Abstract

The technologies used in mineral process engineering are evolving. The digital mineral processing solutions are based on advances in our ability to instrumentally measure phenomena at several stages of the beneficiation circuit, manage the data in real-time, and to analyze these data using machine learning to develop the next generation of process control. The main purpose of this study is to overview various digital solutions for mineral processing plants and characterization laboratories while emphasizing their utilization in the current state of the digitization process of the GTK Mintec. This study highlights the specialized digital technologies that are particularly relevant for mineral processing and beneficiation. The digital solutions studied in this article include digital twin, machine vision, information management system, sensors, smart equipment, machine learning techniques, process control system, robotic cell, and Internet of Things applied across the whole chain of studying materials from the mineralogical examinations through the bench-scale studies to the pilot test trials. The aim is to provide a clear view on the different aspects of digitizing mineral processing plants based upon the lessons learned from the development plans in GTK Mintec.

Highlights

  • The mining industry is required to operate in an increasingly challenging business environment

  • The tests performed at the GTK Mintec pilot plant can be divided into two different

  • This study introduces various digital solutions for mineral processing plants and mineral characterization laboratories with an emphasis on the digitalization of the GTK Mintec

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Summary

Introduction

The mining industry is required to operate in an increasingly challenging business environment. Some ores contain higher amounts of penalty elements [2]. This means that the operating costs for the extraction of metals have become higher than ever before. There has been substantial pressure placed on the industry to extract more metal from increasingly challenging ores. The result of this trend has often been CAPEX and OPEX blowouts [3,4,5,6] in the investment cycle, and highly variable process performance in operation [7]

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