Skip to main content
SpringerLink
Log in

The online quality control methods for the assembling of remanufactured engines’ cylinder block and cover under uncertainty

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

The assembling of cylinder block and cover is one of the keys for the quality controlling of remanufactured engines. First, we analyze the critical factors which influence the assembly quality and study the uncertainty connotation of the flatness and roughness of cylinder block and cover, as well as bolts. Then, an uncertainty quantitative measure model for each factor has been structured, and according to that, we proposed a back propagation (BP) neural network-based quality control method which can achieve self-learning, updating, and online dynamic quality controlling. It can reduce the negative effects caused by the uncertainty and improve the assembly accuracy. Finally, the quality data of remanufactured engine in 2012 proves that the method can improve the qualification rate of 0.63 % and reduce the cost of after-sales claims by 35.2 %; the living examples verify its feasibility and validity.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Bin-shi XU (2005) Remanufacturing engineering and its application [M]. Harbin Institute of Technology, Harbin

    Google Scholar 

  2. Liu M, Liu C, Xing L, et al. Study on a tolerance grading allocation method under uncertainty and quality oriented for remanufactured parts [J]. The International Journal of Advanced Manufacturing Technology, 2013: 1–8.

  3. Qiang Q, Ke K, Anderson T et al (2012) The closed-loop supply chain network with competition, distribution channel investment, and uncertainties [J]. Omega 41(2):186–194

    Article  Google Scholar 

  4. Amin SH, Zhang G (2013) A three-stage model for closed-loop supply chain configuration under uncertainty [J]. Int J Prod Res 51(5):1405–1425

    Article  Google Scholar 

  5. Inderfurth K (2005) Impact of uncertainties on recovery behavior in a remanufacturing environment: a numerical analysis [J]. Int J Phys Distrib Logist Manag 35(5):318–336

    Article  Google Scholar 

  6. Savaskan RC, Bhattacharya S, Van Wassenhove LN (2004) Closed-loop supply chain models with product remanufacturing [J]. Manag Sci 50(2):239–252

    MATH  Google Scholar 

  7. Ferrer G, Swaminathan JM (2006) Managing new and remanufactured products [J]. Manag Sci 52(1):15–26

    Google Scholar 

  8. Geyer R, Van Wassenhove LN, Atasu A (2007) The economics of remanufacturing under limited component durability and finite product life cycles [J]. Manag Sci 53(1):88–100

    MATH  Google Scholar 

  9. Atasu A, Sarvary M, Van Wassenhove LN (2008) Remanufacturing as a marketing strategy [J]. Manag Sci 54(10):1731–1746

    Google Scholar 

  10. Behdad S, Thurston D. Disassembly and reassembly sequence planning tradeoffs under uncertainty for product maintenance [J]. Journal of mechanical design, 2012, 134(4).

  11. Reveliotis SA (2007) Uncertainty management in optimal disassembly planning through learning-based strategies [J]. IIE Trans 39(6):645–658

    Article  Google Scholar 

  12. Kenné JP, Dejax P, Gharbi A (2012) Production planning of a hybrid manufacturing–remanufacturing system under uncertainty within a closed-loop supply chain [J]. Int J Prod Econ 135(1):81–93

    Article  Google Scholar 

  13. Su C, Sha Y (2010) Remanufacturing production planning based on mixed-uncertainty and evidence theory [J]. J Southeast Univ (Nat Sci Ed) 4(40):712–716

    Google Scholar 

  14. Srivastava R (1997) Buffering from material recovery uncertainty in a recoverable manufacturing environment [J]. J Oper Res Soc 48(5):519–529

    Article  MATH  Google Scholar 

  15. Gong X, Chao X (2013) Technical note—optimal control policy for capacitated inventory systems with remanufacturing [J]. Oper Res 61(3):603–611

    Article  MATH  MathSciNet  Google Scholar 

  16. Zhou SX, Yu Y (2011) Technical note—optimal product acquisition, pricing, and inventory management for systems with remanufacturing [J]. Oper Res 59(2):514–521

    Article  MATH  MathSciNet  Google Scholar 

  17. DeCroix GA (2006) Optimal policy for a multiechelon inventory system with remanufacturing [J]. Oper Res 54(3):532–543

    Article  MATH  MathSciNet  Google Scholar 

  18. Ferguson M, Guide VD, Koca E et al (2009) The value of quality grading in remanufacturing [J]. Prod Oper Manag 18(3):300–314

  19. Xifeng T, Haijun M, Xuhong L (2011) Effect of quality uncertainty of parts on performance of reprocessing system in remanufacturing environment. J Southeast Univ (Engl Ed) 1:92–95

    Google Scholar 

  20. Xiangyu C, Gongqian L, Ma S (2007) Continuous quality improvement for remanufacturing products based on PMLC [J]. China Mech Eng 18(2):170–174

    Google Scholar 

  21. Zhou J, Huang P, Zhu Y, Deng J (2012) A quality evaluation model of reuse parts and its management system development for end-of-life wheel loaders. J Clean Prod 35:239–249

    Article  Google Scholar 

  22. Jin X, Hu SJ, Ni J et al (2013) Assembly strategies for remanufacturing systems with variable quality returns [J]. IEEE Trans Autom Sci Eng 1:76–85

    Article  Google Scholar 

  23. Ilgin MA, Gupta SM (2010) Environmentally conscious manufacturing and product recovery (ECMPRO): a review of the state of the art [J]. J Environ Manag 91(3):563–591

    Article  Google Scholar 

  24. Subramoniam R, Huisingh D, Chinnam RB (2009) Remanufacturing for the automotive aftermarket-strategic factors: literature review and future research needs [J]. J Clean Prod 17(13):1163–1174

    Article  Google Scholar 

  25. Lee SW, Lee DG (2007) Torque transmission capability of composite–metal interference fit joints [J]. Compos Struct 78(4):584–595

    Article  Google Scholar 

  26. Marshall MB, Lewis R, Dwyer-Joyce RS (2006) Characterisation of contact pressure distribution in bolted joints [J]. Strain 42(1):31–43

    Article  Google Scholar 

  27. Chen C, Yang G, Chang D et al (2012) Assembly connection design orienting to sealing performance of joint surface [J]. J Xi’an Jiaotong Univ 46(3):75–83

    MathSciNet  Google Scholar 

  28. Osma A (2013) An investigation on the stress–strain relationship of cold-rolled steel sheets used in the automotive industry, the institution of mechanical engineers. Part D: J Automob Eng. doi:10.1177/0954407013479905, published online before print, December 5

    Google Scholar 

  29. Chaouachi A, Kamel RM, Nagasaka K (2010) A novel multi-model neuro-fuzzy-based MPPT for three-phase grid-connected photovoltaic system [J]. Sol Energy 84(12):2219–2229

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Hefei University of Technology, 230009, Hefei, China

    Maogen Ge, Conghu Liu & Mingzhou Liu

Authors
  1. Maogen Ge
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Conghu Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mingzhou Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Conghu Liu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ge, M., Liu, C. & Liu, M. The online quality control methods for the assembling of remanufactured engines’ cylinder block and cover under uncertainty. Int J Adv Manuf Technol 74, 225–233 (2014). https://doi.org/10.1007/s00170-014-5971-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-014-5971-8

Keywords

Search

Navigation