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A hybrid approach based on critical chain for project buffer consumption prediction and monitoring

Jiaojiao Xu, Sijun Bai

Kybernetes

ISSN: 0368-492X

Article publication date: 10 December 2024

19

Abstract

Purpose

The critical chain project buffer monitor process addresses uncertainty and variability in project duration. However, classical buffer monitor methods only consider buffer consumption, while the dynamic allocation of buffer zones and the buffer consumption trend of activities are ignored. This paper presents the innovative framework for dynamic monitoring of project buffer which covers the dynamic buffer allocation, predictive analytics of buffer utilization and a new monitoring technique based on control chart graph.

Design/methodology/approach

First, a dynamically buffer allocation model is framed, and buffer zones are given to the activities considering risks. Then, a predictive model amalgamating Bayesian Optimization, Convolutional Neural Networks, and Long Short-Term Memory networks (BO-CNN-LSTM) is framed. Finally, a new buffer monitor framework is constructed that takes into account historical information about buffer usage and utilizes two thresholds derived from control chart theory.

Findings

This approach is empirically tested on a representative agricultural website project in China. The results show that, first, the dynamic buffer allocation makes better use of the project buffer, reduces buffer waste and increases the possibility of timely completion of the project. Second, the BO-CNN-LSTM model predicts better than Long Short-Term Memory (LSTM) and Grey Neural Network Model (GNNM), providing project managers with new management insights and perspectives. Third, the novel monitoring procedure makes the leveraging of historical data possible in the control of the schedule deviations, allowing for more timely interventions in the course of the implementation of the project.

Originality/value

A new project buffer monitoring method suitable for uncertain project environments is proposed.

Keywords

Acknowledgements

The authors are grateful to three anonymous referees for their helpful comments and suggestions, which have led to much improvement of the paper. In addition, we would like to thank Dr Zhao for her valuable contributions to this research.

Citation

Xu, J. and Bai, S. (2024), "A hybrid approach based on critical chain for project buffer consumption prediction and monitoring", Kybernetes, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/K-02-2024-0340

Publisher

:

Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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