Optimum machine capabilities for reconfigurable manufacturing systems

  • Eram Asghar
  • Uzair Khaleeq uz Zaman
  • Aamer Ahmed Baqai
  • Lazhar Homri
ORIGINAL ARTICLE
  • 93 Downloads

Abstract

Reconfigurable manufacturing systems constitute a new manufacturing paradigm and are considered as the future of manufacturing because of their changeable and flexible nature. In a reconfigurable manufacturing environment, basic modules can be rearranged, interchanged, or modified, to adjust the production capacity according to production requirements. Reconfigurable machine tools have modular structure comprising of basic and auxiliary modules that aid in modifying the functionality of a manufacturing system. As the product’s design and its manufacturing capabilities are closely related, the manufacturing system is desired to be customizable to cater for all the design changes. Moreover, the performance of a manufacturing system lies in a set of planning and scheduling data incorporated with the machining capabilities keeping in view the market demands. This research work is based on the co-evolution of process planning and machine configurations in which optimal machine capabilities are generated through the application of multi-objective genetic algorithms. Furthermore, based on these capabilities, the system is tested for reconfiguration in case of production changeovers. Since, in a reconfigurable environment, the same machine can be used to perform different tasks depending on the required configuration, the subject research work assigns optimum number of machines by minimizing the machining capabilities to carry out different operations in order to streamline production responses. An algorithm has also been developed and verified on a part family. As a result of the proposed methodology, an optimized reconfigurable framework can be achieved to realize optimal production of a part family. Finally, the proposed methodology was applied on a case study and respective conclusions were drawn.

Keywords

Alternative process plans Multi-objective genetic algorithm Reconfigurable manufacturing systems Reconfigurable process plans 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Meghrabi MG, Ulsoy AG, Koren Y (2000) Reconfigurable manufacturing system: key to future manufacturing. J Intell Manuf 11:403–419CrossRefGoogle Scholar
  2. 2.
    Meghrabi MG, Ulsoy AG, Koren Y, Heytler P (2002) Trends and perspectives in flexible and reconfigurable manufacturing system. J Intell Manuf 13:135–146CrossRefGoogle Scholar
  3. 3.
    Rakesh K, Jain PK, Mehta NK (2010) A framework for simultaneous recognition of driving part families and operation groups for driving a reconfigurable system. Adv Prod Eng Manag 5:45–58Google Scholar
  4. 4.
    ElMaraghy HA (2006) Flexible and manufacturing system paradigms. Int J Flex Manuf Syst 17:261–276CrossRefMATHGoogle Scholar
  5. 5.
    Mulubika C (2013) Evaluation of control strategies for reconfigurable manufacturing systems. MScEng thesis, Stellenbosh University, South AfricaGoogle Scholar
  6. 6.
    Liraviasl KK (2015) A capacity planning simulation model for reconfigurable manufacturing systems. MASc thesis, University of Windsor, Ontario, CanadaGoogle Scholar
  7. 7.
    Wiendahl HP, ElMaraghy HA, Nyhuis P, Zah MF, Wiendahl HH, Duffie N, Brieke M (2007) Changeable manufacturing—classification, design and operation. CIRP Ann Manuf Technol 56(2):783–809.  https://doi.org/10.1016/j.cirp.2007.10.003 CrossRefGoogle Scholar
  8. 8.
    Tolio T, Ceglarek D, ElMaraghy HA, Fischer A, SJ H, Laperriere L, Newman ST (2010) SPECIES—co-evolution of products, processes and production systems. CIRP Ann Manuf Technol 59(2):672–693CrossRefGoogle Scholar
  9. 9.
    Wang GX, Huang SH, Yan Y, JJ D (2016) Reconfiguration schemes evaluation based on preference ranking of key characteristics of reconfigurable manufacturing systems. Int J Adv Manuf Technol 89:2231–2249CrossRefGoogle Scholar
  10. 10.
    Wang W, Koren Y (2012) Scalability planning for reconfigurable manufacturing system. J Manuf Syst 31(2):83–91.  https://doi.org/10.1016/j.jmsy.2011.11.001 CrossRefGoogle Scholar
  11. 11.
