Skip to main content

Advertisement

SpringerLink
Log in

Sustainable reconfigurable manufacturing system design using adapted multi-objective evolutionary-based approaches

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

Abstract

Nowadays, manufacturing systems should be cost-effective and environmentally harmless to cope with various challenges in today’s competitive markets. This paper aims to solve an environmental-oriented multi-objective reconfigurable manufacturing system design (i.e., sustainable reconfigurable machines and tools selection) in the case of a single-unit process plan generation. A non-linear multi-objective integer program (NL-MOIP) is presented first, where four objectives are minimized respectively, the total production cost, the total production time, the amount of the greenhouse gases emitted by machines, and the hazardous liquid wastes. Second, to solve the problem, we propose four adapted versions of evolutionary approaches, namely two versions of the well-known non-dominated sorting genetic algorithm (NSGA-II and NSGA-III), weighted genetic algorithms (WGA), and random weighted genetic algorithms (RWGA). To show the efficiency of the four approaches, several instances of the problem are experimented, and the obtained results are analyzed using three metrics respectively hypervolume, spacing metric, and cardinality of the mixed Pareto fronts. Moreover, the influences of the probabilities of genetic operators (crossover and mutation) on the convergence of the adapted NSGA-III are analyzed. Finally, the TOPSIS method is used to help the decision-maker ranking and select the best process plans.

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

Similar content being viewed by others

References

  1. Koren Y, Heisel U, Jovane F, Moriwaki T, Pritschow G, Ulsoy G, Van Brussel H (1999) Reconfigurable manufacturing systems. CIRP Ann 48(2):527–540

    Article  Google Scholar 

  2. Koren Y, Shpitalni M (2010) Design of reconfigurable manufacturing systems. J Manuf Syst 29(4):130–141

    Article  Google Scholar 

  3. Koren Y (2020) The emergence of reconfigurable manufacturing systems (rmss). In: Benyoucef L (ed) Reconfigurable Manufacturing Systems: From Design to Implementation. ISBN: 978-3-030-28782-5. Springer International Publishing, pp 1–9

  4. Koren Y (2010) The global manufacturing revolution: product-process-business integration and reconfigurable systems, vol 80. Wiley & Sons

  5. Koren Y (2006) General rms characteristics. comparison with dedicated and flexible systems. In: Reconfigurable manufacturing systems and transformable factories. Springer, pp 27–45

  6. Howard MC (2014) Sustainable manufacturing initiative (smi): a true public-private dialogue. The US Department of Commerce

  7. Battaïa O, Benyoucef L, Delorme X, Dolgui A, Thevenin S (2020) Sustainable and energy efficient reconfigurable manufacturing systems. In: Benyoucef L (ed) Reconfigurable Manufacturing Systems: From Design to Implementation. ISBN: 978-3-030-28782-5. Springer International Publishing, pp 179–191

  8. Touzout F A, Benyoucef L (2019) Multi-objective sustainable process plan generation in a reconfigurable manufacturing environment: exact and adapted evolutionary approaches. Int J Prod Res 57(8):2531–2547

    Article  Google Scholar 

  9. Benyoucef L (2020) Reconfigurable manufacturing systems: From design to implementation. ISBN: 978-3-030-28782-5

  10. Koren Y, Gu X, Guo W (2018) Reconfigurable manufacturing systems: Principles, design, and future trends. Front Mech Eng 13(2):121–136

    Article  Google Scholar 

  11. Maganha I, Silva C, Ferreira LMDF (2018) Understanding reconfigurability of manufacturing systems: An empirical analysis. J Manuf Syst 48:120–130

    Article  Google Scholar 

  12. Mehrabi M G, Ulsoy A G, Koren Y (2000) Reconfigurable manufacturing systems: Key to future manufacturing. J Intell Manuf 11(4):403–419

    Article  Google Scholar 

  13. ElMaraghy H A (2007) Reconfigurable process plans for responsive manufacturing systems. In: Digital enterprise technology. Springer, pp 35–44

  14. Goyal K K, Jain PK, Jain M (2012) Optimal configuration selection for reconfigurable manufacturing system using nsga ii and topsis. Int J Prod Res 50(15):4175–4191

    Article  Google Scholar 

  15. Swamidass P M (2000) Encyclopedia of production and manufacturing management. Springer Science & Business Media

  16. Musharavati F, Hamouda ASM (2012) Enhanced simulated-annealing-based algorithms and their applications to process planning in reconfigurable manufacturing systems. Adv Eng Softw 45(1):80–90

