Skip to main content
Log in

A methodology for the implementation of automated measuring stations in flexible manufacturing systems

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

Abstract

This paper presents a methodology for the inclusion of an automated measuring station in an existing flexible manufacturing system (FMS) by treating the measuring station as a workstation integrated into the FMS. This approach causes minimal distortion of the FMS work functions and does not depend on the control algorithms implemented on the system. A case study based on an FMS located at the Aeronautical Centre is presented. The FMS used in the case study is called CFF-ETSIA. This system contains the main elements needed in a FMS: two computer numerical control machine tools for machining and two industrial robots for handling and manipulating. The measuring station in the case study is implemented with one of the robots used to perform the necessary actions of measurement and manipulation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Williamson T (1967) System 24. A new concept of manufacture Proc 8th Int Mach Tools Des & Res (MTDR) Conf. Pergamon Press, London, pp 327–376

    Google Scholar 

  2. Blomquist RE, Reynolds CR (1976) Pallet Shuttle System. White-Sundstrand Machine Tool Inc. US Patent 4278381, 14 Jul 1981

  3. Piplani R, Wetjens D (2007) Evaluation of entropy-based dispatching in flexible manufacturing systems. Eur J Op Res 176(1):317–331. doi:10.1016/j.ejor.2005.06.066

    Article  MATH  Google Scholar 

  4. Kumar A, Prakash TMK, Shankar R, Baveja A (2006) Solving machine-loading problem of a flexible manufacturing system with constraint-based genetic algorithm. Eur J Op Res 175(2):1043–1069. doi:10.1016/j.ejor.2005.06.025

    Article  MATH  Google Scholar 

  5. Zeballos LJ (2010) A constraint programming approach to tool allocation and production scheduling in flexible manufacturing systems. Rob Comp Integ Manuf 26(6):725–743. doi:10.1016/j.rcim.2010.04.005

    Article  Google Scholar 

  6. Youssef MA, Al-Ahmady B (2002) Quality management practices in a flexible manufacturing systems (FMS) environment. Tot Qual Manag 13(6):877–890. doi:10.1080/0954412022000010217

    Article  Google Scholar 

  7. Wang JW, Li JS, Arinez J, Biller S, Huang NJ (2010) Quality analysis in flexible manufacturing systems with batch productions: performance evaluation and nonmonotonic properties. IEEE Trans Aut Sci Eng 7(3):671–676. doi:10.1109/tase.2009.2029077

    Article  Google Scholar 

  8. Rezaie K, Ostadi B (2007) A mathematical model for optimal and phased implementation of Flexible Manufacturing Systems. App Math Comp 184:729–736

    Article  MathSciNet  MATH  Google Scholar 

  9. Rubio EM, Sanz A, Sebastián MA (2005) Virtual reality applications for the next generation manufacturing. Int J Comp Int Manuf 7:601–609

    Article  Google Scholar 

  10. Turgay S (2009) Agent-based FMS control. Rob Comp Int Manuf 25(2):470–480

    Article  Google Scholar 

  11. Chan FTS, Bhagwatz R, Wadhwa S (2008) Comparative performance analysis of a flexible manufacturing system (FMS):a review-period-based control. Int J Prod Res 46:1–24

    Article  MATH  Google Scholar 

  12. Piroddi L, Cossalter M, Ferrarini L (2009) A resource decoupling approach for deadlock prevention in FMS. Int J Adv Manuf Tech 40(1–2):157–170

    Article  Google Scholar 

  13. Caumond A, Lacomme P, Moukrim A, Tchernev N (2009) An MILP for scheduling problems in an FMS with one vehicle. Eur J Op Res 199(3):706–722

    Article  MATH  Google Scholar 

  14. Kusiak A (1986) Flexible manufacturing systems: Methods and studies ISBN‑13: 9780444879219. Elsevier Science Ltd, Amsterdam

    Google Scholar 

  15. Sanz A (1985) Simulation and optimization of flexible manufacturing systems Ph D Thesis. Dpt Tecnología Mecánica, ETSII-UPM, Madrid