    Lateef-Ur-Rehman AUR (2012) Manufacturing configuration selection using multicriteria decision tool. Int J Adv Manuf Technol 65:625–639CrossRefGoogle Scholar
  12. 12.
    Azab A, ElMaraghy H, Nyhuis P, Pachow-Frauenhofer J, Schmidt M (2013) Mechanics of change: a framework to reconfigure manufacturing systems. CIRP J Manuf Sci Technol 6(2):110–119.  https://doi.org/10.1016/j.cirpj.2012.12.002 CrossRefGoogle Scholar
  13. 13.
    Zahid T (2013) Multi criteria optimization of process plans for reconfigurable manufacturing system: an evolutionary approach. International Mechanical Engineering Congress and Exposition, ISBN: 978-0-7918-5619-2Google Scholar
  14. 14.
    Prasad D, Jayswal SC (2017) Reconfigurability consideration and scheduling of products in a manufacturing industry. Int J Prod Res 1–20Google Scholar
  15. 15.
    Hees A, Reinhart G (2015) Approach for production planning in reconfigurable manufacturing systems. Procedia CIRP 33:70–75.  https://doi.org/10.1016/j.procir.2015.06.014 CrossRefGoogle Scholar
  16. 16.
    Zhao F, Murray VR, Ramani K, Sutherland JW (2012) Toward the development of process plans with reduced environmental impacts. Front Mech Eng 7(3):231–246.  https://doi.org/10.1007/s11465-012-0334-3 CrossRefGoogle Scholar
  17. 17.
    Azab A, ElMaraghy HA (2007) Mathematical modeling for reconfigurable process planning. CIRP Ann Manuf Technol 56(1):467–472CrossRefGoogle Scholar
  18. 18.
    ElMaraghy HA (2009) Changeable and reconfigurable manufacturing systems. Springer Series in Advanced Manufacturing, ISBN: 978-1-84882-067-8Google Scholar
  19. 19.
    Koren Y, Wang W, Gu X (2017) Value creation through design for scalability of reconfigurable manufacturing systems. Int J Prod Res 55(5):1227–1242.  https://doi.org/10.1080/00207543.2016.1145821 CrossRefGoogle Scholar
  20. 20.
    Koren Y (2006) General RMS characteristics, comparison with dedicated and flexible systems. Reconfigurable manufacturing systems and transformable factories. 3:27–45Google Scholar
  21. 21.
    Koren Y, Ulsoy AG (2002) Vision, principles and impact of reconfigurable manufacturing systems. Powertrain Int 5(3):14–21Google Scholar
  22. 22.
    Bryan A, Ko J, SJ H, Koren Y (2007) Co-evolution of product families and assembly systems. CIRP Ann 56(1):41–44.  https://doi.org/10.1016/j.cirp.2007.05.012 CrossRefGoogle Scholar
  23. 23.
    Wiendahl HP, ElMaraghy HA, Nyhuism P, Zah MF, Duffie N, Brieke M (2007) Changeable manufacturing—classification, design and operation. CIRP Ann 56(2):783–809.  https://doi.org/10.1016/j.cirp.2007.10.003 CrossRefGoogle Scholar
  24. 24.
    Renna P, Ambrico M (2011) Evaluation of cellular manufacturing configurations in dynamic conditions using simulation. Int J Adv Manuf Technol 56(9-12):1235–1251.  https://doi.org/10.1007/s00170-011-3255-0 CrossRefGoogle Scholar
  25. 25.
    Kashkoush M, ElMaraghy HA (2014) Product family formation for reconfigurable assembly systems. Procedia CIRP 17:302–307Google Scholar
  26. 26.
    Goyal KK, Jain P, Jain M (2013) A comprehensive approach to operation sequence similarity based part family formation in the reconfigurable manufacturing system. Int J Prod Res 51(6):1762–1776.  https://doi.org/10.1080/00207543.2012.701771 CrossRefGoogle Scholar
  27. 27.
    Rakesh K, Jain P, Mehta N (2010) A framework for simultaneous recognition of part families and operation groups for driving a reconfigurable manufacturing system. J Adv Prod Eng Manag 5:45–58Google Scholar
  28. 28.
