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Smart mining policy: Integrating fuzzy-VIKOR technique and the Z-number concept to implement industry 4.0 strategies in mining engineering

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  • Poormirzaee, Rashed
  • Hosseini, Shahab
  • Taghizadeh, Rahim

Abstract

New technologies have significant effects on increasing efficiency and improving the productivity of industries, especially the mining industry. Nevertheless, selecting and applying new technologies is a multi-criteria decision-making issue. As mines constitute an important part of a country's economy with a considerable impact on socio-economic development, mining smartening should be carried out to increase efficiency. This research proposes a novel framework for assessing and prioritizing smart mining strategies by integrating the Z-number theory and fuzzy-VIKOR technique. Eight copies of a questionnaire containing five strategies (alternatives) and 11 criteria were presented to an eight-member team of experts. The strategies comprised “A1 provision of government incentives to mines to use up-to-date technologies”, “A2 development of mining cooperation with research centers and R&D to develop new technologies required by mines”, “A3 investment of mine owners in providing the required infrastructure”, “A4 development of green mining and safe operations”, and “A5 training and improving active human resources”. Moreover, the criteria consisted of “C1 employment”, “C2 energy consumption”, “C3 hazards”, “C4 trained human resources”, “C5 marketing and sales”, “C6 environment”, “C7 risk”, “C8 culture”, “C9 technology”, “C10 quality of mineral products”, and “C11 legislations”. Furthermore, a parametric sensitivity analysis was performed to determine the effectiveness and robustness of the five suggested strategies. The results of the proposed hybrid model confirm that the third strategy (A3) is the most appropriate alternative for implementing Industry 4.0 technologies in the large-scale mines of Iran. The results revealed that the presented approach provided a stationary ranking mechanism for smart mining engineering strategies and that the weight of the maximum group utility measure did not substantially affect ranking strategies. An expert group confirmed the obtained results and the evaluation and validation made of the influential factors and conditions of the study area.

Suggested Citation

  • Poormirzaee, Rashed & Hosseini, Shahab & Taghizadeh, Rahim, 2022. "Smart mining policy: Integrating fuzzy-VIKOR technique and the Z-number concept to implement industry 4.0 strategies in mining engineering," Resources Policy, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:jrpoli:v:77:y:2022:i:c:s0301420722002161
    DOI: 10.1016/j.resourpol.2022.102768
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    References listed on IDEAS

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    1. Jiskani, Izhar Mithal & Yasli, Fatma & Hosseini, Shahab & Rehman, Atta Ur & Uddin, Salah, 2022. "Improved Z-number based fuzzy fault tree approach to analyze health and safety risks in surface mines," Resources Policy, Elsevier, vol. 76(C).
    2. Jiskani, Izhar Mithal & Cai, Qingxiang & Zhou, Wei & Ali Shah, Syed Ahsan, 2021. "Green and climate-smart mining: A framework to analyze open-pit mines for cleaner mineral production," Resources Policy, Elsevier, vol. 71(C).
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    Cited by:

    1. Jin, Haifeng, 2023. "Analyzing factors and resource policymaking options for sustainable resource management and carbon neutrality in mining industry: Empirical study in China," Resources Policy, Elsevier, vol. 86(PB).
    2. Hosseini, Shahab & Lawal, Abiodun Ismail & Kwon, Sangki, 2023. "A causality-weighted approach for prioritizing mining 4.0 strategies integrating reliability-based fuzzy cognitive map and hybrid decision-making methods: A case study of Nigerian Mining Sector," Resources Policy, Elsevier, vol. 82(C).
    3. Zhang, Yan & Wang, Yu-Hao & Zhao, Xu & Tong, Rui-Peng, 2023. "Dynamic probabilistic risk assessment of emergency response for intelligent coal mining face system, case study: Gas overrun scenario," Resources Policy, Elsevier, vol. 85(PB).

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