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Determination of critical chain project buffer based on information flow interactions

Author

Listed:
  • Junguang Zhang

    (University of Science and Technology Beijing)

  • Xiwei Song

    (University of Science and Technology Beijing)

  • Hongyu Chen

    (California State University Long Beach)

  • Ruixia (Sandy) Shi

    (University of San Diego)

Abstract

It has been well accepted in the literature that co-dependency between project activity durations is caused by resource tightness and network complexity. However, we show that information flow interaction between activities is the key factor for it. Based on whether there exist spliced relationships between activities, we introduce the concept of rework safety time. We propose a method to compute the rework safety time using the information output and input time factors, rework probability matrix, and rework impact matrix. We achieve the optimization of the critical chain sequencing via the design structure matrix so that the dependency between activities is reduced. The project buffer is then determined by the tail concentration method based on the optimized chain. The empirical results show that, as opposed to the traditional RSEM method, our approach improves the project buffer consumption rate, shortens project duration, reduces project cost, and increases project on-time completion rate.

Suggested Citation

  • Junguang Zhang & Xiwei Song & Hongyu Chen & Ruixia (Sandy) Shi, 2016. "Determination of critical chain project buffer based on information flow interactions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(9), pages 1146-1157, September.
    • Handle: RePEc:pal:jorsoc:v:67:y:2016:i:9:d:10.1057_jors.2016.9
    DOI: 10.1057/jors.2016.9
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    References listed on IDEAS

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    1. Trietsch, Dan & Mazmanyan, Lilit & Gevorgyan, Lilit & Baker, Kenneth R., 2012. "Modeling activity times by the Parkinson distribution with a lognormal core: Theory and validation," European Journal of Operational Research, Elsevier, vol. 216(2), pages 386-396.
    2. Tukel, Oya I. & Rom, Walter O. & Eksioglu, Sandra Duni, 2006. "An investigation of buffer sizing techniques in critical chain scheduling," European Journal of Operational Research, Elsevier, vol. 172(2), pages 401-416, July.
    3. Eppinger, Steven D. & Browning, Tyson R., 2012. "Design Structure Matrix Methods and Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262017520, April.
    4. V González & L F Alarcón & T W Yiu, 2013. "Integrated methodology to design and manage work-in-process buffers in repetitive building projects," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(8), pages 1182-1193, August.
    5. Rabbani, M. & Fatemi Ghomi, S.M.T. & Jolai, F. & Lahiji, N.S., 2007. "A new heuristic for resource-constrained project scheduling in stochastic networks using critical chain concept," European Journal of Operational Research, Elsevier, vol. 176(2), pages 794-808, January.
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    Cited by:

    1. Junguang Zhang & Dan Wan, 2021. "Determination of early warning time window for bottleneck resource buffer," Annals of Operations Research, Springer, vol. 300(1), pages 289-305, May.
    2. She, Bingling & Chen, Bo & Hall, Nicholas G., 2021. "Buffer sizing in critical chain project management by network decomposition," Omega, Elsevier, vol. 102(C).

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