Real-time expert system a real gold mine

Mine revenues jumped $7 million per year at Kemess Mines in British Columbia after installation of an expert system controlling the process, and pushed throughput by 5%.

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By Greg Rasmussen, Mill Superintendent, Northgate Minerals Corp.

NORTHGATE MINERALS CORP. (Vancouver, BC, Canada) is a gold and copper mining company. Its principal assets are its Kemess

HAVING A BALL

Ball mills (shown here) reduces the mined material down to 150 microns, producing 300,000 ounces of gold per year.


South mine in north-central British Columbia, which produces 300,000 ounces per year of gold, and the adjacent Kemess North deposit, which contains an indicated resource of 5.4 million ounces of gold and 2 billion pounds of copper. The Kemess South mine has two mill lines, each consisting of a semi-autogenuous grinding (SAG) mill that grinds rock from 6 in. down to 1/2 in., and a ball mill that further reduces the material down to 150 microns. Powered by two 6,000-hp motors, each of the mills are 15.5 ft. long and 34-ft. in diameter and are controlled by an Invensys Foxboro I/A distributed control system (DCS).

In the past, the mills were not pushed that hard because operators, who also have many other jobs, were not able to focus on throughput. To overcome this, run the mills on a more consistent basis and stabilize our control strategy, the company decided to implement an expert system. We issued a request for proposals and selected mine process systems integrator Minnovex Technologies because the its people clearly understood the mining business and their references were excellent. Minnovex’ proposal also strongly emphasized operator buy-in, which anyone knows critical for a successful implementation of these types of systems.

Room for Improvement
Because operators did not have time to consistently monitor the operation of the mills, downtime was higher and throughput lower than it could have been. The mines operated with four different crews, each with their own individual procedures. Operators were usually able to make supervisory control adjustments but only about every 30 minutes under normal conditions and every 5–10 minutes in the case of upsets. The mills were producing 49,500 tons/day but we believed there was considerable room for improvement. Every 1% increase in throughput in the mills produces $1.5 million in incremental revenues, so the stakes were high.

Northgate began the implementation process with Minnovex by talking to the people that know the machinery and processes best, the mill’s operators. They were asked a number of questions including: How do you control the equipment? What control strategy do you use under various conditions? When do you make setpoint changes and how does the process behave in these situations? Northgate’s managers distilled their existing strategy into a flow chart of decision-making operations that everyone understood. The result was that on Minnovex’ very first trip to the plant, which involved two people and took five days, everyone--from operators to top management--agreed on the best operating practices for the mill. From the beginning the integrator had a very good idea of what the expert system would do and went back to their offices to create it.

Platform Reduces Development Time
Minnovex Expert Technology (MET) system consists of a toolkit and a repeatable and sustainable methodology designed for developing expert systems in the industries in which the company works. The toolkit was developed using Gensym’s G2 real-time expert system platform. An expert system is a software program that solves problems using information and reasoning techniques normally associated with a human expert. With such a system operators can assess, diagnose, and respond to unusual operating situations or seek to optimize operations. The MET system also provides a number of diagnostic and development tools so that system administrators can help ensure maintenance goals are met and continued growth are possible without extensive training or experience.

The G2 platform provides a structure that makes it easy to collect data in real time and determine what actions to take. Development time and effort are reduced because most of the application logic can be applied parametrically by changing the properties of or relationships between objects rather than by coding.

MET modules use the platform to optimize the operation of the mill lines by defining the state of the process through both measured and inferred values. MET then determines the operating actions that maximize throughput.

For example, suppose the mill was approaching an overload condition, with the power decreasing and load increasing. In this situation, the expert system employs fuzzy logic, an approach that emulates human reasoning. With fuzzy logic the rules of inference are approximate rather than exact.

LIFT AND SEPARATE
Kemess' flotation cells accept the output of the ball mills and separate the minerals from the crushed rock.


The control system feeds the instrument readings and the rate at which the load is changing to fuzzy-logic sets that are designed to encapsulate the experience of the operators in running the mill. At an 1,800 psi load, the expert system might have a 10% belief that the load is high. At a 2,000 psi load, it might have a 70% belief. At a 2,500 psi load the system may be completely certain (100%) that the load is high. The level of confidence that the load is high becomes the driver for the expert system’s actions, in this case, reducing the feed. The fuzzy logic employed within the expert system works just like a human operator by determining the magnitude of the response based on the confidence level in the original assumption.

Implementation and Tuning
When the coding was completed, Minnovex engineers brought the expert system back to the Kemess mine, installed it on a PC, and began the coarse tuning process. At first, they ran the expert system connected to the DCS in an advisory mode while operators and supervisors viewed and commented on its responses to the changing mill conditions.

The initial version required relatively few changes. In only three days everyone was happy with its performance and the first line was put under its control while operators continued to closely monitor its decisions.

After two more days, the second line was put under control of the MET expert system and, after another day of monitoring, the MET expert was allowed to control both lines.

A key to the fast implementation was the way that Minnovex obtained input from the operators and explained how the system was simply implementing decisions that they would have made on their own. The operators bought into the expert system so they rarely interrupt its operation.

DAILY GRIND

Semi autogenous grinding (SAG) mills grind rock from 6 inches down to ½ in.

With the mill running under the control of the expert system, we noticed significant increases in throughput almost immediately. The main difference is that the expert system implements the control strategy on a much more consistent basis. It monitors instrument readings continually and adjusts operating parameters every couple of minutes, avoiding drift and keeping the mill running at a heavy load. The expert system can also monitor many more points simultaneously and reacts to changes much faster than an operator, which helps to avoid upsets that sometimes caused downtime in the past. For example, if the load on the SAG mill increases too much, the expert system will quickly decrease the density and feed to bring conditions back into line.

Extra Revenues Realized
When Northgate first put the lines under the control of the expert system, operators kept a watch on the system and made notes on areas that might be improved. Minnovex’s engineers came back a few weeks later and spent several days in a fine-tuning process that provided even further throughput gains. Northgate has since taken over administration of the system and it has remained stable and easy to maintain. Another benefit of this whole effort has been that Northgate’s operators are now more knowledgeable about controlling mill processes and better prepared to help drive future improvements.

Before Northgate installed the expert system, the company’s two mill lines were producing an average of 49,500 tons/day. The mills are now running at 51,500 to 52,000 tons/day, a nearly 5% improvement, which generates an extra $7 million in revenues per year. Based on its success Northgate is planning to use a similar systems to control flotation cells, which accept the output of the ball mills and separate the minerals from the crushed rock. Finally the company is in the process of installing new flotation cells using vision technology to monitor the size of the bubbles and speed of the froth. With the expert system controlling the process based on this and other process data, Northgate expects to achieve gains similar in magnitude to those that achieved on the mill lines.


  About the Author
Greg Rasmussen is Mill Superintendent at Kemess Mines in Vancouver, British Columbia, Canada (copper/gold). His mining experience streches across numerous minerals and several mines throughout British Columbia.
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