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Rigid-flexible coupling virtual prototyping-based approach to the failure mode, effects, and criticality analysis

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Abstract

The reliability analysis is a quantification of the sources of failures in a product, with emphasis on the most significant contributors towards the overall product unreliability. As the reliability analysis of complex products is very crucial for analyzing the behavior of the products, many researches have been focused on it in recent decades with a result of many valuable contributions. However, current researches always focus on rigid product, while the product is always a rigid-flexible coupling multibody system, which could affect the accuracy of reliability analysis. This paper is devoted to virtual prototyping-based approach to a fuzzy Failure Mode, Effects, and Criticality Analysis (FMECA) with the consideration of rigid-flexible coupling virtual prototyping model. This paper discussed proposed approach in detail with three steps: the traditional FMECA method, the fuzzy FMECA method, and the rigid-flexible coupling-based analysis for FEMCA. The cold heading machine is given as an example which demonstrates that the methodology is helpful to reliability analysis. The physical prototyping is also carried out to demonstrate the product reliability.

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References

  1. Hoyland A, Rausand M (2004) System reliability theory: models, statistical methods, and applications. Wiley-Interscience, NJ

    MATH  Google Scholar 

  2. Verma AK, Srividya A, Karanki DR (2016) Reliability and safety engineering. Springer London, London

    Google Scholar 

  3. Aramesh M, Rimpault X, Klim ZH, Balazinski M (2013) Wear dependent tool reliability analysis during cutting titanium metal matrix composites (Ti-MMCs). SAE Int J Aerospace 6(2):492–498

    Article  Google Scholar 

  4. He X (2016) Recent development in reliability analysis of NC machine tools. Int J Adv Manuf Technol 85(1):115–131

    Article  Google Scholar 

  5. Garcia PAA, Schirru R (2005) A fuzzy data envelopment analysis approach for FMEA. Prog Nucl Energ 46:359–373

    Article  Google Scholar 

  6. Okaro IA, Tao L (2016) Reliability analysis and optimisation of subsea compression system facing operational covariate stresses. Reliab Eng Syst Safe 156:159–174

    Article  Google Scholar 

  7. He B, Pan QJ, Deng ZQ (2018c) Product carbon footprint for product life cycle under uncertainty. J Clean Prod 187:459–472

    Article  Google Scholar 

  8. Guaragni F, Schmidt T, Paetzold K (2016) Traditional and agile product development in a hyperconnected world: turning weaknesses into strengths. Procedia CIRP 52:62–67

    Article  Google Scholar 

  9. Misra KB (2012) Reliability analysis and prediction: a methodology oriented treatment. Elsevier Science, Amsterdam

    Google Scholar 

  10. Schoefs F, Chevreuil M, Pasqualini O, Cazuguel M (2016) Partial safety factor calibration from stochastic finite element computation of welded joint with random geometries. Reliab Eng Syst Safe 155:44–54

    Article  Google Scholar 

  11. Bowles JB, Pelaez CE (1995) Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis. Reliab Eng Syst Safe 50:203–213

    Article  Google Scholar 

  12. Sankar NR, Prabhu BS (2001) Modified approach for prioritization of failures in a system failure mode and effects analysis. Int J Qual Reliab Manag 18:324–336

    Article  Google Scholar 

  13. He B, Zhou G, Hou S, Zeng L (2017a) Virtual prototyping-based fatigue analysis and simulation of crankshaft. Int J Adv Manuf Technol 88:2631–2650

    Article  Google Scholar 

  14. Franceschini F, Galetto M (2001) A new approach for evaluation of risk priorities of failure modes in FMEA. Int J Prod Res 39:2991–3002

    Article  Google Scholar 

  15. Gargama H, Chaturvedi SK (2011) Criticality assessment models for failure mode effects and criticality analysis using fuzzy logic. IEEE Trans Reliab 60:102–110

    Article  Google Scholar 

  16. Keskin GA, Ozkan C (2009) An alternative evaluation of FMEA: fuzzy ART algorithm. Qual Reliab Eng Int 25:647–661

    Article  Google Scholar 

  17. Chin KS, Chan A, Yang JB (2008) Development of a fuzzy FMEA based product design system. Int J Adv Manuf Technol 36:633–649

