IDEAS home Printed from https://ideas.repec.org/a/ids/injams/v4y2012i1p91-106.html
   My bibliography  Save this article

Design of experiments for the analysis of the effects of pallet arrival patterns and maintenance policies on FMC productivity

Author

Listed:
  • Fawaz Abdulmalek
  • Mehmet Savsar
  • Majid M. Aldaihani

Abstract

This paper analyses the effects of various maintenance policies and part arrival patterns on the performance of a flexible manufacturing cell (FMC). A simulation analysis coupled with design of experiments is utilised in the study. In particular, the design of experiments includes maintenance policy as a factor with five levels and part release patterns as a factor with six levels. Effects of all the combinations of factors on the productivity of a typical FMC system are analysed using a simulation modelling approach. The results show that both factors have significant effects on manufacturing cell productivity and equipment utilisations. Releasing the pallets with longest processing time first into the cell and introducing preventive maintenance (PM) combined with corrective maintenance (CM) resulted in highest cell productivity. When a CM was started, it was found that the next scheduled PM should be combined with the CM if the time left to the next scheduled PM was 20% or less than the actual scheduled time.

Suggested Citation

  • Fawaz Abdulmalek & Mehmet Savsar & Majid M. Aldaihani, 2012. "Design of experiments for the analysis of the effects of pallet arrival patterns and maintenance policies on FMC productivity," International Journal of Applied Management Science, Inderscience Enterprises Ltd, vol. 4(1), pages 91-106.
  • Handle: RePEc:ids:injams:v:4:y:2012:i:1:p:91-106
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=44873
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Komonen, Kari, 2002. "A cost model of industrial maintenance for profitability analysis and benchmarking," International Journal of Production Economics, Elsevier, vol. 79(1), pages 15-31, September.
    2. Waeyenbergh, Geert & Pintelon, Liliane, 2004. "Maintenance concept development: A case study," International Journal of Production Economics, Elsevier, vol. 89(3), pages 395-405, June.
    3. Savsar, Mehmet & Aldaihani, Majid, 2008. "Modeling of machine failures in a flexible manufacturing cell with two machines served by a robot," Reliability Engineering and System Safety, Elsevier, vol. 93(10), pages 1551-1562.
    4. Savsar, Mehmet, 2006. "Effects of maintenance policies on the productivity of flexible manufacturing cells," Omega, Elsevier, vol. 34(3), pages 274-282, June.
    5. Cho, Danny I. & Parlar, Mahmut, 1991. "A survey of maintenance models for multi-unit systems," European Journal of Operational Research, Elsevier, vol. 51(1), pages 1-23, March.
    6. Majid M. Aldaihani & Mehmet Savsar, 2008. "Stochastic models for reliable and unreliable flexible manufacturing cells with two machines and two robots," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 3(5), pages 610-624.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Savsar, Mehmet, 2006. "Effects of maintenance policies on the productivity of flexible manufacturing cells," Omega, Elsevier, vol. 34(3), pages 274-282, June.
    2. Muchiri, Peter & Pintelon, Liliane & Gelders, Ludo & Martin, Harry, 2011. "Development of maintenance function performance measurement framework and indicators," International Journal of Production Economics, Elsevier, vol. 131(1), pages 295-302, May.
    3. Pinciroli, Luca & Baraldi, Piero & Zio, Enrico, 2023. "Maintenance optimization in industry 4.0," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    4. Crespo Marquez, Adolfo & Gupta, Jatinder N.D., 2006. "Contemporary maintenance management: process, framework and supporting pillars," Omega, Elsevier, vol. 34(3), pages 313-326, June.
    5. Xiang, Yisha, 2013. "Joint optimization of X¯ control chart and preventive maintenance policies: A discrete-time Markov chain approach," European Journal of Operational Research, Elsevier, vol. 229(2), pages 382-390.
    6. Seyed Habib A. Rahmati & Abbas Ahmadi & Kannan Govindan, 2018. "A novel integrated condition-based maintenance and stochastic flexible job shop scheduling problem: simulation-based optimization approach," Annals of Operations Research, Springer, vol. 269(1), pages 583-621, October.
    7. Zhu, Mixin & Zhou, Xiaojun, 2023. "Hybrid opportunistic maintenance policy for serial-parallel multi-station manufacturing systems with spare part overlap," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    8. Fleischmann, Moritz & Bloemhof-Ruwaard, Jacqueline M. & Dekker, Rommert & van der Laan, Erwin & van Nunen, Jo A. E. E. & Van Wassenhove, Luk N., 1997. "Quantitative models for reverse logistics: A review," European Journal of Operational Research, Elsevier, vol. 103(1), pages 1-17, November.
    9. Braglia, Marcello & Carmignani, Gionata & Frosolini, Marco & Zammori, Francesco, 2012. "Data classification and MTBF prediction with a multivariate analysis approach," Reliability Engineering and System Safety, Elsevier, vol. 97(1), pages 27-35.
    10. Hoskins, R. P. & Brint, A. T. & Strbac, G., 1999. "A structured approach to Asset Management within the electricity industry," Utilities Policy, Elsevier, vol. 7(4), pages 221-232, February.
    11. Haque, Lani & Armstrong, Michael J., 2007. "A survey of the machine interference problem," European Journal of Operational Research, Elsevier, vol. 179(2), pages 469-482, June.
    12. Vanneste, S. G. & Van Wassenhove, L. N., 1995. "An integrated and structured approach to improve maintenance," European Journal of Operational Research, Elsevier, vol. 82(2), pages 241-257, April.
    13. Min-Tsai Lai, 2007. "Periodical Replacement Model for a Multi-Unit System Subject to Failure Rate Interaction," Quality & Quantity: International Journal of Methodology, Springer, vol. 41(3), pages 401-411, June.
    14. Liu, Xinbao & Yang, Tianji & Pei, Jun & Liao, Haitao & Pohl, Edward A., 2019. "Replacement and inventory control for a multi-customer product service system with decreasing replacement costs," European Journal of Operational Research, Elsevier, vol. 273(2), pages 561-574.
    15. Faccio, M. & Persona, A. & Sgarbossa, F. & Zanin, G., 2014. "Industrial maintenance policy development: A quantitative framework," International Journal of Production Economics, Elsevier, vol. 147(PA), pages 85-93.
    16. Dilaver, Halit Metehan & Akçay, Alp & van Houtum, Geert-Jan, 2023. "Integrated planning of asset-use and dry-docking for a fleet of maritime assets," International Journal of Production Economics, Elsevier, vol. 256(C).
    17. Briš, Radim & Byczanski, Petr & Goňo, Radomír & Rusek, Stanislav, 2017. "Discrete maintenance optimization of complex multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 80-89.
    18. Rajesh Kumar Singh & Ayush Gupta, 2020. "Framework for sustainable maintenance system: ISM–fuzzy MICMAC and TOPSIS approach," Annals of Operations Research, Springer, vol. 290(1), pages 643-676, July.
    19. Ludvík Friebel & Jana Friebelová, 2012. "Stochastic analysis of maintenance process costs in the IT industry: a case study," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(3), pages 393-408, September.
    20. Jyrki Savolainen & Michele Urbani, 2021. "Maintenance optimization for a multi-unit system with digital twin simulation," Journal of Intelligent Manufacturing, Springer, vol. 32(7), pages 1953-1973, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ids:injams:v:4:y:2012:i:1:p:91-106. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=286 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.