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dc.contributor.advisorAnani, Angelina
dc.contributor.authorQuansah, Ebo Acquah
dc.creatorQuansah, Ebo Acquah
dc.date.accessioned2025-08-04T23:32:46Z
dc.date.available2025-08-04T23:32:46Z
dc.date.issued2025
dc.identifier.citationQuansah, Ebo Acquah. (2025). Optimizing Overall Slope Angle and Net Present Value (NPV) Through the Utilization of Ground-Based Pit Wall Monitoring Data (Master's thesis, University of Arizona, Tucson, USA).
dc.identifier.urihttp://hdl.handle.net/10150/678049
dc.description.abstractIn open-pit mining, determining the optimal Overall Slope Angle (OSA) is a complex but essential task that balances safety and economic considerations. Slope angle decisions directly impact both the stability of open pit mine walls and the economic viability of the operation. This research proposes a structured approach to OSA optimization by leveraging real-time ground-based pit-wall monitoring data. By integrating radar system data with detailed geotechnical models, the study assessed slope stability in a data-driven manner. Through the use of Rocscience Slide3 software, stability analysis was conducted on actual mine data, offering an understanding of the effectiveness of using monitoring technologies to guide slope design adjustments. A significant finding of this study was the regressive trend observed in the radar data obtained from the chosen mine for this study, which indicated that steepening the slope could be feasible without compromising safety. The initial and modified slopes were evaluated by calculating the Factor of Safety (FS), a key metric for assessing stability. The FS was observed to In open-pit mining, determining the optimal Overall Slope Angle (OSA) is a complex but essential task that balances safety and economic considerations. Slope angle decisions directly impact both the stability of open pit mine walls and the economic viability of the operation. This research proposes a structured approach to OSA optimization by leveraging real-time ground-based pit-wall monitoring data. By integrating radar system data with detailed geotechnical models, the study assessed slope stability in a data-driven manner. Through the use of Rocscience Slide3 software, stability analysis was conducted on actual mine data, offering an understanding of the effectiveness of using monitoring technologies to guide slope design adjustments. A significant finding of this study was the regressive trend observed in the radar data obtained from the chosen mine for this study, which indicated that steepening the slope could be feasible without compromising safety. The initial and modified slopes were evaluated by calculating the Factor of Safety (FS), a key metric for assessing stability. The FS was observed to decrease from 1.59 to 1.401 after the slope adjustment, remaining within industry and company-accepted safety thresholds. This calculated reduction demonstrated that, even with a steeper slope, the mine retained a satisfactory safety level, thus validating the reliability of using ground-based radar data to inform slope modifications. In addition to confirming slope stability, the study assessed the economic implications of slope adjustments using MinePlan 3D software. An economic analysis revealed that increasing the OSA by just 1° yielded a 1.534% improvement in the mine's Net Present Value (NPV). This finding underscored the economic advantages of refining slope angles in real-time based on accurate monitoring data. Overall, this paper illustrates how real-time monitoring, paired with geotechnical modeling and economic assessment, can effectively optimize slope design. This approach not only reduces the likelihood of slope failures but also enhances profitability and extends the operational life of mine, providing a solid foundation for balancing safety and economic goals in open-pit miningdecrease from 1.59 to 1.401 after the slope adjustment, remaining within industry and company-accepted safety thresholds. This calculated reduction demonstrated that, even with a steeper slope, the mine retained a satisfactory safety level, thus validating the reliability of using ground-based radar data to inform slope modifications. In addition to confirming slope stability, the study assessed the economic implications of slope adjustments using MinePlan 3D software. An economic analysis revealed that increasing the OSA by just 1° yielded a 1.534% improvement in the mine's Net Present Value (NPV). This finding underscored the economic advantages of refining slope angles in real-time based on accurate monitoring data. Overall, this paper illustrates how real-time monitoring, paired with geotechnical modeling and economic assessment, can effectively optimize slope design. This approach not only reduces the likelihood of slope failures but also enhances profitability and extends the operational life of mine, providing a solid foundation for balancing safety and economic goals in open-pit mining.en_US
dc.language.isoen_USen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectGeotechnical modelsen_US
dc.subjectMonitoring technologiesen_US
dc.subjectNet Present Value (NPV)en_US
dc.subjectOpen-pit miningen_US
dc.subjectOverall Slope Angle (OSA)en_US
dc.subjectSlope stabilityen_US
dc.titleOptimizing Overall Slope Angle and Net Present Value (NPV) Through the Utilization of Ground-Based Pit Wall Monitoring Dataen_US
dc.typetexten_US
dc.typeElectronic Thesisen_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.levelmastersen_US
dc.contributor.committeememberAnani, Angelina
dc.contributor.committeememberMomayez, Moe
dc.contributor.committeememberWaqas, Muhammad
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineMining and Geological Engineeringen_US
thesis.degree.nameM.S.en_US
refterms.dateFOA2025-08-04T23:32:48Z


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