.eswa.2022.118762
26	XIAO Y, WEI S B, CHAI Y, et al Reliability optimization of flexible test system based on pyro-mechanical device products production driven. Reliability Engineering & System Safety, 2024, 245, 109742. doi: 10.1016/j.ress.2022.108880
27	PHILIPP Z, BADR S, STEPHANIE K, et al Data-driven equipment condition monitoring and reliability assessment for sterile drug product manufacturing: method and application for an operating facility. Chemical Engineering Research and Design, 2022, 188, 301- 314. doi: 10.1016/j.cherd.2022.09.005
28	LIU N M, ZHANG R, LIU B Contracting and diagnostic test for new product development under uncertain production reliability. Computers & Industrial Engineering, 2022, 173, 108740. doi: 10.1016/j.cie.2022.108740
29	GUO Z Y, ZHOU D, CHEN J Y, et al Using virtual reality to support the product’s maintainability design: immersive maintainability verification and evaluation system. Computers in Industry, 2018, 101, 41- 50. doi: 10.1016/j.compind.2018.06.007
30	YAN L, QIAN C D, SHI J T, et al The influencing factors of evaporation residue of emulsified modified asphalt to optimize the environmental adaptability. Construction and Building Materials, 2022, 356, 129169. doi: 10.1016/j.conbuildmat.2022.129169

Index	$ {f}_{i} $	$ {e}_{i} $	$ {m}_{i} $	$ {n}_{i} $
Reliability	0.8024	0.6486	1.4509	0.1538
Maintainability	0.6864	1.2892	1.9756	−0.6029
Testability	0.8412	0.4343	1.2755	0.4069
Safety	0.6364	1.5648	2.2012	−0.9284
Supportability	0.9198	0.0000	0.9198	0.9199
Environmental adaptability	0.7866	0.7359	1.5225	0.0507

Index	Reliability	Maintainability	Testability	Safety	Supportability	Environmental adaptability
Reliability	0.113	0.261	0.075	0.223	0.214	0.111
Maintainability	0.132	0.136	0.134	0.208	0.211	0.050
Testability	0.137	0.253	0.180	0.092	0.166	0.265
Safety	0.211	0.000	0.121	0.137	0.171	0.183
Supportability	0.187	0.211	0.294	0.170	0.113	0.230
Environmental adaptability	0.220	0.140	0.196	0.170	0.125	0.161

Equipment product	Reliability	Maintainability	Testability	Safety	Supportability	Environmental adaptability
$ {a}_{1} $	0.98	0.88	0.87	0.98	0.84	0.91
$ {a}_{2} $	0.95	0.92	0.89	0.97	0.86	0.94
$ {a}_{3} $	0.99	0.87	0.88	0.92	0.85	0.92
$ {a}_{4} $	0.97	0.91	0.85	0.93	0.89	0.90