دورية أكاديمية

A Data-driven Framework to Reduce Diesel Spillages in Underground Mines

التفاصيل البيبلوغرافية
العنوان: A Data-driven Framework to Reduce Diesel Spillages in Underground Mines
المؤلفون: Sheila R. Ngwaku, Janine Pascoe, Wiehan A. Pelser, Jan C. Vosloo, Jean H. van Laar
المصدر: Mining, Vol 3, Iss 4, Pp 683-695 (2023)
بيانات النشر: MDPI AG, 2023.
سنة النشر: 2023
المجموعة: LCC:Mining engineering. Metallurgy
مصطلحات موضوعية: DIKW, underground mine, diesel spillages, diesel management, root cause analysis, Mining engineering. Metallurgy, TN1-997
الوصف: Several methodologies have been developed to manage diesel in open-cast mining due to its high demand and increasing diesel prices. Although the use of diesel-powered equipment in underground mines has increased over the years, effective management thereof has not received the same attention. With the advent of Industry 4.0, data can be utilised more effectively by modern businesses to identify and solve problems in a structured manner. In this study, an underground mine was used as a case study to determine whether a Data, Information, Knowledge, Wisdom (DIKW) method for diesel management could be coupled with the Six Sigma Define, Measure, Analyse, Improve, Control (DMAIC) tool to make more informed decisions and gain new insights to help reduce diesel wastage underground. The new integrated methodology identified diesel spillages and highlighted the biggest contributors to these underground spillages. The Six Sigma DMAIC domain utilised root cause analysis to determine the reason for recent systems failures, followed by the identification of practical solutions to eliminate up to 200 ML (megalitres) of diesel spillage. With this information, the case study mine stands to save over USD 175,000 per annum.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2673-6489
Relation: https://www.mdpi.com/2673-6489/3/4/37; https://doaj.org/toc/2673-6489
DOI: 10.3390/mining3040037
URL الوصول: https://doaj.org/article/03089b42bba94ce8ad143deb60711047
رقم الأكسشن: edsdoj.03089b42bba94ce8ad143deb60711047
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:26736489
DOI:10.3390/mining3040037