IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i13p2505-d243945.html
   My bibliography  Save this article

Analysing the Utilisation Effectiveness of Mining Machines Using Independent Data Acquisition Systems: A Case Study

Author

Listed:
  • Jarosław Brodny

    (Faculty of Organization and Management, Silesian University of Technology, 41-800 Zabrze, Poland)

  • Magdalena Tutak

    (Faculty of Mining, Safety Engineering and Industrial Automation, Silesian University of Technology, 44-100 Gliwice, Poland)

Abstract

Growing competition in the market for energy raw materials needed for power generation has led to an increasing number of measures being undertaken in the mining sector to reduce the unit costs of mining production. One of the areas that offer considerable savings in this regard is the utilisation of the technical resources owned by mines. This article is therefore focussed on analysing the utilisation effectiveness of these machines, based on the data recorded by industrial automation systems, as well as on measurements from independent surveying and chemical analysis of the excavated material’s quality. For this purpose, a methodology was developed to use the data about the operational parameters of the machines in order to analyse the effectiveness of their utilisation. It was assumed that the reliability of this assessment would depend mainly on the quality of the data used to conduct it. It was also assumed that using independent data sources for the analysis would provide objective and reliable information on the operation of the machines, devoid of any subjective feelings of the personnel or other factors. The developed methodology, based on a modified Overall Equipment Effectiveness (OEE) model, was used to analyse four machines that comprise the automated longwall system. Values were determined for each machine, including their availability, performance and product quality. This, in turn, made it possible to determine a total effectiveness indicator, based on a modified Overall Equipment Effectiveness (OEE) model, for the particular machines and the entire technical systems they form. The obtained results were used to assess the effectiveness of their utilisation and recommend corrective measures aimed at improving this metric. Moreover, the analysis results made it possible to assess the utilisation status of the machines in question. They also served as the basis for determining further lines of research, the purpose of which is to improve the effectiveness of the mining sector. The obtained results indicated that this process requires the wide application of IT tools, especially for data archiving and analysis. These tools, along with the developed model and methodology based on the analysis of large volumes of digital data, are in accord with the activities related to the implementation of Industry 4.0 idea in mining. It is the authors’ opinion that the material at hand should find a wide range of practical applications in supporting the management of technical resources within the mining sector.

