Skip to main content

Advertisement

SpringerLink
Log in

Concurrent multi-objective tolerance allocation of mechanical assemblies considering alternative manufacturing process selection

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

Abstract

Concurrent design of tolerances by considering both the manufacturing cost and quality loss of each component by alternate processes of the assemblies may ensure the manufacturability, reduce the manufacturing costs, decrease the number of fraction nonconforming (or defective rate), and shorten the production lead time. Most of the current tolerance design research does not consider the quality loss. In this paper, a novel multi-objective optimization method is proposed to enhance the operations of the non-traditional algorithms (Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO)) and systematically distribute the tolerances among various the components of mechanical assemblies. The problem has a multi-criterion character in which three objective functions, one constraint, and three variables are considered. The average fitness factor method and normalized weighted objective function method are used to select the best optimal solution from Pareto-optimal fronts. Two multi-objective performance measures namely solution spread measure and ratio of non-dominated individuals are used to evaluate the strength of Pareto-optimal fronts. Two more multi-objective performance measures namely optimizer overhead and algorithm effort are used to find the computational effort of NSGA-II and MOPSO algorithms. The Pareto-optimal fronts and results obtained from various techniques are compared and analysed. Both NSGA-II and MOPSO algorithms are best for this problem.

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. Ye B, Salustri FA (2003) Simultaneous tolerance synthesis for manufacturing and quality. Res Eng Des 14(2):98–106

    Google Scholar 

  2. Singh PK, Jain SC, Jain PK (2003) Tolerance allocation with alternative manufacturing processes-suitability of genetic algorithm. Proceeding Inst Mech Eng J Eng Manufacture 2(1–2):22–34

    Google Scholar 

  3. Singh PK, Jain SC, Jain PK (2004) A GA based solution to optimum tolerance synthesis of mechanical assemblies with alternate manufacturing processes: focus on complex tolerancing problems. Int J Prod Res 42(24):5185–5215

    Article  MATH  Google Scholar 

  4. Prabhaharan G, Asokan P, Ramesh P, Rajendran S (2004) Genetic algorithm-based optimal tolerance allocation using least-cost model. Int J Adv Manuf Technol 24:647–660

    Article  Google Scholar 

  5. Prabhaharan G, Asokan P, Rajendran S (2005) Sensitivity-based conceptual design and tolerance allocation using the continuous ants colony algorithm (CACO). Int J Adv Manuf Technol 25:516–526

    Article  Google Scholar 

  6. Krishna G, Mallikarjuna Rao K (2006) Simultaneous optimal selection of design and manufacturing tolerances with different stack-up conditions using scatter search. Int J Adv Manuf Technol 30(3–4):328–333. doi:10.1007/s00170-005-0059-0

    Article  Google Scholar 

  7. Huang YM, Shiau C-S (2006) Optimal tolerance allocation for a sliding vane compressor. J Mech Des 128(1):98–107

    Article  Google Scholar 

  8. Huang MF, Zhong YR (2007) Optimized sequential design of two-dimensional tolerances. Int J Adv Manuf Technol 33:579–593

    Article  Google Scholar 

  9. Singh PK, Jain PK, Jain SC (2008) Optimal tolerance design of mechanical assemblies for economical manufacturing in the presence of alternative machines—a genetic algorithm-based hybrid methodology. Proceeding Inst Mech Eng J Eng Manufacture 222B:591–604

    Article  Google Scholar 

  10. Sivakumar M, Kannan SM, Jayabalan V (2009) A new algorithm for optimum tolerance allocation of complex assemblies with alternative processes selection. Int J Adv Manuf Technol 40(7–8):819–836

    Google Scholar 

  11. González I, Sánchez I (2009) Statistical tolerance synthesis with correlated variables. Mech Mach Theory 44(6):1097–1107

    Article  MATH  Google Scholar 

  12. Huang M, Zhong Y (2008) Dimensional and geometrical tolerance balancing in concurrent design. Int J Adv Manuf Technol 35(7–8):723–735. doi:10.1007/s00170-006-0749-2

    Article  Google Scholar 

  13. Forouraghi B (2009) Optimal tolerance allocation using a multiobjective particle swarm optimizer. Int J Adv Manuf Technol 44:710–724

    Article  Google Scholar 

  14. Siva Kumar M, Stalin B (2009) Optimum tolerance synthesis for complex assembly with alternative process selection using Lagrange multiplier method. Int J Adv Manuf Technol 44:405–411

