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Application of the analytic hierarchy process-fuzzy comprehensive evaluation method to assess the quality of electrophoresis on heavy-duty vehicle frames

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The evaluation methods used to examine the quality of electrophoresis painting applied to heavy-duty vehicle frames in the automotive industry are not comprehensive. Therefore, this investigation presents such a method based on the present manufacturing situation concerning the electrophoresis process for frames, using an evaluation index system designed for frame electrophoresis quality management. Based on the previous literature, the analytic hierarchy processand the fuzzy evaluation method are employed in this study for the evaluation. Per the principle of maximum membership, we assessed the production quality of heavy-duty vehicle frames. The presentation quality was deemed “average,” while the paint film quality, corrosion resistance was good, and comprehensive evaluation grade were found to be “good.”. Together, these results contribute to the state of the art by facilitating an accurate evaluation of the quality of vehicle frame electrophoresis, improving the electrophoresis process for heavy-duty vehicle frames.
Twórcy
autor
  • China National Heavy Truck Group Co., Ltd., Hua’ao Road, Jinan, China
autor
  • Army Engineering University of PLA, Hou Biao Ying Road, Nanjing, China
Bibliografia
  • 1. Zhu, Z.C.; Guo, R.F.; Nie, G.Z. Experimental study on heavy truck frame electrophoresis process. Development & Innovation of Machinery & Electrical Products 2017, 30, 17–19.
  • 2. Xiang, L.Q.; Wu, J.X. Reason analysis and solution for poor adhesion of electrophoretic paint film on light truck frame. Electroplating & Finishing 2022, 30, 399–402. https://doi.org/10.19289/j.1004-227x.2022.06.005
  • 3. Zhu, Z.C.; Wei, J.C.; Guo, R.F. Fuzzy evaluation of electrophoretic quality of heavy-duty vehicle frames. Electroplating & Finishing 2018, 37, 80–82. https://doi.org/10.19289/j.1004-227x.2018.02.008
  • 4. Yang, T.Y.; Wang, H.T.; Chen, Z.Z. Analysis and solution of quality issues in electrophoretic coatings. Electroplating & Finishing 2020, 39, 1563–1568. https://doi.org/10.19289/j.1004-227x.2020.22.009
  • 5. Zheng, N. Brief analysis of quality control in pretreatment and e-coating processes. Modern Paint and Finishing 2019, 22, 45–48.
  • 6. Dai, S.H.; Wang, P.; Wang, L. Effect of takt improvement on auto body electrophoresis quality & improvement. Automobile Technology & Material 2020, 11, 45–48. https://doi.org/10.19710/J.cnki.1003-8817.20200044
  • 7. Valerio A, P.S.; Luiz F, A.M.G. Consistency improvement in the analytic hierarchy process. Mathematics 2024, 12, 828. https://doi.org/10.3390/math12060828
  • 8. Zhu, Q.X.; Luo, P.P.; Wang, P.P. Operation process identification for intelligent drill rig base on analytic hierarchy process. Meitiandizhi Yu Kantan/Coal Geology and Exploration 2024, 52, 184–190. https://doi.org/10.12363/issn.1001-1986.23.06.0327
  • 9. Xue, B.; Lu, F.; Guo, J. Research on energy efficiency evaluation model of substation building based on AHP and fuzzy comprehensive theory. Sustainability 2023, 15, 14493. https://doi.org/10.3390/su151914493
  • 10. Saucedo-Martinez J, A.; Salais-Fierro T, E.; Rodriguez-Aguilar, R. Selecting the distribution system using AHP and Fuzzy AHP methods. Mobile networks & applications 2024, 1, 235–242. https://doi.org/10.1007/s11036-023-02290-9
  • 11. Saaty T.L.; Vargas L.G. Inconsistency and rank preservation. Journal of Mathematical Psychology 1984, 28, 205–214. https://doi.org/10.1016/0022-2496(84)90027-0
  • 12. Saaty T.L. A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology 1977, 15, 234–281. https://doi.org/10.1016/0022-2496(77)90033-5
  • 13. Saaty T.L.; Majak. How to make a decision: The analytic hierarchy process. European Journal of Operational Research 1991, 48, 9–26. https://doi.org/10.1016/0377-2217(90)90057-I
  • 14. Wu, J.; He, Y.; Zhao, J.L. An infrared target images recognition and processing method based on the fuzzy comprehensive evaluation. IEEE Access 2024, 12, 12126–12137. https://doi.org/10.1109/ACCESS.2024.3355157
  • 15. Zheng, W.Q.; Xu, X.S.; Wang, Z.C. Fuzzy comprehensive evaluation of collapse risk in mountain tunnels based on game theory. Applied Sciences 2024, 14, 5163. https://doi.org/10.3390/app14125163
  • 16. Peng, D.; Wei, T.; Zhao, H. Information security risk assessment of control systems in thermal power plants based on D-AHP and TOPSIS. Control and Decision 2019, 34, 2445–2451. https://link.cnki.net/doi/10.13195/j.kzyjc.2019.0240
  • 17. Wu, B.; Wei, Y.; Meng, G. Multi-source monitoring data fusion comprehensive evaluation method for the safety status of deep foundation pit. Sustainability 2023, 15, 11809. https://doi.org/10.3390/su151511809
  • 18. Li, W.T.; Yin, H.Y.; Song, Y.L. Evaluating the risk of social isolation in older people: AHP-fuzzy comprehensive evaluation. Risk management and healthcare policy 2023, 16, 79–92.https://doi.org/10.2147/RMHP.S383031
  • 19. Luo, D.J.; Huang, J.; Liang, Y. Comprehensive evaluation of green mine construction level considering fuzzy factors using intuitionistic fuzzy TOPSIS with kernel distance: AHP-Fuzzy Comprehensive Evaluation. Environmental Science and Pollution Research 2024, 31, 16884–16898. https://doi.org/10.1007/s11356-023-31812-x
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3b29f90c-fc69-4cf9-85bf-e49af722411f
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