Suggested Citation

  • Jarosław Brodny & Magdalena Tutak, 2019. "Analysing the Utilisation Effectiveness of Mining Machines Using Independent Data Acquisition Systems: A Case Study," Energies, MDPI, vol. 12(13), pages 1-15, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:13:p:2505-:d:243945
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/13/2505/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/13/2505/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Barabady, Javad & Kumar, Uday, 2008. "Reliability analysis of mining equipment: A case study of a crushing plant at Jajarm Bauxite Mine in Iran," Reliability Engineering and System Safety, Elsevier, vol. 93(4), pages 647-653.
    2. Rosario Domingo & Sergio Aguado, 2015. "Overall Environmental Equipment Effectiveness as a Metric of a Lean and Green Manufacturing System," Sustainability, MDPI, vol. 7(7), pages 1-17, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sergey Zhironkin & Alexey Selyukov & Magerram Gasanov, 2020. "Parameters of Transition from Deepening Longitudinal to Continuous Lateral Surface Mining Methods to Decrease Environmental Damage in Coal Clusters," Energies, MDPI, vol. 13(13), pages 1-22, June.
    2. Zhiguo LU & Wenjun JU & Fuqiang GAO & Youliang FENG & Zhuoyue SUN & Hao WANG & Kang YI, 2019. "A New Bursting Liability Evaluation Index for Coal –The Effective Elastic Strain Energy Release Rate," Energies, MDPI, vol. 12(19), pages 1-15, September.
    3. Katarzyna Tobór-Osadnik & Bożena Gajdzik & Grzegorz Strzelec, 2023. "Configurational Path of Decarbonisation Based on Coal Mine Methane (CMM): An Econometric Model for the Polish Mining Industry," Sustainability, MDPI, vol. 15(13), pages 1-16, June.
    4. Railh Gugus Tresor Massonini Ngoma & Cety Gessica Abraham Mahanga Tsoni & Xiangrui Meng & Sumaiya Bashiru Danwana, 2023. "The Impact of the Mining Equipment, Technological Trends, and Natural Resource Demand on Climate Change in Congo," Sustainability, MDPI, vol. 15(2), pages 1-28, January.
    5. Yang Yu & Jianbiao Bai & Xiangyu Wang & Lianying Zhang, 2020. "Control of the Surrounding Rock of a Goaf-Side Entry Driving Heading Mining Face," Sustainability, MDPI, vol. 12(7), pages 1-16, March.
    6. Jarosław Brodny & Magdalena Tutak, 2020. "The Use of Artificial Neural Networks to Analyze Greenhouse Gas and Air Pollutant Emissions from the Mining and Quarrying Sector in the European Union," Energies, MDPI, vol. 13(8), pages 1-31, April.
    7. Cun Zhang & Xiaojie Wang & Shangxin Fang & Xutao Shi, 2022. "Construction and Application of VR-AR Teaching System in Coal-Based Energy Education," Sustainability, MDPI, vol. 14(23), pages 1-14, December.
    8. Dawid Szurgacz & Sergey Zhironkin & Stefan Vöth & Jiří Pokorný & A.J.S. (Sam) Spearing & Michal Cehlár & Marta Stempniak & Leszek Sobik, 2021. "Thermal Imaging Study to Determine the Operational Condition of a Conveyor Belt Drive System Structure," Energies, MDPI, vol. 14(11), pages 1-18, June.
    9. Liu, Hao & Li, Zenghua & Yang, Yongliang & Miao, Guodong, 2023. "Study on the thermal behavior of coal during the spontaneous combustion latency," Energy, Elsevier, vol. 281(C).
    10. Dawid Szurgacz & Sergey Zhironkin & Michal Cehlár & Stefan Vöth & Sam Spearing & Ma Liqiang, 2021. "A Step-by-Step Procedure for Tests and Assessment of the Automatic Operation of a Powered Roof Support," Energies, MDPI, vol. 14(3), pages 1-16, January.
    11. Arabi, Mahsa & Gholamian, Mohammad Reza, 2023. "Resilient closed-loop supply chain network design considering quality uncertainty: A case study of stone quarries," Resources Policy, Elsevier, vol. 80(C).
    12. Magdalena Tutak & Jarosław Brodny & Dawid Szurgacz & Leszek Sobik & Sergey Zhironkin, 2020. "The Impact of the Ventilation System on the Methane Release Hazard and Spontaneous Combustion of Coal in the Area of Exploitation—A Case Study," Energies, MDPI, vol. 13(18), pages 1-31, September.
    13. Rafał Trzaska & Adam Sulich & Michał Organa & Jerzy Niemczyk & Bartosz Jasiński, 2021. "Digitalization Business Strategies in Energy Sector: Solving Problems with Uncertainty under Industry 4.0 Conditions," Energies, MDPI, vol. 14(23), pages 1-21, November.
    14. Houqiang Yang & Changliang Han & Nong Zhang & Changlun Sun & Dongjiang Pan & Minghui Dong, 2019. "Stability Control of a Goaf-Side Roadway under the Mining Disturbance of an Adjacent Coal Working Face in an Underground Mine," Sustainability, MDPI, vol. 11(22), pages 1-18, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Railh Gugus Tresor Massonini Ngoma & Cety Gessica Abraham Mahanga Tsoni & Xiangrui Meng & Sumaiya Bashiru Danwana, 2023. "The Impact of the Mining Equipment, Technological Trends, and Natural Resource Demand on Climate Change in Congo," Sustainability, MDPI, vol. 15(2), pages 1-28, January.