    Google Scholar 

  16. Bhattacharya A, Abraham A, Vasant P, Grosan C (2007) Evolutionary artificial neural network for selecting flexible manufacturing systems under disparate level-of-satisfaction of decision maker. Int J Innov Comp Inf Con 3(1):131–140

    Google Scholar 

  17. Shiue YR, Su CT (2002) Attribute selection for neural network-based adaptive scheduling systems in flexible manufacturing systems. Int J Adv Manuf Tech 20(7):532–544

    Article  Google Scholar 

  18. Prakash A, Chan FTS, Deshrnukh SG (2011) FMS scheduling with knowledge based genetic algorithm approach. Exp Sys App 38(4):3161–3171. doi:10.1016/j.eswa.2010.09.002

    Article  Google Scholar 

  19. Yogeswaran M, Ponnambalam SG, Tiwari MK (2009) An efficient hybrid evolutionary heuristic using genetic algorithm and simulated annealing algorithm to solve machine loading problem in FMS. Int J Prod Res 47(19):5421–5448. doi:10.1080/00207540801910429

    Article  MATH  Google Scholar 

  20. Hsu T, Korbaa O, Dupas R, Goncalves G (2008) Cyclic scheduling for FMS: modelling and evolutionary solving approach. Eur J Op Res 191(2):463–483

    Google Scholar 

  21. Lu MS, Liu YJ (2011) Dynamic dispatching for a flexible manufacturing system based on fuzzy logic. Int J Adv Manuf Tech 54(9-12):1057–1065. doi:10.1007/s00170-010-2993-8

    Article  Google Scholar 

  22. Mehrabad MS, Anvari M (2010) Provident decision making by considering dynamic and fuzzy environment for FMS evaluation. Int J Prod Res 48(15):4555–4584

    Article  MATH  Google Scholar 

  23. Chen YF, Li ZW, Khalgui M, Mosbahi O (2011) Design of a maximally permissive liveness-enforcing petri net supervisor for flexible manufacturing systems. IEEE Trans Aut Sci Eng 8(2):374–393. doi:10.1109/tase.2010.2060332

    Article  Google Scholar 

  24. Li SY, Li ZW, Hu HS (2011) Siphon extraction for deadlock control in flexible manufacturing systems by using Petri nets. Int J Comp Integ Manuf 24(8):710–725. doi:10.1080/0951192x.2011.575182

    Article  Google Scholar 

  25. Yasuda G (2011) Model based design and implementation of hierarchical and distributed control for robotic flexible manufacturing cells using Petri nets. In: Chen R (ed) Mechatronics and intelligent materials, pts 1 and 2. Adv Mat Res 211–212: 856–860

  26. Prakash A, Tiwari MK, Shankar R (2008) Optimal job sequence determination and operation machine allocation in flexible manufacturing systems: an approach using adaptive hierarchical ant colony algorithm. J Intel Manuf 19(2):161–173. doi:10.1007/s10845-008-0071-y

    Article  Google Scholar 

  27. Udhayakumar P, Kumanan S (2010) Sequencing and scheduling of job and tool in a flexible manufacturing system using ant colony optimization algorithm. Int J Adv Manuf Tech 50(9-12):1075–1084. doi:10.1007/s00170-010-2583-9

    Article  Google Scholar 

  28. Sanz A, González I, García del Valle I, Tobaruela E (1994) La célula flexible de fabricación ETSIA-CFF. Anales de Ingeniería Mecánica 10(3):127–134

    Google Scholar 

  29. ACL. Automated control language. (1998) Rev. 1.43. Eshed Robotec. www.intelitek.com.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. Sanz.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sanz, A., González, I., Casado, J. et al. A methodology for the implementation of automated measuring stations in flexible manufacturing systems. Int J Adv Manuf Technol 66, 1065–1073 (2013). https://doi.org/10.1007/s00170-012-4389-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-012-4389-4

Keywords

Navigation