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Reliability allocation of rotary ultrasonic vibration-assisted EDM machine tool based on maximum entropy ordered weighted average and constraint under the index of overall cost

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Abstract

In this paper, the reliability allocation and index of overall cost of rotary ultrasonic vibration-assisted EDM machine tool were studied. The failure rate of each module of the rotary ultrasonic vibration-assisted EDM machine tool can be accurately predicted by the maximum entropy ordered weighted average algorithm so that the corrected maintenance cost can be predicted. And effective control of preventive maintenance costs can be achieved by selecting the best maintenance times under the premise of reliability. The cost of corrective maintenance can be reduced by improving modules with a high failure rate, so as to realize the purpose of cost optimization under the premise of determining the maintenance time and reliability. The reliability function of the rotary ultrasonic vibration-assisted EDM machine tool is established according to the series-parallel relationship of each module. The results showed that the reliability of rotary ultrasonic vibration-assisted EDM machine tool is stabler at the non-fixed maintenance period according to the comparison between the non-fixed and the fixed maintenance period.

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References

  1. Maity KP, Choubey M (2019) A review on vibration-assisted EDM, micro-EDM and WEDM. Surf Rev Lett 26(05):1830008. https://doi.org/10.1142/S0218625X18300083

    Article  Google Scholar 

  2. Sabyrov N, Jahan MP, Bilal A et al (2019) Ultrasonic vibration assisted electro-discharge machining (edm)—an overview. Materials 12(3):522. https://doi.org/10.3390/ma12030522

    Article  Google Scholar 

  3. Tsai MY, Fang CS, Yen MH (2018) Vibration-assisted electrical discharge machining of grooves in a titanium alloy (Ti-6A-4V). Int J Adv Manuf Technol 97(1):297–304. https://doi.org/10.1007/s00170-018-1904-2

    Article  Google Scholar 

  4. Yinghuai D, Jianbao S, Guangyan L, Yan W, Wei X (2021) Research on non-contact ultrasonic vibration assisted rotating electrical discharge machining (EDM) machine tool. International Journal of Nanomanufacturing 17(1):1–12. https://doi.org/10.1504/IJNM.2021.113298

    Article  Google Scholar 

  5. Wang Y, Liu Z, Shi J, Dong Y, Yang S, Zhang X, Lin B (2020) Analysis of material removal and surface generation mechanism of ultrasonic vibration–assisted EDM. Int J Adv Manuf Technol 110(1):177–189. https://doi.org/10.1007/s00170-020-05769-x

    Article  Google Scholar 

  6. Hirao A, Gotoh H, Tani T (2018) Some effects on EDM characteristics by assisted ultrasonic vibration of the tool electrode. Procedia CIRP 68:76–80. https://doi.org/10.1016/j.procir.2017.12.025

    Article  Google Scholar 

  7. Kumar S, Grover S, Walia RS (2018) Analyzing and modeling the performance index of ultrasonic vibration assisted EDM using graph theory and matrix approach. International Journal on Interactive Design and Manufacturing (IJIDeM) 12(1):225–242. https://doi.org/10.1007/s12008-016-0355-y

    Article  Google Scholar 

  8. Lin YC, Chuang FP, Wang AC, Chow HM (2014) Machining characteristics of hybrid EDM with ultrasonic vibration and assisted magnetic force. Int J Precis Eng Manuf 15(6):1143–1149. https://doi.org/10.1007/s12541-014-0449-z

    Article  Google Scholar 

  9. Shervani-Tabar MT, Maghsoudi K, Shabgard MR (2013) Effects of simultaneous ultrasonic vibration of the tool and the workpiece in ultrasonic assisted EDM. International Journal for Computational Methods in Engineering Science and Mechanics 14(1):1–9. https://doi.org/10.1080/15502287.2012.698696

    Article  Google Scholar 

  10. Teimouri R, Baseri H (2013) Experimental study of rotary magnetic field-assisted dry EDM with ultrasonic vibration of workpiece. Int J Adv Manuf Technol 67(5-8):1371–1384. https://doi.org/10.1007/s00170-012-4573-6

    Article  Google Scholar 

  11. Cheng Q, Wang H, Liu Z, Zhang C, Sun D, Qi B (2019) Reliability allocation method based on maximum entropy ordered weighted average and hesitant fuzzy Linguistic term set. J Intell Fuzzy Syst 37(6):7991–8004. https://doi.org/10.3233/JIFS-190376

    Article  Google Scholar 

  12. Maldonado S, Merigó J, Miranda J (2018) Redefining support vector machines with the ordered weighted average. Knowl-Based Syst 148:41–46. https://doi.org/10.1016/j.knosys.2018.02.025