    2. Rajkumar Bhimgonda Patil & Basavraj S Kothavale & Laxman Yadu Waghmode, 2019. "Selection of time-to-failure model for computerized numerical control turning center based on the assessment of trends in maintenance data," Journal of Risk and Reliability, , vol. 233(2), pages 105-117, April.
    3. Barabadi, Abbas & Barabady, Javad & Markeset, Tore, 2014. "Application of reliability models with covariates in spare part prediction and optimization – A case study," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 1-7.
    4. Luis Miguel Calvo & Rosario Domingo, 2017. "CO 2 Emissions Reduction and Energy Efficiency Improvements in Paper Making Drying Process Control by Sensors," Sustainability, MDPI, vol. 9(4), pages 1-17, March.
    5. Panagiotis H. Tsarouhas & George K. Fourlas, 2016. "Mission reliability estimation of mobile robot system," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 7(2), pages 220-228, June.
    6. Kartick Bhushan & Somnath Chattopadhyaya & Shubham Sharma & Kamal Sharma & Changhe Li & Yanbin Zhang & Elsayed Mohamed Tag Eldin, 2022. "Analyzing Reliability and Maintainability of Crawler Dozer BD155 Transmission Failure Using Markov Method and Total Productive Maintenance: A Novel Case Study for Improvement Productivity," Sustainability, MDPI, vol. 14(21), pages 1-17, November.
    7. Giancarlo Nota & Francesco David Nota & Domenico Peluso & Alonso Toro Lazo, 2020. "Energy Efficiency in Industry 4.0: The Case of Batch Production Processes," Sustainability, MDPI, vol. 12(16), pages 1-28, August.
    8. Jacek Paś, 2023. "Issues Related to Power Supply Reliability in Integrated Electronic Security Systems Operated in Buildings and Vast Areas," Energies, MDPI, vol. 16(8), pages 1-22, April.
    9. Orlando Durán & Andrea Capaldo & Paulo Andrés Duran Acevedo, 2018. "Sustainable Overall Throughputability Effectiveness (S.O.T.E.) as a Metric for Production Systems," Sustainability, MDPI, vol. 10(2), pages 1-15, January.
    10. Ali Nouri Gharahasanlou & Mohammad Ataei & Reza Khalokakaie & Abbas Barabadi & Vahid Einian, 2017. "Risk based maintenance strategy: a quantitative approach based on time-to-failure model," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(3), pages 602-611, September.
    11. Chia-Nan Wang & Ying-Fang Huang & Thi-Nham Le & Thanh-Tuan Ta, 2016. "An Innovative Approach to Enhancing the Sustainable Development of Japanese Automobile Suppliers," Sustainability, MDPI, vol. 8(5), pages 1-19, April.
    12. Amin Moniri-Morad & Mohammad Pourgol-Mohammad & Hamid Aghababaei & Javad Sattarvand, 2019. "Reliability-based covariate analysis for complex systems in heterogeneous environment: Case study of mining equipment," Journal of Risk and Reliability, , vol. 233(4), pages 593-604, August.
    13. Silvana Dalmutt Kruger & Antonio Zanin & Orlando Durán & Paulo Afonso, 2022. "Performance Measurement Model for Sustainability Assessment of the Swine Supply Chain," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    14. Wilson Kosasih & I Nyoman Pujawan & Putu Dana Karningsih, 2023. "Integrated Lean-Green Practices and Supply Chain Sustainability for Manufacturing SMEs: A Systematic Literature Review and Research Agenda," Sustainability, MDPI, vol. 15(16), pages 1-28, August.
    15. Nupur Goyal & Mangey Ram & Ajay Kaushik, 2017. "Performability of solar thermal power plant under reliability characteristics," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 479-487, June.
    16. Nader, Joelle & El-Khalil, Raed & Nassar, Elma & Hong, Paul, 2022. "Pandemic planning, sustainability practices, and organizational performance: An empirical investigation of global manufacturing firms," International Journal of Production Economics, Elsevier, vol. 246(C).
    17. P Viveros & E Zio & F Kristjanpoller & A Arata, 2012. "Integrated system reliability and productive capacity analysis of a production line. A case study for a Chilean mining process," Journal of Risk and Reliability, , vol. 226(3), pages 305-317, June.
    18. Cagatay Tasdemir & Rado Gazo, 2018. "A Systematic Literature Review for Better Understanding of Lean Driven Sustainability," Sustainability, MDPI, vol. 10(7), pages 1-54, July.
    19. Muñoz-Villamizar, Andrés & Santos, Javier & Montoya-Torres, Jairo R. & Jaca, Carmen, 2018. "Using OEE to evaluate the effectiveness of urban freight transportation systems: A case study," International Journal of Production Economics, Elsevier, vol. 197(C), pages 232-242.
    20. Barabadi, Abbas & Barabady, Javad & Markeset, Tore, 2011. "Maintainability analysis considering time-dependent and time-independent covariates," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 210-217.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:13:p:2505-:d:243945. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.