    Article  Google Scholar 

  17. Chaube A, Benyoucef L, Tiwari M K (2012) An adapted nsga-2 algorithm based dynamic process plan generation for a reconfigurable manufacturing system. J Intell Manuf 23(4):1141–1155

    Article  Google Scholar 

  18. Bensmaine A, Dahane M, Benyoucef L (2013) A non-dominated sorting genetic algorithm based approach for optimal machines selection in reconfigurable manufacturing environment. Comput Ind Eng 66 (3):519–524

    Article  Google Scholar 

  19. Hasan F, Jain PK (2015) Genetic modelling for selecting optimal machine configurations in reconfigurable manufacturing system. In: Applied Mechanics and Materials, vol 789. Trans Tech Publ, pp 1229–1239

  20. Haddou-Benderbal H, Dahane M, Benyoucef L (2016) Hybrid heuristic to minimize machine’s unavailability impact on reconfigurable manufacturing system using reconfigurable process plan. IFAC-PapersOnLine 49(12):1626–1631

    Article  Google Scholar 

  21. Wang G X, Huang S H, Yan Y, Du J J (2017) Reconfiguration schemes evaluation based on preference ranking of key characteristics of reconfigurable manufacturing systems. Int J Adv Manuf Technol 89 (5):2231–2249

    Article  Google Scholar 

  22. Haddou-Benderbal H, Dahane M, Benyoucef L (2018) Modularity assessment in reconfigurable manufacturing system (rms) design: an archived multi-objective simulated annealing-based approach. Int J Adv Manuf Technol 94(1):729–749

    Article  Google Scholar 

  23. Haddou-Benderbal H, Benyoucef L (2019) Machine layout design problem under product family evolution in reconfigurable manufacturing environment: a two-phase-based amosa approach. Int J Adv Manuf Technol 104(1):375–389

    Article  Google Scholar 

  24. Wang Y, Zhang G, Han L (2019) A methodology of setting module groups for the design of reconfigurable machine tools. Int J Adv Manuf Technol 104(5):2133–2147

    Article  Google Scholar 

  25. Touzout F A, Benyoucef L (2019) Multi-objective multi-unit process plan generation in a reconfigurable manufacturing environment: a comparative study of three hybrid metaheuristics. Int J Prod Res 57 (24):7520–7535

    Article  Google Scholar 

  26. Battaïa O, Dolgui A, Guschinsky N (2020) Optimal cost design of flow lines with reconfigurable machines for batch production. Int J Prod Res 58(10):2937–2952

    Article  Google Scholar 

  27. Allwood JM, Laursen S E, Russell SN, de Rodriguez C M, Bocken NMP (2008) An approach to scenario analysis of the sustainability of an industrial sector applied to clothing and textiles in the uk. J Cleaner Prod 16(12):1234–1246

    Article  Google Scholar 

  28. Machado C G, Winroth M P, Ribeiro da Silva E H D (2020) Sustainable manufacturing in industry 4.0: an emerging research agenda. Int J Prod Res 58(5):1462–1484

    Article  Google Scholar 

  29. Jayal AD, Badurdeen F, Dillon Jr OW, Jawahir IS (2010) Sustainable manufacturing: Modeling and optimization challenges at the product, process and system levels. CIRP J Manuf Sci Technol 2 (3):144–152

  30. Küster T, Lützenberger M, Freund D, Albayrak S (2013) Distributed evolutionary optimisation for electricity price responsive manufacturing using multi-agent system technology. Int J Adv Intell Syst 7

  31. Moon J-Y, Shin K, Park J (2013) Optimization of production scheduling with time-dependent and machine-dependent electricity cost for industrial energy efficiency. Int J Adv Manuf Technol 68 (1-4):523–535

    Article  Google Scholar 

  32. Choi Y-C, Xirouchakis P (2015) A holistic production planning approach in a reconfigurable manufacturing system with energy consumption and environmental effects. Int J Comput Integr Manuf 28(4):379–394

    Article  Google Scholar 

  33. Afrin K, Iquebal A S, Kumar S K, Tiwari MK, Benyoucef L, Dolgui A (2016) Towards green automated production line with rotary transfer and turrets: a multi-objective approach using a binary scatter tabu search procedure. Int J Comput Integr Manuf 29(7):768–785

