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Multi-objective design and tolerance allocation for single- and multi-level systems

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Abstract

In this work we develop a method to perform simultaneous design and tolerance allocation for engineering problems with multiple objectives. Most studies in existing literature focus on either optimal design with constant tolerances or the optimal tolerance allocation for a given design setup. Simultaneously performing both design and tolerance allocation with multiple objectives for hierarchical systems increases problem dimensions and raises additional computational challenges. A design framework is proposed to obtain optimal design alternatives and to rank their performances when variations are present. An optimality influence range is developed to aid design alternatives selections with an influence signal-to-noise ratio that indicates the accordance of objective variations to the Pareto set and an influence area that quantifies the variations of a design . An additional tolerance design scheme is implemented to ensure that design alternatives meet the target tolerance regions. The proposed method is also extended to decomposed multi-level systems by integrating traditional sensitivity analysis for uncertainty propagation with analytical target cascading. This work enables decision-makers to select their best design alternatives on the Pareto set using three measures with different purposes. Examples demonstrate the effectiveness of the method on both single- and multi-level systems.

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References

  • Allison, J., Kokkolaras, M., Zawislak, M., & Papalambros, P. (2005). On the use of analytical target cascading and collaborative optimization for complex system design. In Proceedings of the 6th world congress on structural and multidisciplinary optimization.

  • ASME Standards Committee Y14. (2004). Mathematical definition of dimensioning and tolerancing principles. Engineering Drawing and Related Documentation Practices, ASME 14.5.1M.

  • ASME Standards Committee Y14. (2009). Dimensioning and tolerance. Engineering Drawing and Related Documentation Practices, ASME Y14.5.

  • Berrichi A., Amodeo L., Yalaoui F., Chtelet E., Mezghiche M. (2009) Bi-objective optimization algorithms for joint production and maintenance scheduling: Application to the parallel machine problem. Journal of Intelligent Manufacturing 20: 389–400

    Article  Google Scholar 

  • Caleb Li M. (2004) Optimal target selection for unbalanced tolerance design. International Journal of Advanced Manufacturing Technology 23: 743–749

    Article  Google Scholar 

  • Chen T.-C., Fischer G. (2000) A GA-based search method for the tolerance allocation problem. Artificial Intelligence in Engineering 14(2): 133–141

    Article  Google Scholar 

  • Cheng B., Maghsoodloo S. (1995) Optimization of mechanical assembly tolerances by incorporating taguchi’s quality loss function. Journal of Manufacturing Systems 14(4): 264– 276

    Article  Google Scholar 

  • Cheng F., Ye F., Yang J. (2009) Multi-objective optimization of collaborative manufacturing chain with time-sequence constraints. International Journal of Advanced Manufacturing Technology 40(9–10): 1024–1032

    Article  Google Scholar 

  • Choi H., Park M., Salisbury E. (2000) Optimal tolerance allocation with loss function. Journal of Manufacturing Science and Engineering 122(3): 529–535

    Article  Google Scholar 

  • Early R., Thompson J. (1989) Variation simulation modeling—variation analysis using monte carlo simulation. ASME Publication No. DE 16: 139–144

    Google Scholar 

  • Fletcher R. (2001) Practical methods of optimization. Wiley, New York

    Google Scholar 

  • Fowlkes W., Creveling C. (1995) Engineering methods for robust product design. Addison-Wesley, Reading, MA

    Google Scholar 

  • Giassi A., Bennis F., Maisonneuve J.-J. (2004) Multidisciplinary design optimisation and robust design approaches applied to concurrent design. Structural and Multidisciplinary Optimization 28(5): 356–371

    Article  Google Scholar 

  • Hanss M. (2004) Applied fuzzy arithmetic: An introduction with engineering applications. Springer, The Netherlands

    Google Scholar 

  • Jeang A. (2007) Combined parameter and tolerance design optimization with quality and cost. International Journal of Production Research 39(5): 923–952

    Article  Google Scholar 

  • Jordaan J., Ungerer C. (2002) Optimization of design tolerances through response surface approximations. Journal of Manufacturing Science and Engineering 124(3): 762–767

    Article  Google Scholar 

  • Kim H., Michelena N., Papalambros P., Jiang T. (2003) Target cascading in optimal system design. Journal of Mechanical Design 125(3): 474–480

    Article  Google Scholar 

  • Li M., Azarm S. (2008) Multiobjective collaborative robust optimization with interval uncertainty and interdisciplinary uncertainty propagation. Journal of Mechanical Design 130(8): 081402

    Article  Google Scholar 

  • Li D., Haimes Y. (1987) Hierarchical generating method for large-scale multiobjective systems. Journal of Optimization Theory and Applications 54(2): 303–333

    Article  Google Scholar 

  • Li M., Williams N., Azarm S. (2009) Interval uncertainty reduction and single-disciplinary sensitivity analysis with multi-objective optimization. Journal of Mechanical Design 131: 031007

