Strategic load management: Enhancing eco-efficiency in mining operations through automated technologies
In the face of escalating global demands for sustainable practices within the construction and mining sectors, this paper investigates the transformative impact of automated load analysis technologies. Focused on bridging the gap between traditional operational methodologies and the forefront of aut...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Results in Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123024011459 |
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| author | Ali Akbar Firoozi Magdeline Tshambane Ali Asghar Firoozi Sajid Mubashir Sheikh |
| author_facet | Ali Akbar Firoozi Magdeline Tshambane Ali Asghar Firoozi Sajid Mubashir Sheikh |
| author_sort | Ali Akbar Firoozi |
| collection | DOAJ |
| description | In the face of escalating global demands for sustainable practices within the construction and mining sectors, this paper investigates the transformative impact of automated load analysis technologies. Focused on bridging the gap between traditional operational methodologies and the forefront of automation technology, the study provides an in-depth examination of the integration of onboard weighing systems, the Internet of Things (IoT), and machine learning into mining operations. Through a series of detailed case studies, the research showcases how these technological innovations contribute to substantial improvements in operational efficiency, notably through enhanced load management, reduced fuel consumption, and optimized resource allocation, thereby fostering a decrease in the environmental footprint of mining activities. Furthermore, the paper addresses critical sustainability issues, including workforce transformation, stakeholder engagement, and the broader environmental implications of adopting automated technologies in mining processes. Concluding with strategic policy recommendations, the study advocates for widespread adoption of automated systems within the construction sector to achieve improved environmental and economic outcomes. By emphasizing a multidisciplinary approach, this research highlights the essential role of technological innovation in aligning mining operations with sustainable development goals, positioning automated load analysis as a pivotal strategy for advancing eco-efficiency in the construction and mining industries. |
| format | Article |
| id | doaj-art-aaede1d4c75a4cb89cf10238bf4d7210 |
| institution | OA Journals |
| issn | 2590-1230 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-aaede1d4c75a4cb89cf10238bf4d72102025-08-20T01:58:31ZengElsevierResults in Engineering2590-12302024-12-012410289010.1016/j.rineng.2024.102890Strategic load management: Enhancing eco-efficiency in mining operations through automated technologiesAli Akbar Firoozi0Magdeline Tshambane1Ali Asghar Firoozi2Sajid Mubashir Sheikh3Department of Civil Engineering, Faculty of Engineering & Technology, University of Botswana, Gaborone, Botswana; Corresponding author.Department of Civil Engineering, Faculty of Engineering & Technology, University of Botswana, Gaborone, BotswanaDepartment of Civil Engineering, Faculty of Engineering & Technology, University of Botswana, Gaborone, Botswana; Department of Electrical Engineering, Faculty of Engineering & Technology, University of Botswana, Gaborone, Botswana; Department of Civil Engineering, Faculty of Engineering, National University of Malaysia (UKM), Selangor, MalaysiaDepartment of Electrical Engineering, Faculty of Engineering & Technology, University of Botswana, Gaborone, BotswanaIn the face of escalating global demands for sustainable practices within the construction and mining sectors, this paper investigates the transformative impact of automated load analysis technologies. Focused on bridging the gap between traditional operational methodologies and the forefront of automation technology, the study provides an in-depth examination of the integration of onboard weighing systems, the Internet of Things (IoT), and machine learning into mining operations. Through a series of detailed case studies, the research showcases how these technological innovations contribute to substantial improvements in operational efficiency, notably through enhanced load management, reduced fuel consumption, and optimized resource allocation, thereby fostering a decrease in the environmental footprint of mining activities. Furthermore, the paper addresses critical sustainability issues, including workforce transformation, stakeholder engagement, and the broader environmental implications of adopting automated technologies in mining processes. Concluding with strategic policy recommendations, the study advocates for widespread adoption of automated systems within the construction sector to achieve improved environmental and economic outcomes. By emphasizing a multidisciplinary approach, this research highlights the essential role of technological innovation in aligning mining operations with sustainable development goals, positioning automated load analysis as a pivotal strategy for advancing eco-efficiency in the construction and mining industries.http://www.sciencedirect.com/science/article/pii/S2590123024011459Sustainable miningAutomated load analysisConstruction efficiencyIoT in miningMachine learningResource optimization |
| spellingShingle | Ali Akbar Firoozi Magdeline Tshambane Ali Asghar Firoozi Sajid Mubashir Sheikh Strategic load management: Enhancing eco-efficiency in mining operations through automated technologies Results in Engineering Sustainable mining Automated load analysis Construction efficiency IoT in mining Machine learning Resource optimization |
| title | Strategic load management: Enhancing eco-efficiency in mining operations through automated technologies |
| title_full | Strategic load management: Enhancing eco-efficiency in mining operations through automated technologies |
| title_fullStr | Strategic load management: Enhancing eco-efficiency in mining operations through automated technologies |
| title_full_unstemmed | Strategic load management: Enhancing eco-efficiency in mining operations through automated technologies |
| title_short | Strategic load management: Enhancing eco-efficiency in mining operations through automated technologies |
| title_sort | strategic load management enhancing eco efficiency in mining operations through automated technologies |
| topic | Sustainable mining Automated load analysis Construction efficiency IoT in mining Machine learning Resource optimization |
| url | http://www.sciencedirect.com/science/article/pii/S2590123024011459 |
| work_keys_str_mv | AT aliakbarfiroozi strategicloadmanagementenhancingecoefficiencyinminingoperationsthroughautomatedtechnologies AT magdelinetshambane strategicloadmanagementenhancingecoefficiencyinminingoperationsthroughautomatedtechnologies AT aliasgharfiroozi strategicloadmanagementenhancingecoefficiencyinminingoperationsthroughautomatedtechnologies AT sajidmubashirsheikh strategicloadmanagementenhancingecoefficiencyinminingoperationsthroughautomatedtechnologies |