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Research on Resource Consumption Standards for Highway Electromechanical Equipment Based on Monte Carlo Model

Author

Listed:
  • Linxuan Liu

    (School of Business, Xinjiang University, Urumqi 830017, China)

  • Wei Tian

    (Xinjiang Transportation Investment (Group) Co., Ltd., Urumqi 830001, China
    Engineering Technology and Transportation Industry in Arid Desert Areas, Urumqi 830001, China)

  • Xiaomin Dai

    (School of Transportation Engineering, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Green Construction and Maintenance of Transportation Infrastructure and Intelligent Traffic Control, Urumqi 830017, China)

  • Liang Song

    (School of Transportation Engineering, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Green Construction and Maintenance of Transportation Infrastructure and Intelligent Traffic Control, Urumqi 830017, China)

Abstract

The increasing complexity of highway electromechanical systems has created a critical need to improve the accuracy of resource consumption standards. Traditional deterministic methods often fail to capture inherent variability in resource usage, resulting in significant discrepancies between budget estimates and actual costs. To address this issue for a specific device, this study develops a probabilistic framework based on Monte Carlo simulation, using manual barrier gate installation as a case study. First, probability distribution models for key parameters were established by collecting and statistically analyzing field data. Next, Monte Carlo simulation generated 100,000 pseudo-observations, yielding mean labor consumption of 1.08 workdays (SD 0.29), expansion bolt usage of 6.02 sets (SD 0.97), and equipment shifts of 0.20 (SD 0.10). Comparison with the “Highway Engineering Budget Standards” (JTG/T 3832-2018) revealed deviations of 1% to 4%, and comparison with market bid prices showed errors below 2%. These results demonstrate that the proposed method accurately captures dynamic fluctuations in resource consumption, aligning with both national norms and actual tender data. In conclusion, the framework offers a robust and adaptable tool for cost estimation and resource allocation in highway electromechanical projects, enhancing budgeting accuracy and reducing the risk of cost overruns.

Suggested Citation

  • Linxuan Liu & Wei Tian & Xiaomin Dai & Liang Song, 2025. "Research on Resource Consumption Standards for Highway Electromechanical Equipment Based on Monte Carlo Model," Sustainability, MDPI, vol. 17(10), pages 1-21, May.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:10:p:4640-:d:1658808
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    References listed on IDEAS

    as
    1. Cao, Sheng & Xu, Haicheng & Xu, Yan & Wang, Xiaoshen & Zheng, Yingjie & Li, Yanling, 2023. "Assessment of the integrated benefits of highway infrastructure and analysis of the spatiotemporal variation: Evidence from 29 provinces in China," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    2. Antonello Ignazio Croce & Giuseppe Musolino & Corrado Rindone & Antonino Vitetta, 2021. "Traffic and Energy Consumption Modelling of Electric Vehicles: Parameter Updating from Floating and Probe Vehicle Data," Energies, MDPI, vol. 15(1), pages 1-20, December.
    3. Chonghui Guo & Menglin Lu & Wei Wei, 2021. "An Improved LDA Topic Modeling Method Based on Partition for Medium and Long Texts," Annals of Data Science, Springer, vol. 8(2), pages 331-344, June.
    Full references (including those not matched with items on IDEAS)

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