Sürdürülebilir Kalkınma Amaçları

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Yazarlar

• Altun, O.(1)
• Aydogan, N.(1)
• Benzer, H.(1)
• Dessureault, Sean(1)
• Dundar, H.(1)
• Gulsun Kilic, M.(1)
• Kahraman, M. Mustafa(1)
• Kahraman, M.M.(1)
• Karadeniz, M.(1)
• Kertmen, P.(1)
• Kundak, E.(1)
• Rogers, W. Pratt(1)
• Yilmazkaya, E.(1)

• BildiriYalnız künye2019/r/gumushane/15064
  Measuring and improving operator performance on large mining equipment

  Kahraman, M.M.; Benzer, H.; Aydogan, N.; Karadeniz, M.; Altun, O.; Dundar, H.; Gulsun Kilic, M.; Kundak, E.; Yilmazkaya, E.; Kertmen, P.

  Mining as an industry is in the middle of commodity price upheaval that is wiping out many mining firms. Only the companies that have adapted right technology and data driven decision making culture will survive after each commodity price cycle. Latest technological solutions made it possible to track materials and equipment in every step of mining; from the face to plant to facilitate decision making process. Mines are investing in equipment monitoring technology with the expectation of gaining large increases in equipment productivity and reliability. Simply buying the technology does not result in achieving the promised benefits. Only a holistic approach can achieve these benefits, considering the people (analytical skills and culture), the process (deliberate means of using the data), and the platform (analytical technology). One of the principle methods for achieving this advantage is through increasing productivity and equipment health of major production equipment. This paper presents a case study using equipment monitoring technology as part of an operator performance system for a major machine asset: a dragline.

  AtıfScopus1

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• MakaleYalnız künye2019Scopus SJRQ2/r/gumushane/11352
  Exploring the value of using data: a case study of continuous improvement through data warehousing

  Rogers, W. Pratt; Kahraman, M. Mustafa; Dessureault, Sean

  The mining industry is adapting data-rich technology. Data management processes and infrastructure require additional investment which, can be difficult to justify. A valuation model for data management infrastructure would necessitate modelling the ‘use’ of data and quantifying the value and the likelihood of success of improvement initiatives. A model is presented which can assess the impacts of a data-driven initiative. The initiatives are shown to be the foundation of improved shift coordination resulting in significant and sustained operational improvements. This paper aims to illustrate the value of using data from source systems in mining operations.

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  AtıfScopus9·WoS8·OpenAlex11

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