    Article  Google Scholar 

  13. Chaji A (2017) Analytic approach on maximum Bayesian entropy ordered weighted averaging operators. Comput Ind Eng 105:260–264. https://doi.org/10.1016/j.cie.2016.12.041

    Article  Google Scholar 

  14. Kabir G, Tesfamariam S, Loeppky J et al (2015) Integrating Bayesian linear regression with ordered weighted averaging: uncertainty analysis for predicting water main failures. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering 1(3):04015007. https://doi.org/10.1061/AJRUA6.0000820

    Article  Google Scholar 

  15. Yari G, Chaji AR (2012) Maximum Bayesian entropy method for determining ordered weighted averaging operator weights. Comput Ind Eng 63(1):338–342. https://doi.org/10.1016/j.cie.2012.03.010

    Article  Google Scholar 

  16. Ahn BS (2011) Compatible weighting method with rank order centroid: maximum entropy ordered weighted averaging approach. Eur J Oper Res 212(3):552–559. https://doi.org/10.1016/j.ejor.2011.02.017

    Article  MATH  Google Scholar 

  17. Treanţă S (2021) On a class of constrained interval-valued optimization problems governed by mechanical work cost functionals. J Optim Theory Appl 188(3):913–924. https://doi.org/10.1007/s10957-021-01815-0

    Article  MATH  Google Scholar 

  18. Xiao H, Zhang R, Chen Z, Liu Y, Zhou Y (2020) Maintenance cycle optimisation of multi-component systems under the constraints of overall cost and reliability. Int J Embed Syst 13(2):148–157. https://doi.org/10.1504/IJES.2020.108862

    Article  Google Scholar 

  19. Liu J, Chen Q, Liang X, To AC (2019) Manufacturing cost constrained topology optimization for additive manufacturing. Front Mech Eng 14(2):213–221. https://doi.org/10.1007/s11465-019-0536-z

    Article  Google Scholar 

  20. Klanšek U (2019) Cost optimization of project schedules under constrained resources and alternative production processes by mixed-integer nonlinear programming. Eng Constr Archit Manag 26:2474–2508. https://doi.org/10.1108/ECAM-01-2019-0013

    Article  Google Scholar 

  21. Domínguez-Isidro S, Mezura-Montes E (2018) A cost-benefit local search coordination in multimeme differential evolution for constrained numerical optimization problems. Swarm and evolutionary computation 39:249–266. https://doi.org/10.1016/j.swevo.2017.10.006

    Article  Google Scholar 

  22. O’Hagan M (1988) Aggregating template or rule antecedents in real-time expert systems with fuzzy set logic[C]//Twenty-second Asilomar conference on signals, systems and computers. IEEE 2:681–689. https://doi.org/10.1109/ACSSC.1988.754637

    Article  Google Scholar 

  23. Fullér R, Majlender P (2001) An analytic approach for obtaining maximal entropy OWA operator weights. Fuzzy Sets Syst 124(1):53–57. https://doi.org/10.1016/S0165-0114(01)00007-0

    Article  MATH  Google Scholar 

  24. Guo S, Sun Y, Zhao G et al (2016) Optimization of maintenance strategy for multi-component system subject to degradation process[C]//2016 Prognostics and System Health Management Conference (PHM-Chengdu). IEEE:1–6. https://doi.org/10.1109/PHM.2016.7819854

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Availability of data and materials

The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.

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Funding

National Natural Science Foundation of China (51205005)

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Authors and Affiliations

  1. School of Mechanical and Materials Engineering, North China University of Technology, No. 5, Jinyuanzhuang Road, Shijingshan District, Beijing, China

    Minggang Xu, Hao Fu, Wang Tian, Binbin Lyu, Zihao Jiang & Baosheng Guan

Authors
  1. Minggang Xu
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  2. Hao Fu
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  3. Wang Tian
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  4. Binbin Lyu
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  5. Zihao Jiang
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  6. Baosheng Guan
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Contributions

Minggang Xu and Hao Fu: validation, analysis, investigation, writing of the original draft.

Wang Tian and Binbin lyu: data calculation, analysis, investigation, writing review.

Zihao Jiang and Baosheng Guan: investigation, analysis, writing review.

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Correspondence to Hao Fu.

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Xu, M., Fu, H., Tian, W. et al. Reliability allocation of rotary ultrasonic vibration-assisted EDM machine tool based on maximum entropy ordered weighted average and constraint under the index of overall cost. Int J Adv Manuf Technol 124, 4639–4648 (2023). https://doi.org/10.1007/s00170-021-07420-9

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