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ABB at SME conference 2020 - #MineXchange2020

February 23-26, 2020 - Phoenix, AZ

ABB in Mining

ABB in Mining @ABB_Mining

Planning to visit Phoenix for #MineXchange2020? Join our technical sessions on Feb 24-26, with six interesting cas… t.co/yjypimX2YO

ABB sessions and speakers - February 24

GMD Cycloconverter Control Upgrade - Barrick Goldstrike

Obsolescence is one key topic that needs to be addressed by maintenance teams in mining operations. With the advancements in technology, especially on the control and automation fields, sometimes it is necessary to upgrade the existing system to prevent major downtimes due to e.g. threats on cyber security.

In Gearless Mill Drives application, the Cycloconverter that drives the ring motor has a control system that, in the recent case of Barrick Goldstrike, had to undergo a control upgrade.

This presentation shows the highlights and the challenges of the control upgrade at Barrick, where operators received a modern, very fast and state-of-the-art technology platform, including several new useful functionalities.

Learn more about ABB solutions for grinding

Best Practices - Condition Monitoring and Advanced Asset Health Tracking in Conveyor Belt Systems

Healthiness of a conveyor is largely determined through physical inspections at regular intervals and time-based maintenance. However, in many cases the conveyor belt damage happens between the actions causing huge production and time losses to the plants. The presentation purpose is to introduce how some traditional maintenance gaps on the conveyor condition based monitoring can be filled through the application of systematic failure modes monitoring, taking advantage of existing data and delivering valuable information about potential failures on the conveyor systems.

The existing information on the traditional systems can be integrated providing a full-view, online dashboard for the maintenance teams embracing mechanic, electric and control. Main savings of predictive approach aligns with studies of the Dept. of Energy achieving up to 40% over reactive and 12% over preventive maintenance, extending the life of the assets and avoiding unnecessary people exposure to the field. A reliable maintenance time-window for a planned action and an enhanced condition-based approach, monitoring the conveyor main components as belt, motor, gearbox, drives and transformers are key benefits.

Learn more about ABB Ability™ Predictive mantenance for mining

ABB sessions and speakers - February 25

SPCC Toquepala Expansion – Designing a Reliable Grinding Circuit

During feasibility phase, mining companies face several uncertainties which impact the design of the process: ore price fluctuations, permits, financing, speculations in markets etc.

Southern Peru Copper Corporation’s (SPCC) Toquepala Expansion project was not different. However, since the early phases the project team specified a grinding circuit with a state-of-the-art technology for the mills.

SPCC has chosen the variable speed gearless mill drives (GMD) technology for their Ball Mills, which brings multiple advantages in terms of efficiency and availability in comparison to standard ring-geared mills. This paper will present the reasons why SPCC considered GMDs for their mills, even when the mill powers were as low as 11MW.

Learn more about GMD technology

Case Study: Results From the Implementation of a Maintenance 4.0 Application for Plant Asset Management in a Mine & Processing Site

This study presents results obtained through the implementation of a Condition Monitoring System integrated to the Process Control System, focused on early diagnosis and optimization of maintenance planning activities in a Maintenance 4.0 application.

Major advantages of integrating operational and maintenance data are:

  • Break silos of information across maintenance and operation
  • Detect problems that cannot be identified using current predictive techniques
  • Holistic figures of plant assets, can be drilled down and detailed to each asset of the plant, per family of assets or process area, supporting failure analysis and identification of root causes.

Installed in a mine or processing plant, such application monitors on-line more than 6000 assets, assessing the health status of the assets and the process plant, defined by the combination and intelligent treatment of the available information on assets and the process, which is only possible through the integration between the process control system and the maintenance system. The benefits refer to losses of production and maintenance avoided in real cases in assets like crushers, vibrating screens, stackers and long-distance conveyors.

Learn more about Maintenance 4.0 application case study

Closing the Loop Between Mine Short Term Planning and Realtime Mine Operation Takes Ability

In open-pit and underground mining operations, the weekly production schedule is divided into days, shifts and hours for detailed planning and scheduling of resources. Although seemingly simple at first, the coordination between weekly production schedule and production execution is one of the top challenges in mines and has a direct impact on operational efficiency and costs.

This presentation is a practical demonstration of how an innovative Operations Management System integrates Short Interval Control and Closed Loop Scheduling into the same digital platform and effectively closes the loop between mine short term planning and real-time mine operation.

Learn more about ABB Ability™ Operations Management System

ABB sessions and speakers - February 26

Experiences From the Use of a Predictive Asset Health Monitoring Platform in Grinding

The maintenance process has been changing from corrective and preventive to predictive maintenance in order to improve availability of assets and productivity. While the first two paradigms focus on maintenance upon a failure or at fixed periods, the predictive maintenance continuously monitors health of the equipment and offers condition-based maintenance. In order to develop a reliable condition based monitoring platform, data is collected, stored and analyzed using advanced signal processing and artificial intelligence methods.

This presentation shows a holistic condition-monitoring platform applied in Grinding mills, where a broad fleet asset data is aggregated in a central platform, allowing for big data processing using machine learning techniques and providing asset health and advanced failure notifications. Real cases will be illustrated where unplanned shutdowns have been prevented by utilizing the remote diagnostic platform in conjunction with predictive maintenance techniques. A comparison among different types of techniques is presented while trying to understand which methodology fits best to the ultimate target of the maintenance strategy.

Learn more about ABB Ability™ Predictive Maintenance for grinding

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