    Article  Google Scholar 

  15. Wu F, Dantan J-Y, Etienne A, Siadat A, Martin P (2009) Improved algorithm for tolerance allocation based on Monte Carlo simulation and discrete optimization. Comput Ind Eng 56(4):1402–1413

    Article  Google Scholar 

  16. Muthu P, Dhanalakshmi V, Sankaranarayanasamy K (2009) Optimal tolerance design of assembly for minimum quality loss and manufacturing cost using metaheuristic algorithms. Int J Adv Manuf Technol 44:1154–1164

    Article  Google Scholar 

  17. Noorul Haq A, Sivakumar K, Saravanan R, Muthiah V (2005) Tolerance design optimization of machine elements using genetic algorithm. Int J Adv Manuf Technol 25:385–391

    Article  Google Scholar 

  18. Singh PK, Jain PK, Jain SC (2003) Simultaneous optimal selection of design and manufacturing tolerances with different stack-up conditions using genetic algorithms. Int J Prod Res 41(11):2411–2429

    Article  MATH  Google Scholar 

  19. Singh PK, Jain SC, Jain PK (2005) Advanced optimal tolerance design of mechanical assemblies considering interrelated dimension chains and process precision limits. Comput Ind 56(2):179–194

    Article  MathSciNet  Google Scholar 

  20. Singh PK, Jain SC, Jain PK (2005) Comparative study of genetic algorithm and simulated annealing for optimal tolerance design formulated with discrete and continuous variables. Proceeding Inst Mech Eng J Eng Manufacture 219B:735–759

    Article  Google Scholar 

  21. Coello Coello C, Lamont GB, Van Veldhuizen DA (2007) Evolutionary algorithms for solving multi-objective problems, 2nd edn. Springer, New York

    MATH  Google Scholar 

  22. Deb K (2001) Multi-objective optimization using evolutionary algorithms. Wiley, Chichester

    MATH  Google Scholar 

  23. Knowles J, Corne D, Deb K (eds) (2008) Multiobjective problem solving from nature: from concepts to applications. Springer, New York

    MATH  Google Scholar 

  24. Salazar D, Rocoo CM (2007) Solving advanced multi-objective robust designs by means of multiple objective evolutionary algorithms (MOEA): a reliability application. Reliab Eng Syst Saf 92:697–706. doi:10.1016/j.ress.2006.03.003

    Article  Google Scholar 

  25. Singh PK, Jain SC, Jain PK (2004) A genetic algorithm based solution to optimum tolerance synthesis of mechanical assemblies with alternate manufacturing processes—benchmarking with the exhaustive search method using the Lagrange multiplier. Proceeding Inst Mech Eng J Eng Manufacture 218 B:765–778

    Google Scholar 

  26. Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197

    Article  Google Scholar 

  27. Price K, Storn R (1997) Differential evolution—a simple evolution strategy for fast optimization. DrDobb’s Journal 22(4):18–24 & 78

    MathSciNet  Google Scholar 

  28. Tan KC, Lee TH, Khor EF (2002) Evolutionary algorithms for multi-objective optimization: performance assessments and computations. Artif Intell Rev 17:253–290

    Article  Google Scholar 

  29. Singh PK, Jain SC, Jain PK (2006) Concurrent optimal adjustment of nominal dimensions and selection of tolerances considering alternative machines. Comput Aided Des 38:1074–1087

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Bannari Amman Institute of Technology, Sathyamangalam, 638 401, Erode District, Tamil Nadu, India

    K. Sivakumar

  2. Department of Mechanical Engineering, M.A.M. College of Engineering, Tiruchirappalli, 621105, Tamil Nadu, India

    C. Balamurugan

  3. Department of Mechanical Engineering, EGS Pillay Engineering College, Nagapattinam, 611002, Tamil Nadu, India

    S. Ramabalan

Authors
  1. K. Sivakumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. C. Balamurugan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. Ramabalan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to C. Balamurugan.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sivakumar, K., Balamurugan, C. & Ramabalan, S. Concurrent multi-objective tolerance allocation of mechanical assemblies considering alternative manufacturing process selection. Int J Adv Manuf Technol 53, 711–732 (2011). https://doi.org/10.1007/s00170-010-2871-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-010-2871-4

Keywords

Search

Navigation