    Article  Google Scholar 

  34. Huang A, Badurdeen F (2017) Sustainable manufacturing performance evaluation: Integrating product and process metrics for systems level assessment. Procedia Manuf 8:563–570

    Article  Google Scholar 

  35. Stoycheva S, Marchese D, Paul C, Padoan S, Juhmani A-s, Linkov I (2018) Multi-criteria decision analysis framework for sustainable manufacturing in automotive industry. J Clean Prod 187:257– 272

    Article  Google Scholar 

  36. Zhu Z, Chu F, Dolgui A, Chu C, Zhou W, Piramuthu S (2018) Recent advances and opportunities in sustainable food supply chain: a model-oriented review. Int J Prod Res 56(17):5700–5722

    Article  Google Scholar 

  37. Zhang J, Khalgui M, Boussahel W M, Frey G, Hon C, Wu N, Li Z (2015) Modeling and verification of reconfigurable and energy-efficient manufacturing systems. Discret Dyn Nat Soc 2015

  38. Ghanei S, AlGeddawy T (2016) A new model for sustainable changeability and production planning. Procedia CIRP 57:522–526

    Article  Google Scholar 

  39. Massimi E, Khezri A, Haddou Benderbal H, Benyoucef L (2020) A heuristic-based non-linear mixed integer approach for optimizing modularity and integrability in a sustainable reconfigurable manufacturing environment. Int J Adv Manuf Technol 108:1997–2020

    Article  Google Scholar 

  40. Murata T, Ishibuchi H, Tanaka H (1996) Multi-objective genetic algorithm and its applications to flowshop scheduling. Comput Ind Eng 30(4):957–968

    Article  Google Scholar 

  41. Konak A, Coit D W, Smith A E (2006) Multi-objective optimization using genetic algorithms: A tutorial. Reliab Eng Syst Safety 91(9):992–1007

    Article  Google Scholar 

  42. Deb K, Pratap A, Agarwal S, Meyarivan TAMT (2002) A fast and elitist multiobjective genetic algorithm: Nsga-ii. IEEE Trans Evol Comput 6(2):182–197

    Article  Google Scholar 

  43. Deb K, Jain H (2014) An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part i: solving problems with box constraints. IEEE Trans Evol Comput 18(4):577–601

    Article  Google Scholar 

  44. Hwang C-L, Lai Y-J, Liu T-Y (1993) A new approach for multiple objective decision making. Comput Oper Res 20(8):889– 899

    Article  Google Scholar 

  45. Huband S, Hingston P, While L, Barone L (2003) An evolution strategy with probabilistic mutation for multi-objective optimisation. In: The 2003 Congress on Evolutionary Computation, 2003. CEC’03., vol 4. IEEE, pp 2284–2291

  46. Koffi B, Cerutti A K, Duerr M, Iancu A, Kona A, Janssens-Maenhout G (2017) Covenant of mayors for climate and energy: Default emission factors for local emission inventories. Joint Research Centre (JRC)

Download references

Funding

Not applicable

Author information

Authors and Affiliations

  1. DGRSDT, LaROMaD Laboratory, USTHB University, Algiers, Algeria

    Imen Khettabi & Mohamed Amine Boutiche

  2. Aix Marseille University, University of Touloun, CNRS, LIS, Marseille, France

    Lyes Benyoucef

Authors
  1. Imen Khettabi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lyes Benyoucef
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mohamed Amine Boutiche
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lyes Benyoucef.

Ethics declarations

Ethics approval

The submitted work is original and has never been published elsewhere in any form or language.

Consent to participate

Not applicable

Consent to publish

Not applicable

Competing Interests

Not applicable

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Author contribution

All the authors have involved equally in the realized work.

1. Miss Khettabi: paper writing, problem formulation, approaches proposal and experimental performing and analysis

2. Prof. Benyoucef: paper writing, problem formulation, approaches proposal and experimental performing and analysis

3. Prof. Boutiche: paper writing, problem formulation, approaches proposal and experimental performing and analysis.

Availability of data and materials

The used data and materials are available when requested.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khettabi, I., Benyoucef, L. & Boutiche, M.A. Sustainable reconfigurable manufacturing system design using adapted multi-objective evolutionary-based approaches. Int J Adv Manuf Technol 115, 3741–3759 (2021). https://doi.org/10.1007/s00170-021-07337-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-021-07337-3

Keywords

Search

Navigation