Mining company uses Operations Optimization, powered by Predix, to improve throughput by more than 5.5%

Transcription

1 Mining company uses Operations Optimization, powered by Predix, to improve throughput by more than 5.5% Challenge: The company believed that it was losing potential revenue as a result of sub-optimal throughput and efficiency in the milling circuits. Action: Implemented GE s Digital Mine solution for process optimization on one of the milling circuits, to stabilize the circuit and optimize throughput. Increased average throughput by more than 5.5% Decreased power consumption per ton of material fed by almost 2% Decreased density variation of the cyclone feed

2 A problem that forced a new way of operating The senior metallurgist had a problem: the milling circuits were processing more and more waste material together with ore from the main reefs, causing significant operational issues. Even though the different sources were blended, the characteristics of the ore being fed to the mill changed dramatically, often in the space of minutes. This led to extreme variability in the circuit. Although there was a control strategy in place, it required a significant amount of manual intervention. Each operator had a different level of experience and, therefore, a different capacity to deal with the complex situations which faced him. If an operator hesitated to make a decision when he first saw a sign of instability in the circuit, or if he didn t make the right decision, operations could be compromised. With no technical assistance to automatically compensate for changes in the feed, results were inconsistent. With process inconsistency came reduced throughput and revenue losses. The senior metallurgist and the plant manager wanted to improve and stabilize grind quality, improve throughput, decrease energy costs, and increase revenue. They knew that it would be difficult to meet their goals under current conditions, so they decided to test advanced process control (APC) technology to help augment their staff.

3 If Operations Optimization were switched off, we would have to revert to the inconsistencies of the different mill operators using our old manual process. Mine Performance has had a massive impact on our efficiency. We now have more consistent throughput and more consistent power consumption. Plant Manager

4 The solution: Digital Mine delivers process optimization. Why Digital Mine? The plant needed to find the right solution for their problem, so the plant decided to ask for advice from a leading-edge mining company that already had faced a similar problem and had implemented the Digital Mine solution for process optimization. The senior metallurgist visited the mine and saw its solution Operations Optimization in use. - He talked to the operators, learned about process improvements in their milling circuits, and became convinced that they should test the solution at the processing plant on one of the mills. Tough challenges but a successful implementation Since it is an older plant, there were some challenges. It required some new base sensory and control infrastructure, and it needed technical assistance. It needed onsite help at the mill s remote location, along with help to overcome cultural challenges in the acceptance of the new solution. GE worked closely with the company onsite to address Figure 1: Mill Power-Load relationship before and after implementing Digital Mine. Before the solution was implemented, grind was suboptimal as shown in red. Post implementation (yellow data points), the mill operated closer to the apex where the maximum grind and energy efficiency are consistently reached. all of these needs. The Operations Optimization APC solution was implemented, which now continues to calculate optimal setpoints in real-time for multiple interacting variables (including mill feed rate, inmill density and cyclone feed). Increased throughput decreased power consumption decreased variation Operations Optimization proved that it could control the milling process to better handle disturbances within operational and physical constraints. The solution helped the mill obtain more consistent performance and higher, more stable throughput. Since the solution controlled the mill at its most optimal operating point, it also helped to decrease specific power consumption and improve grind (Figure 1). Solution results: 6 Increased average throughput by more than 5.5% 6 Decreased power consumption per ton of material fed by almost 2% 6 Decreased density variation of the cyclone feed.

5 Copyright 2016 By General Electric Company. All rights reserved. This document shall not be reproduced, redistributed, retransmitted, translated, abridged, adapted, condensed, revised or otherwise modified, in any form, in whole or in part, without the express written consent of GE.