An Underground Mine Risk Identification Model and Safety Management Method Based on Explanation Graph-Probabilistic Multi-Plan Analysis (EG-PMPA)

Gao, Rugao; Zhou, Keping; Yang, Chun; Zhu, Ke

doi:10.1109/access.2020.3045339

Cited by 2 publications

(2 citation statements)

References 40 publications

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“…In the context of underground mining safety management, a study proposed a framework model that uses process node management and probabilistic multi-plan analysis to analyze and rank key risk factors. This model can assist in implementing risk factor management control plans (16). Another study introduced a mine safety management system that includes a safety monitoring subsystem, a health monitoring subsystem, a potential accident analysis subsystem, and a potential accident prediction subsystem.…”

Section: Planningmentioning

confidence: 99%

Implementation of safety management system in nickel mining: A case of PT Putra Perkasa Abadi Job Site MLP in 2023

Agus Amirudin,

Ikhsan Hidayanto,

Faham Burhanudin

et al. 2024

World J. Adv. Res. Rev.

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Background: The audit of the Mineral and Coal Mining Safety Management System aims to obtain an overview of the level of implementation of the mineral and coal mining management system, assess the capacity of the mining system to ensure compliance with the legislative requirements, evaluate the effectiveness of mining systems in meeting the set targets and identify the potential application of the MSMS to be enhanced at the P.T. Putra Perkasa Eternal Site of PT Makmur Lestari Primatama from the period January 1, 2023 until December 2023. The purpose of this study was to find out the implementation of the safety management system in nickel mining of PT. Putra Perkasa Abadi Job Site MLP in 2023. Method: This type of research is quantitative descriptive. The research conducted in December 2023. Compliance measurements are carried out on 7 elements consisting of Policy, Planning, Organization and Personnel, Implementation, Monitoring, Evaluation and Follow-up Action, Documentation, and Management Review and Performance Improvement. Data collection methods are carried out with interviews, observations, and document explanations. Results: The policy element achieved 74% compliance from the maximum achievable value. Although the maximum value has not been reached, it still shows a good level of compliance. The planning element achieves 59% compliance from the maximum achievable value. Further evaluation is needed to understand the factors that lead to this achievement. Organizational and staff elements reach 51% compliance from the maximum value. Implementation elements reach 38% compliance. There is great potential for improvement in the implementation of this element. The monitoring, evaluation, and follow-up elements reached 46% compliance. More effort is needed to improve performance in this regard. Despite low maximum values, documentation elements reach 58% compliance, indicating a good focus on document management but still requiring optimization. Management review elements and performance improvements reached 46% compliance. This aspect can be a focus of improvement to improve overall performance. Overall, the management system achieved 49% compliance from the maximum value. Conclusion: In general, PT Putra Perkasa Abadi Job Site MLP has procedures and mechanisms that support the creation of a mining safety system. However, improvements are needed that can be directed to elements with lower compliance scores. It requires optimization of each element consisting of Policy, Planning, Organization and Personnel, Implementation, Monitoring, Evaluation and Follow-up, Documentation, as well as management review and performance improvement. Data collection methods were carried out using interviews, observation and document review.

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Section: Planningmentioning

confidence: 99%

Implementation of safety management system in nickel mining: A case of PT Putra Perkasa Abadi Job Site MLP in 2023

Agus Amirudin,

Ikhsan Hidayanto,

Faham Burhanudin

et al. 2024

World J. Adv. Res. Rev.

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“…As a valuable asset accumulated by mines in the process of dealing with actual safety risks, the use of intelligent analysis tools to fully explore the information of the laws implied in safety production data and realize the in-depth utilization of safety data assets has become an effective means to strengthen the pertinence and scientificity of safety management and control. Current research on the in-depth utilization of safety production data mainly focuses on safety status assessment and prediction [8][9][10][11][12][13][14], safety risk identification and analysis [15][16][17][18], and safety risk pre-control [19][20][21]. Wu et al [22] established a mine safety supervision capability evaluation index system consisting of a target layer, a criterion layer, and a sub-criterion layer, and identified effective measures that could improve the efficiency of safety supervision by determining the weights of each index and combining the accident causation 2-4 model.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Safety Risk Analysis and Decision-Making System for Underground Metal Mines Based on Big Data

Qiang

Hou

et al. 2023

Sustainability

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In view of the new situation faced by safety risk management in underground metal mines, based on a comprehensive analysis of the current situation of mine safety management business and system construction requirements, the main functional modules, overall architecture, and data interaction mode of the intelligent safety risk analysis and decision-making system were analyzed and designed. On the basis of elaborating the implementation process of the main functional modules of the system, such as multi-source safety information collection and governance, and safety risk intelligence analysis and visualization, a safety risk intelligence analysis and decision-making system was constructed, which provided efficient and real-time intelligent application and analysis services for safety in the production of underground metal mines and realized the whole process information management of collection, aggregation, processing, analysis, and visual display of multi-source mine safety risk information. The application of the system has made an essential change in the mode of mine safety risk management, realizing the active safety management goal of shifting safety risk management from post-analysis to pre-prevention, helping to improve the pertinence and efficiency of safety risk management, and greatly reducing the risk of mine safety accidents.

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An Underground Mine Risk Identification Model and Safety Management Method Based on Explanation Graph-Probabilistic Multi-Plan Analysis (EG-PMPA)

Cited by 2 publications

References 40 publications

Implementation of safety management system in nickel mining: A case of PT Putra Perkasa Abadi Job Site MLP in 2023

Implementation of safety management system in nickel mining: A case of PT Putra Perkasa Abadi Job Site MLP in 2023

Intelligent Safety Risk Analysis and Decision-Making System for Underground Metal Mines Based on Big Data

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