{
    "abstract": "Recently, there has been a growing interest in issues related to mining equipment maintenance, with particular focus on pumping systems' continuous operation. However, despite wide applications of pump system maintenance in a wide range of industries, such as water and wastewater, aviation, petrochemical, building (HVAC system), and nuclear power plant industries, the literature on maintenance of pump systems operating in the mining industry still needs development. This study aims to review the existing literature to present an up-to-date analysis of maintenance strategies for mining pumps, with a particular focus on proactive maintenance approaches. Key aspects considered include predictive diagnostics and prognosis, health status monitoring, maintenance management, and the integration of intelligent mining systems to enhance operational reliability and efficiency in harsh mining environments. The proposed methodology includes a systematic literature review with the use of the Primo multi-search tool, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The selection criteria focused on English studies published between 2005 and 2024, resulting in 88 highly relevant papers. These papers were categorized into six groups: (a) condition/health status monitoring, (b) dewatering system operation and maintenance, (c) health diagnosis and prognosis, (d) intelligent mining (modern technologies), (e) maintenance management, and (f) operational efficiency and reliability optimization. A notable strength of this study is its use of diverse scientific databases facilitated by the multi-search tool. Additionally, a bibliometric analysis was performed, showcasing the evolution of research on pump maintenance in the mining sector over the past decade and identifying key areas such as predictive diagnostics, dewatering system optimization, and intelligent maintenance management. This study highlights the varied levels of research and practical implementation across industries, emphasizing the mining sector's unique challenges and opportunities. Significant research gaps were identified, including the need for tailored diagnostic tools, real-time monitoring systems, and cost-effective maintenance strategies specific to harsh mining environments. Future research directions are proposed, focusing on advancing predictive maintenance technologies, integrating intelligent systems, and enhancing operational efficiency and reliability. The study concludes with a detailed discussion of the findings and their implications, offering a roadmap for innovations in pump maintenance within the mining industry.",
    "authors": [
        {
            "affiliation": "Faculty of Mechanical Engineering, Wroclaw University of Science and Technology, Wyspianskiego 27, 50-370 Wroclaw, Poland.",
            "firstname": "Sylwia",
            "initials": "S",
            "lastname": "Werbinska-Wojciechowska"
        },
        {
            "affiliation": "Faculty of Mechanical Engineering, Wroclaw University of Science and Technology, Wyspianskiego 27, 50-370 Wroclaw, Poland.",
            "firstname": "Rafal",
            "initials": "R",
            "lastname": "Rogowski"
        }
    ],
    "conclusions": null,
    "copyrights": null,