    Article  Google Scholar 

  • Li M., Hamel J., Azarm S. (2010) Optimal uncertainty reduction for multi-disciplinary multi-output systems using sensitivity analysis. Structural and Multidisciplinary Optimization 40(1–6): 77–96

    Article  Google Scholar 

  • Lin E., Zhang J. (2001) Theoretical tolerance stackup analysis based on tolerance zone analysis. International Journal of Advanced Manufacturing Technology 17: 257–262

    Article  Google Scholar 

  • Martosell S., Sanchez A., Carlos S. (2007) A tolerance interval based approach to address uncertainty for rams+c optimization. Reliability Engineering and System Safety 92: 408–422

    Article  Google Scholar 

  • McAllister C., Simpson T. (2003) Multidisciplinary robust design optimization of an internal combustion engine. Journal of Mechanical Design 125: 124–130

    Article  Google Scholar 

  • Michalek J., Papalambros P. (2005) An efficient weighting update method to achieve acceptable consistency deviation in analytical target cascading. Journal of Mechanical Design 127(2): 206–214

    Article  Google Scholar 

  • Michelena N., Park H., Papalambros P. (2003) Convergence properties of analytical target cascading. AIAA Journal 41(5): 897–905

    Article  Google Scholar 

  • Neufville R. (1990) Applied system analysis. McGraw-Hill, New York, NY

    Google Scholar 

  • Papalambros P., Wilde D. (2000) Principles of optimal design (2nd ed.). Cambridge University Press, New York

    Book  Google Scholar 

  • Parkinson D. (2000) The application of a robust design method to tolerancing. Journal of Mechanical Design 122: 149–154

    Article  Google Scholar 

  • Savage G., Tong D., Carr S. (2006) Optimal mean and tolerance allocation using conformance-based design. Quality and Reliability Engineering International 22(4): 445–472

    Article  Google Scholar 

  • Skowronski V., Turner J. (1997) Using Monte-Carlo variance reduction in statistical tolerance synthesis. Computer-Aided Design 29(1): 63–69

    Article  Google Scholar 

  • Sobieszczanski-Sobieski J. (1990) Sensitivity of complex, internally coupled systems. AIAA Journal 28(1): 153–160

    Article  Google Scholar 

  • Subramaniam V., Senthil Kumar A., Seow K. C. (2001) A multi-agent approach to fixture design. Journal of Intelligent Manufacturing 12: 31–42

    Article  Google Scholar 

  • Taguchi G., Elsayed E., Hsiang T. (1989) Quality engineering in production systems. McGraw-Hill, New York

    Google Scholar 

  • Tappeta R., Renaud J. (1997) Multiobjective collaborative optimization. Journal of Mechanical Design 119: 403–411

    Article  Google Scholar 

  • Turkcan A., Selim Akturk M. (2003) A problem space genetic algorithm in multiobjective optimization. Journal of Intelligent Manufacturing 14: 363–378

    Article  Google Scholar 

  • Utyuzhnikov S., Maginot J., Guenov M. (2008) Local pareto approximation for multi-objective optimization. Engineering Optimization 40(9): 821–847

    Article  Google Scholar 

  • Vasseur H., Kurfess T., Cagan J. (1997) Use of a quality loss function to select statistical tolerances. Journal of Manufacturing Science and Engineering 119: 410–416

    Article  Google Scholar 

  • Wu W., Rao S. (2004) Interval approach for the modeling of tolerance and clearances in mechanism analysis. Journal of Mechanical Design 126: 581–592

    Article  Google Scholar 

  • Xu L., Cheng G., Yi P. (2005) Tolerance synthesis by a new method for system reliability-based optimization. Engineering Optimization 37(7): 717–732

    Article  Google Scholar 

  • Xue J., Ji P. (2004) Process tolerance allocation in angular tolerance charting. International Journal of Production Research 42(18): 3929–3945

    Article  Google Scholar 

  • Ye B., Salustri F. (2003) Simultaneous tolerance synthesis for manufacturing and quality. Research in Engineering Design 14: 98–106

    Google Scholar 

  • Yeo S. H., Ngoi B. K. A., Chen H. (1998) Process sequence optimization based on a new costtolerance model. Journal of Intelligent Manufacturing 9: 29–37

    Article  Google Scholar 

  • Zhou Z., Huang W., Zhang L. (2001) Sequential algorithm based on number theoretic method for statistical tolerance analysis and synthesis. Journal of Manufacturing Science and Engineering 123(3): 490–493

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Mechanical Engineering, National Cheng Kung University, Tainan, Taiwan

    Tzu-Chieh Hung & Kuei-Yuan Chan

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  1. Tzu-Chieh Hung
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  2. Kuei-Yuan Chan
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Correspondence to Kuei-Yuan Chan.

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Hung, TC., Chan, KY. Multi-objective design and tolerance allocation for single- and multi-level systems. J Intell Manuf 24, 559–573 (2013). https://doi.org/10.1007/s10845-011-0608-3

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  • DOI: https://doi.org/10.1007/s10845-011-0608-3

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