    Azab A, ElMaraghy HA (2007) Sequential process planning: a hybrid optimal macro level approach. J Manuf Syst 26(3):147–160.  https://doi.org/10.1016/j.jmsy.2008.03.003 CrossRefGoogle Scholar
  29. 29.
    Shabaka AI, ElMaraghy HA (2008) A model for generating optimal process plan in RMS. Int J Comput Integr Manuf 21(2):180–194.  https://doi.org/10.1080/09511920701607741 CrossRefGoogle Scholar
  30. 30.
    Chaube A, Benyoucef L, Tiwari M (2012) An adapted NSGA-2 algorithm based dynamic process plan generation for a reconfigurable manufacturing system. J Intell Manuf 23(4):1141–1155.  https://doi.org/10.1007/s10845-010-0453-9 CrossRefGoogle Scholar
  31. 31.
    Youssef AM, ElMaraghy HA (2007) Optimal configuration selection for reconfigurable manufacturing systems. Int J Manuf Syst 19(2):67–106.  https://doi.org/10.1007/s10696-007-9020-x CrossRefMATHGoogle Scholar
  32. 32.
    Aboufazili N (2012) Reconfigurable machine tool and measuring reconfigurable for design evaluation. The Royal Institute of Technology, SwedenGoogle Scholar
  33. 33.
    Moon YM, Kota S (2002) Design of reconfigurable machine tools. J Manuf Sci Eng 124(2):480–483.  https://doi.org/10.1115/1.1452748 CrossRefGoogle Scholar
  34. 34.
    Shabaka AI, ElMaraghy HA (2007) Generation of machine configurations based on product features. Int J Comput Integr Manuf 20(4):355–369.  https://doi.org/10.1080/09511920600740627 CrossRefGoogle Scholar
  35. 35.
    Bryan A, Ko J, SJ H, Koren Y (2007) Co-evolution of product families and assembly systems. CIRP Ann Manuf Technol 56(1):41–44CrossRefGoogle Scholar
  36. 36.
    Kumar C, Deb S (2012) Generation of optimal sequence of machining operations in set up planning by genetic algorithms. J Adv Manuf Syst 11(1):67–80.  https://doi.org/10.1142/S0219686712500059 CrossRefGoogle Scholar
  37. 37.
    Goyal KK, Jain PK, Jain M (2012) Optimal configuration selection for reconfigurable manufacturing system using NSGA II and TOPOSIS. Int J Prod Res 50(15):4175–4191.  https://doi.org/10.1080/00207543.2011.599345 CrossRefGoogle Scholar
  38. 38.
    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.  https://doi.org/10.1016/j.cie.2012.09.008 CrossRefGoogle Scholar
  39. 39.
    Baqai A (2010) Co-conception des processus d‟usinage et des configurations cinematiques d‟un systeme de production reconfigurable. (Doctoral dissertation, Arts et Metiers Paris Tech), France, NNT: 2010-ENAM- 0010Google Scholar
  40. 40.
    Mohapatra P, Benyoucef L, Tiwari MK (2013) Integration of process planning and scheduling through adaptive setup planning: a multi-objective approach. Int J Prod Res 51(23–24):7190–7208.  https://doi.org/10.1080/00207543.2013.853890 CrossRefGoogle Scholar
  41. 41.
    Mohapatra P, Nayak A, Kumar SK, Tiwari MK (2015) Multi-objective process planning and scheduling using controlled elitist non-dominated sorting genetic algorithm. Int J Prod Res 53(6):1712–1735.  https://doi.org/10.1080/00207543.2014.957872 CrossRefGoogle Scholar
  42. 42.
    Bensmaine A, Dahane M, Benyoucef L (2014) A new heuristic for integrated process planning and scheduling in reconfigurable manufacturing system. Int J Prod Res 52(12):3583–3594.  https://doi.org/10.1080/00207543.2013.878056 CrossRefGoogle Scholar
  43. 43.
    Azab A, Naderi B (2015) Modelling the problem of production scheduling for reconfigurable manufacturing systems. CIRP Conf Intell Comput Manuf Eng 33:76–80Google Scholar
  44. 44.
