Data Analytics Applied to the Mining Industry
暫譯: 應用於礦業的數據分析

Soofastaei, Ali

Data Analytics Applied to the Mining Industry
  • 出版商: CRC
  • 出版日期: 2020-11-13
  • 售價: $7,690
  • 貴賓價: 9.5 折 $7,306
  • 語言: 英文
  • 頁數: 280
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1138360007
  • ISBN-13: 9781138360006
  • 相關分類: Data Science

    • 海外代購書籍(需單獨結帳)

商品描述

Data Analytics Applied to the Mining Industry describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centers, autonomous equipment and the opportunities offered by the industrial internet of things. It provides guidelines on how data needs to be collected, stored and managed to enable the different advanced data analytics methods to be applied effectively in practice, through use of case studies, and worked examples. Aimed at graduate students, researchers, and professionals in the industry of mining engineering, this book:

 

  • Explains how to implement advanced data analytics through case studies and examples in mining engineering
  • Provides approaches and methods to improve data-driven decision making
  • Explains a concise overview of the state of the art for Mining Executives and Managers
  • Highlights and describes critical opportunity areas for mining optimization
  • Brings experience and learning in digital transformation from adjacent sectors

商品描述(中文翻譯)

《應用於礦業的數據分析》描述了礦業在轉型為數位產業過程中所面臨的主要挑戰，這使其能夠充分利用流程自動化、遠端操作中心、自主設備以及工業物聯網所提供的機會。本書提供了有關如何收集、儲存和管理數據的指導，以便有效地應用各種先進的數據分析方法，並通過案例研究和實作範例進行說明。本書的目標讀者為研究生、研究人員以及礦業工程領域的專業人士，內容包括：

- 解釋如何通過案例研究和礦業工程中的範例來實施先進的數據分析
- 提供改善數據驅動決策的方法和途徑
- 為礦業高管和經理提供最新技術的簡要概述
- 突出並描述礦業優化的關鍵機會領域
- 帶來來自相鄰行業的數位轉型經驗和學習

作者簡介

Ali Soofastaei is a Data Analyst at Vale and a Professorial Research Fellow at the University of Queensland (UQ) Australia. Vale is a Brazilian multinational corporation engaged in metals and mining and one of the largest logistics operators in Brazil. Vale is the most significant producer of iron ore and nickel in the world. Dr Soofastaei uses new models based on Artificial Intelligence (AI) methods to increase productivity, energy efficiency and reduce the total costs of mining operations. In the past 14 years, Dr Soofastaei has conducted a variety of research studies in academic and industrial environments. He has acquired an in-depth knowledge of Energy Efficiency Opportunities (EEO), VE and advanced data analysis. He is also proficient at using AI methods in data analysis to optimize the number of effective parameters in energy consumption in mining operations. Dr Soofastaei has been working in the oil, gas and mining industries and he has academic experience as an assistant professor. He has been in School of Mechanical and Mining Engineering at UQ since 2012 involved in many research and industrial projects, and I have been a member of the supervisory team for PhD and Master Students. Dr Soofastaei has completed many research projects and published their results in a lot of journal and conference papers. He also has developed few patents and five software packages.

作者簡介(中文翻譯)

阿里·蘇法斯泰（Ali Soofastaei）是巴西淡水河谷（Vale）的數據分析師，同時也是澳大利亞昆士蘭大學（University of Queensland, UQ）的教授研究員。淡水河谷是一家巴西跨國公司，專注於金屬和礦業，並且是巴西最大的物流運營商之一。淡水河谷是全球最大的鐵礦石和鎳的生產商。蘇法斯泰博士利用基於人工智慧（Artificial Intelligence, AI）方法的新模型來提高生產力、能源效率並降低礦業運營的總成本。在過去的14年中，蘇法斯泰博士在學術和工業環境中進行了各種研究。他對能源效率機會（Energy Efficiency Opportunities, EEO）、價值工程（Value Engineering, VE）和高級數據分析擁有深入的了解。他還擅長使用AI方法進行數據分析，以優化礦業運營中能源消耗的有效參數數量。蘇法斯泰博士在石油、天然氣和礦業行業工作，並擁有助理教授的學術經驗。自2012年以來，他一直在昆士蘭大學的機械與礦業工程學院工作，參與了許多研究和工業項目，並且是博士和碩士生的指導團隊成員。蘇法斯泰博士已完成多個研究項目，並在許多期刊和會議論文中發表了其結果。他還開發了幾項專利和五個軟體包。

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