Data analytics applied to the mining industry / edited by Ali Soofastaei.

Format:

Book

Contributor:

Soofastaei, Ali, editor.

Language:

English

Subjects (All):

Mining engineering--Data processing.

Mining engineering.

Physical Description:

1 online resource : illustrations (some color)

Edition:

1st edition

Place of Publication:

Boca Raton, FL ; Abingdon, Oxon : CRC Press, Taylor & Francis Group, 2021.

Summary:

"The book describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centres, 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. Each chapter ends with a section detailing lessons for mining. The final chapter explores the revised operating principles, the organizational characteristics and the new skills needed by mining companies"-- Provided by publisher.

Contents:

Digital transformation of mining

Advanced-data analytics

Data collection, storage and retrieval

Making sense of data

Analytics toolsets

Process analytics

Predictive maintenance of mining machines : applying advanced data analysis

Data analytics for energy efficiency and gas emission reduction

Making decisions based on analytics

Future skills requirements.

Notes:

Includes bibliographical references and index.

Description based on print version record and CIP data provided by publisher.

ISBN:

0-429-43336-0

0-429-78176-8

9780429433368

OCLC:

1156428782