    Benderbal HH, Dahane M, Benyoucef L (2017) Flexibility-based multi-objective approach for machines selection in reconfigurable manufacturing system (RMS) design under unavailability constraints. Int J Prod Res 55(20):6033–6051.  https://doi.org/10.1080/00207543.2017.1321802 CrossRefGoogle Scholar
  45. 45.
    Benderbal HH, Dahane M & Lyes Benyoucef (2017) Modularity assessment in reconfigurable manufacturing system (RMS) design: an archived multi-objective simulated annealing-based approach. Int J Adv Manuf Technol 1–21Google Scholar
  46. 46.
    Xie N, Li A, Xue W (2012) Cooperative optimization of reconfigurable machine tool configurations and production process plan. Chin J Mech Eng 25(5):982–989.  https://doi.org/10.3901/CJME.2012.05.982 CrossRefGoogle Scholar
  47. 47.
    Gyulai D, Kadar B, Monosotori L (2015) Robust production planning and capacity control for flexible assembly lines. IFAC Papers Online 48(3):2312–2317.  https://doi.org/10.1016/j.ifacol.2015.06.432 CrossRefGoogle Scholar
  48. 48.
    Zhang R, Ong SK, Nee AY (2015) A simulation-based genetic algorithm approach for remanufacturing process planning and scheduling. Appl Soft Comput 37:521–532.  https://doi.org/10.1016/j.asoc.2015.08.051 CrossRefGoogle Scholar
  49. 49.
    Hees A, Reinhart G (2015) Approach for production planning in reconfigurable manufacturing systems. 9th CIRP conference on intelligent Computing 33: 70–75Google Scholar
  50. 50.
    ElMaraghy HA, Moussa M, ElMaraghy W, Abbas M (2017) Integrated product/system design and planning for new product family in a changeable learning factory. Proceedings of 7th International Conference on Learning Factories 65-72Google Scholar
  51. 51.
    Navaei J, ElMaraghy HA (2017) Optimal operations sequence retrieval from master operations sequence for part/product families. Int J Prod Res 1-24.  https://doi.org/10.1080/00207543.2017.1391417
  52. 52.
    Hassan F, Jain PK, Kumar D (2013) Optimum configuration selection in reconfigurable manufacturing system involving multiple part families. Opsearch 51(2):297–311CrossRefGoogle Scholar
  53. 53.
    Hassan SM, Baqai A (2013) An approach for the selection of process plans based on part family changes. Adv Sustain Compet Manuf Syst 65–77Google Scholar
  54. 54.
    Abbas M, ElMaraghy H (2017) Synthesis and optimization of manufacturing systems configuration using co-platforming. CIRP J Manuf Sci Technol (in press)Google Scholar
  55. 55.
    Goyal KK, Jain PK, Jain M (2013) A novel methodology to measure the responsiveness of RMTs in reconfigurable manufacturing system. J Manuf Syst 32(4):724–730.  https://doi.org/10.1016/j.jmsy.2013.05.002 CrossRefGoogle Scholar
  56. 56.
    Venter G (2010) Review of optimization techniques. Encycl Aerospace Eng.  https://doi.org/10.1002/9780470686652.eae495
  57. 57.
    Sastry K, Goldberg D, Kendall G (2014) Genetic algorithms. In:Burke E, Kendall G. (eds) Search Methodologies. Springer, Boston MAGoogle Scholar
  58. 58.
    Asghar E, Baqai AA, Zaman UKU (2015) Performance of NSGA-II and WGA in macro level process planning considering reconfigurable manufacturing system. Proceedings of 25th International Conference on Flexible Automation and Intelligent Manufacturing 2: 320-327Google Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  • Eram Asghar
    • 1
  • Uzair Khaleeq uz Zaman
    • 2
  • Aamer Ahmed Baqai
    • 3
  • Lazhar Homri
    • 2
  1. 1.Ghulam Ishaq Khan Institute of Engineering Sciences and TechnologyTopiPakistan
  2. 2.Laboratoire de Conception Fabrication Commande, École nationale supérieure d’arts et métiersMetzFrance
  3. 3.National University of Sciences and TechnologyIslamabadPakistan

Personalised recommendations