    Article  Google Scholar 

  18. Kutlu AC, Ekmekçioğlu M (2012) Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP. Expert Syst Appl 39:61–67

    Article  Google Scholar 

  19. Parracho SA (2012) Probabilistic priority numbers for failure modes and effects analysis. Int J Qual Reliab Manag 29:349–362

    Article  Google Scholar 

  20. He B, Luo T, Huang S (2018a) Product sustainability assessment for product life cycle. J Clean Prod (In press)

  21. He B, Niu YC, Hou SC, Li FF (2018b) Sustainable design from functional domain to physical domain. J Clean Prod 197:1296–1306

    Article  Google Scholar 

  22. Ibrahim MH, Kharmanda G, Charki A (2015) Reliability-based design optimization for fatigue damage analysis. Int J Adv Manuf Technol 76(5–8):1021–1030

    Article  Google Scholar 

  23. He B, Xiao JL, Deng ZQ (2018d) Product design evaluation for product environmental footprint. J Clean Prod 172:3066–3080

    Article  Google Scholar 

  24. He B, Zhou G, Hou S, Zeng L (2017b) An approach to computational co-evolutionary product design. Int J Adv Manuf Technol 90:249–265

    Article  Google Scholar 

  25. Abebe M, Park JW, Kang BS (2017) Reliability-based robust process optimization of multi-point dieless forming for product defect reduction. Int J Adv Manuf Technol 89(1):1223–1234

    Article  Google Scholar 

  26. He B, Tang W, Cao JT (2014) Virtual prototyping-based multibody systems dynamics analysis of offshore crane. Int J Adv Manuf Technol 75:161–180

    Article  Google Scholar 

  27. He B, Zhou GF, Hou SC, Zeng LB (2016b) Virtual prototyping-based fatigue analysis and simulation of crankshaft. Int J Adv Manuf Technol 88(9):2631–2650

    Google Scholar 

  28. Gao ZG, Zeng LB, He B, Luo T, Zhang PC (2018) Type synthesis of non-holonomic spherical constraint underactuated parallel robotics. Acta Astronaut (In Press)

  29. He B, Wang J, Huang S, Wang Y (2015) Low-carbon product design for product life cycle. J Eng Des 26(10–12):321–339

    Article  Google Scholar 

  30. Shabana AA (2013) Dynamics of multibody systems. Cambridge University Press

  31. Zimmermann HJ (2011) Fuzzy set theory—and its applications. Springer Science & Business Media

  32. Zhu CZ, Tang Q, Huang ZH et al (2009) Dynamic study for driver-motorcycle-road system with rigid-flexible coupling. Chin J Mech Eng 45(5):225–229 [In Chinese]

    Article  Google Scholar 

  33. Cold HM (2014) Common faults of cold heading machine and its solution. RAYLITER. http://www.rayliter.com/html/192470552.html. Accessed 21 Aug 2014

  34. Sun M (2006) Causes of common faults of automatic cold heading machine and their elimination. Fasten Technol 3:12–14

    Google Scholar 

  35. He B, Hua Y (2017) Feature-based integrated product model for low-carbon conceptual design. J Eng Des 28(6):408–432

    Article  Google Scholar 

  36. He B, Tang W, Huang S, Hou S., Cai H. (2016a) Towards low-carbon product architecture using structural optimization for lightweight. Int J Adv Manuf Technol 83(5–8): 1419–1429

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Funding

The work was supported by the National Natural Science Foundation of China (No. 51675319).

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Authors and Affiliations

  1. Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, 149 Yanchang Rd, Shanghai, 200072, People’s Republic of China

    Bin He, Haojun Xue, Lilan Liu, Qijun Pan & Wen Tang

  2. Laboratoire IRTES-M3M, Université de Technologie de Belfort-Montbéliard, Sevenans, France

    Egon Ostrosi

Authors
  1. Bin He
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  2. Haojun Xue
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  3. Lilan Liu
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  4. Qijun Pan
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  5. Wen Tang
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  6. Egon Ostrosi
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Corresponding author

Correspondence to Lilan Liu.

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He, B., Xue, H., Liu, L. et al. Rigid-flexible coupling virtual prototyping-based approach to the failure mode, effects, and criticality analysis. Int J Adv Manuf Technol 100, 1695–1717 (2019). https://doi.org/10.1007/s00170-018-2641-2

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  • DOI: https://doi.org/10.1007/s00170-018-2641-2

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