Skip to main content
SpringerLink
Log in

Role of multi-response principal component analysis in reliability-based robust design optimization: an application to commercial vehicle design

  • INDUSTRIAL APPLICATION
  • Published:
Structural and Multidisciplinary Optimization Aims and scope Submit manuscript

Abstract

The Taguchi method is a widely used conventional approach for robust design that combines experimental design with quality loss functions. However, this method can be only used in a single-response problem. In this study, we propose the use of principal component analysis (PCA) to consider multi-response problems in the Taguchi method and to investigate the influence factor of a cab suspension system. We compute the normalized quality loss for each response and perform PCA to calculate the multi-response performance index. In this study, control factors with three level combinations and noise factors with random sampling from each normal distribution are considered. Additionally, we applied multi-objective reliability based robust design optimization (RBRDO) to accommodate design uncertainties and its data scattering based on rational probabilistic approaches. This is used to develop the reliability assessment and reliability based design optimization and corresponds to an integrated method that accounts for the design robustness in the objective function and reliability in the constraints.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Antony J (2000) Multi-response optimization in industrial experiments using taguchi’s quality loss function and principal component analysis. Quality and Reliability Eng International 16:3–8

    Article  Google Scholar 

  • Arora JS, Elwakeil OA, Chahande AI, Hsieh CC (1995) Global optimization methods for engineering applications: a review. Structural Optimization 9:137–159

    Article  Google Scholar 

  • Beck AT, de Santana Gomes WJ (2012) A comparison of deterministic, reliability-based and risk-based structural optimization under uncertainty. Probabilistic Eng Mechanics 28:18–29

    Article  Google Scholar 

  • Choi K, Lee G, Choi DH (2009) Reliability-based design optimization using kriging Metamodel with sequential sampling technique. Trans Korean Soc Mech Eng A 33:1464–1470

    Article  Google Scholar 

  • Coello CAC, Pulido GT (2005) Multiobjective structural optimization using a microgenetic algorithm. Struct Multidisc Optim 30:388–403

    Article  Google Scholar 

  • Cole DJ (2001) Fundamental issues in suspension Design for Heavy Road Vehicles. Veh Syst Dyn 35:319–360

    Article  Google Scholar 

  • Der Kiureghian A, Lin HZ, Hwang SJ (1987) Second-order reliability approximations. J Engrg Mech, ASCE 113:1208–1225

    Article  Google Scholar 

  • Enevoldsen I, Sorensen JD (1994) Reliability-based optimization in structural engineering. Struct Saf 15:169–196

    Article  Google Scholar 

  • Gauri SK, Pal S (2014) The principal component analysis (PCA)-based approaches for multi-response optimization: some areas of concerns. Int J Adv Manuf Technol 70:1875–1887

    Article  Google Scholar 

  • Haftka RT, Scott EP, Cruz JR (1998) Optimization and experiments: a survey. Appl Mech Rev 51:435–448

    Article  Google Scholar 

  • Jean MD, Wang JT (2006) Using a principal components analysis for developing a robust Design of Electron Beam Welding. Int J Adv Manuf Technol 28:882–229

    Article  Google Scholar 

  • Jeong SB, Lee SJ, Park GJ (2012) Improvement of the convergence capability of a single loop single vector approach using conjugate gradient for a concave function. Trans Korean Soc Mech Eng A 36:805–811

    Article  Google Scholar 

  • Jollife L (2002) Principal component analysis. John Wiley and Sons, Ltd., New Jersey

    Google Scholar 

  • Kaiser HF (1960) The application of electronic computers to factor analysis. Educ Psychol Meas 20:141–151

    Article  Google Scholar 

  • Kim MS, Kim JR, Jeon JY, Choi DH (2001) Design optimization using two-diagonal quadratic approximation. Trans Korean Soc Mech Eng A 25:1423–1431

    Google Scholar 

  • Lee I, Choi KK, Du L, Gorsich D (2008a) Dimension reduction method for reliability-based robust design optimization. Comput Struct 86:1550–1562

    Article  MATH  Google Scholar 

  • Lee JS, Choi GJ, Lee KH (2008b) Ride performance evaluation of a heavy truck semi-active cabin air suspension system. Trans Korean Soc Automotive Eng 16:77–83

    Article  Google Scholar 

  • Lee I, Shin J, Choi KK (2013) Equivalent target probability of failure to convert high-reliability model to low-reliability model for efficiency of sampling-based RBDO. Struct Multidisc Optim 48:235–248

    Article  MathSciNet  Google Scholar 

  • Motta RS, Afonso SMB (2016) An efficient procedure for structural reliability-based robust design optimization. Struct and Multidisc Opt 54(3):511–530

    Article  MathSciNet  Google Scholar 

  • Phadke MS (1989) Quality engineering using robust design. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Sandgren E, Cameron TM (2002) Robust design optimization of structures through consideration of variation. Comput Struct 80:1605–1613

    Article  Google Scholar 

  • Shahrak AF, Noorossana R (2014) Reliability-based robust design optimization: a general methodology using genetic algorithm. Comput Ind Eng 74:199–207

    Article  Google Scholar 

  • Sim HM, Song CY, Lee J, Choi HY (2012) A preliminary study of reliability based robust optimization using conservative approximate meta-models. J of Ocean Eng and Technol 26:80–85

    Article  Google Scholar 

  • Song CY, Lee J (2010) Comparative study of approximate optimization techniques in CAE based structural design. Trans Korean Soc Mech Eng A 34:1603–1611

    Article  Google Scholar 

  • Su CT, Tong LI (1997) Multi-response robust design by principal component analysis. Total Qual Manag 8:409–416

    Article  Google Scholar 

  • Tu J, Choi KK, Park YH (1999) A new study on reliability-based design optimization. ASME J of Mech Design 121:557–564

    Article  Google Scholar 

  • Yang YS, Park CK, Lee KH, Suh JC (2007) A study on the preliminary ship design method using deterministic approach and probabilistic approach including hull form. Struct Multidisc Optim 33:529–539

    Article  Google Scholar 

  • Youn BD, Choi KK (2004) A new response surface methodology for reliability-based design optimization. Comput Struct 82:241–256

    Article  Google Scholar 

  • Youn BD, Xi Z (2009) Reliability-based robust design optimization using the eigenvector dimension reduction (EDR) method. Structural Optimization 37(5):475–492

    Article  Google Scholar 

  • Yu X, Choi KK, Chang KH (1997) A mixed design approach for probabilistic structural durability. Structural Optimization 14:81–90

    Article  Google Scholar 

Download references

Acknowledgements

This research is supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT & Future Planning (2017R1A2B4009606). This work is supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of Republic of Korea (20163030024420). This research is supported by NGV & Hyundai Motor Group (2016-11-0906).

Author information

Authors and Affiliations

  1. School of Mechanical Engineering, Yonsei University, Seoul, 03722, South Korea

    Juhee Lim & Jongsoo Lee

  2. Research & Development Division, Hyundai Motor Group, Gyeonggi, 18280, South Korea

    Yong Sok Jang, Hong Suk Chang & Jong Chan Park

Authors
  1. Juhee Lim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yong Sok Jang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hong Suk Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jong Chan Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jongsoo Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jongsoo Lee.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lim, J., Jang, Y.S., Chang, H.S. et al. Role of multi-response principal component analysis in reliability-based robust design optimization: an application to commercial vehicle design. Struct Multidisc Optim 58, 785–796 (2018). https://doi.org/10.1007/s00158-018-1908-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00158-018-1908-4

Keywords

Search

Navigation