    "doi": "10.3390/s25082365\n10.1080/17480930902916239\n10.1016/S1674-5264(09)60248-9\n10.1007/978-1-84800-288-3_8\n10.1007/s42461-019-0094-2\n10.7166/27-4-1493\n10.3390/en15176263\n10.1109/28.315247\n10.1016/j.resourpol.2023.104291\n10.3390/machines12120845\n10.1504/IJISE.2013.056095\n10.1007/s11668-020-00949-z\n10.1108/JQME-03-2017-0016\n10.1016/0308-0161(94)00114-X\n10.1016/S1474-6670(17)42529-8\n10.5277/ms142101\n10.3390/mining3010002\n10.1108/JQME-12-2015-0067\n10.1016/j.proeng.2017.01.237\n10.1049/joe.2018.9162\n10.1016/j.rser.2013.11.030\n10.3390/s20082425\n10.1016/j.rser.2022.112826\n10.1016/j.cirpj.2024.02.003\n10.1080/25726668.2023.2257479\n10.1007/s11831-018-9286-z\n10.3390/vibration7040054\n10.1088/2631-8695/ad299f\n10.1136/bmj.n71\n10.1016/j.rineng.2020.100181\n10.1016/j.jclepro.2019.05.029\n10.3390/mining1010008\n10.1007/BF02504559\n10.1016/j.eswa.2011.10.008\n10.2298/TSCI0604033V\n10.1080/01430750.2022.2056917\n10.1088/1742-6596/2591/1/012057\n10.1016/j.cie.2012.02.002\n10.1108/13552511211281552\n10.3390/app122211691\n10.1016/j.autcon.2021.104049\n10.1016/j.sna.2022.113864\n10.1109/ACCESS.2022.3187718\n10.3390/s22249714\n10.36001/ijphm.2022.v13i1.3134\n10.1007/s42452-023-05618-y\n10.3390/app12020688\n10.32604/sv.2020.05055\n10.3311/PPme.12140\n10.3390/s21041470\n10.1108/JQME-10-2020-0107\n10.5772/26439\n10.3390/s22062106\n10.1145/1134285.1134500\n10.1007/s10479-022-04983-y\n10.1097/01.NAJ.0000444496.24228.2c\n10.1111/1467-8551.00375\n10.1016/j.ijsu.2010.02.007\n10.1136/bmj.b2535\n10.1007/s13563-024-00455-w\n10.1080/12460125.2020.1798591\n10.3390/s23031409\n10.1016/j.engfailanal.2019.104152\n10.1109/ICCAD49821.2020.9260504\n10.3390/analytics3040028\n10.1186/1471-2288-13-141\n10.1007/s11192-009-0146-3\n10.1016/j.engfailanal.2021.105637\n10.3389/fenrg.2021.762159\n10.3390/machines9120373\n10.35940/ijrte.c4354.099320\n10.1109/ICIG.2013.163\n10.1179/174328610X12682159815109\n10.1007/s40430-023-04240-8\n10.5604/01.3001.0053.9060\n10.5120/12403-8851\n10.1109/MEC.2011.6025693\n10.1007/s12665-018-7878-4\n10.9734/psij/2024/v28i2821\n10.1016/j.proeng.2017.03.229\n10.3390/pr10112241\n10.1016/j.engappai.2015.01.003\n10.1007/s13202-021-01392-y\n10.3390/w15050992\n10.5604/01.3001.0016.3245\n10.1016/j.vacuum.2022.111425\n10.1016/j.apenergy.2016.12.093\n10.1016/j.psep.2021.05.017\n10.3390/app12062825\n10.1109/TIA.2014.2339403\n10.1016/j.matpr.2020.09.327\n10.1016/j.measurement.2020.108676\n10.1016/j.procir.2022.05.106\n10.3390/s24030739\n10.1016/j.ymssp.2006.10.001\n10.1016/j.engfailanal.2022.106095\n10.1016/j.ymssp.2015.03.029\n10.1007/s13369-023-07976-6\n10.1016/j.infrared.2016.12.003\n10.23919/ICEMS50442.2020.9291035\n10.3390/app12010350\n10.1109/ICCTD.2010.5646134\n10.1016/j.triboint.2017.05.010\n10.1109/EPE.2015.7161127\n10.1109/ACCESS.2021.3108427\n10.1177/1687814019845955\n10.1088/1742-6596/1333/5/052014\n10.1016/j.ress.2013.07.017\n10.23977/jceup.2024.060110\n10.3390/s23229034\n10.1007/s10845-021-01861-5\n10.54517/met.v3i2.2130\n10.1088/1742-6596/2121/1/012024\n10.1155/2021/5569994\n10.7166/31-4-2325\n10.1016/j.ress.2013.06.038\n10.17159/2411-9717/2017/v117n1a9\n10.1016/j.psep.2012.11.003",
    "journal": "Sensors (Basel, Switzerland)",
    "keywords": [
        "condition-based monitoring",
        "predictive maintenance",
        "pump diagnosis and prognosis",
        "pump systems",
        "systematic review",
        "the mining industry"
    ],
    "methods": null,
    "publication_date": "2025-04-26",
    "pubmed_id": "40285056\n32344674\n33782057\n36560083\n33672479\n35336277\n15141602\n36212520\n24572533\n20171303\n21603045\n36772449\n24237877\n20585380\n38339456\n38005422",
    "results": null,
    "title": "Proactive Maintenance of Pump Systems Operating in the Mining Industry-A Systematic Review.",
    "xml": "<Element 'PubmedArticle' at 0x78850447b3d0>"
}