Putting Information to Work
Mining operations could benefit greatly from data-driven decision making
By Steve Fiscor, Editor-in-Chief
In fact, experts say that only 5% of operations have implemented and harnessed the benefits of IoT. So, if a mine or plant has not yet connected to the data- driven world of decision making, don’t stress, it’s not alone. From a glass-halffull perspective, it means there is considerable room for improvement.
A great amount of financial benefit could be harvested without much effort. The industry is constantly reminded that the costs for sensors, equipment and software to implement IoT continue to decrease. There is, however, more to the program than simply installing and collecting data from a few more sensors.
Implementing IoT is both a technological feat and an organizational effort. If an organization has not been trained or does not see the value in data-driven decision making, then the effort will likely be wasted. The first steps could be as simple as monitoring a problematic bearing and knowing when it must be replaced. Seeing the benefits of avoiding catastrophic failure in a fresh light can lead to the programs taking off and the organization growing with them.
Advanced Process Control
Implementing IoT will have a great impact on maintenance practices and it will allow mines and mineral processing plants to integrate maintenance and process optimization. In other words, in addition to optimizing the key performance indicators (KPIs) for processing, the operation could combine maintenance KPIs with process KPIs for process control, explained Skage Hem, vice president for mining R&D, FLSmidth.
When operations discuss maintenance and process control they often prioritize one over the other. The brilliance of the IoT is that the two subjects can be balanced, said Greg Weaver, global product line director, digital solutions for FLSmidth. “If a mine is pushing a lot of product through its equipment, which is also inducing extra wear and potential damage, they could balance the tradeoff between increasing revenue through the extra input and the increasing maintenance costs due to wear and tear on the machine,” Weaver said. “Recognizing wear patterns and acting on the information, an operation can increase performance and optimize all maintenance and process strategies through the intelligent use of data.”
Using a crusher as an example, sensor data might indicate that the mantle has worn to a certain level. Acting on that information, the system could adjust the opening and the operation of the crusher to maintain the desired particle size even if the machine is somewhat worn. The system could also protect the crusher by adjusting the process parameters.
Implementing IoT affects three parameters: process optimization (quality and throughput), maintenance strategies and utility consumption. “That’s the beauty of data and analytics,” Weaver said. “There are so many variables that can come into play affecting all aspects of the equipment and the operation. With advanced sensing and data analytics, the mine’s needs can be balanced. At times, they need to meet quotas and push equipment harder. At other times, the operation may need to ease off. Maybe the ore grade changes and the process needs to be adjusted slightly. Understanding the data becomes an all-encompassing way of managing the plant.”
IoT will enable digitalization and data- driven decision making. The groups that implement this type of program will benefit from data-driven decision making, Hem explained. “Similarly, if a maintenance organization is not geared to take advantage of the information provided by these systems, they will not harvest the clear benefits,” Hem said. “For an organization to use and implement IoT, they must have a professional maintenance organization. One that not only understands the information, but acts on the information given. So, it’s not only a technology challenge, but also an organizational challenge. They must be trained to benefit from its use.”
One of FLSmidth’s customers, a copper mine in South America, was experiencing premature wear on their mill liners. “We installed an impact meter that measured the acoustics within the mill and then adjusted the speed and several other variables on the mills to optimize performance,” Weaver said. “Analyzing the data provided by IoT, we saw an increase in production by 8.75%. The program also lowered energy consumption by 8.7% and the number of critical impacts between the balls and the mill shell was reduced by 46.9%.” All those benefits (process improvement, decreased energy usage and prolonged equipment life) were accomplished through data analysis. “This could have been accomplished manually, but it would have been time consuming,” Weaver said. “The process control system factors those parameters into data ecosystems, adjusting speed, feed rates, etc. The mill itself had 25 to 30 parameters that were analyzed and adjusted for optimization. This is far superior to anything that could be done manually.”
Water has become an issue for many mines in Latin America and some are currently debating eventual waterless operations. In the future, that may be a distinct possibility. Until then, implementing IoT could be a way to optimize the amount of water the operation needs. It could bridge the gap to waterless processing.
Converting information into a digital format allows engineers to see and interpret the data differently. The integration of digital technologies into processes, or digitalization, will have a profound effect on productivity and availability in the mining industry, explained Roland Ehrl, vice president-minerals for Siemens. “It’s certainly an area that is currently ‘under development’ and five mining companies would explain the principles differently,” Ehrl said. “Mining operations, however, are most concerned with availability, followed by condition monitoring and beyond that to predictive maintenance.”
Most engineers are interested in gathering data from production processes and getting it into a proper format to make the best use of it. Data collection is easy, Ehrl explained, making the best use of it is another story.
Siemens’ Asset Health Management lays the foundation for enabling conveyor systems, mills and crushers to supply additional data. The analysis of this data provides mining operations with all the information needed to make well-informed, fact-based maintenance decisions — and to optimally plan maintenance and service measures in advance.
Siemens can provide mine operators with everything needed to effectively collect, analyze, visualize and share data — starting with a complete portfolio of sensors for all applications, along with smart products that set new benchmarks in precision and reliability, even under extreme conditions. With SIMATIC IT, data from the plant can be used for operational execution and enterprise resource planning (ERP). The company’s Manufacturing Execution System (MES) translates raw real-time manufacturing data into business performance indicators, providing transparency on performance metrics for better real-time business decisions.
“We have management information systems (software) that can provide very detailed information about what is happening in the process,” Ehrl said. “We are also able to supply complete MES systems for multiple connected plants. We can cover all the processes.”
The Minerals Automation Standard from Siemens is based on its SIMATIC PCS 7, an open, flexible and scalable distributed control system (DCS) designed to ensure highest productivity and reliability. With its integrated safety, industrial security and energy management concept, it combines all the requirements needed to protect humans, machinery and the environment — and paves the way to the digital enterprise. The integrated Advanced Process Library (APL) offers a great route for gaining higher operational and engineering efficiency.
“Digitalization is a topic that is starting to motivate the mining business,” Ehrl said. “The market is forming now. We are here to help form it and drive it. There are great opportunities for the mining business to make improvements.”
In the past, optimizing operations often meant cutting costs. Technology is opening new paths to establish benchmarks in productivity. The intelligent use of data provides another effective lever for increasing productivity and real time decision making.
Data-driven Decision Making
The ability to manage and interpret the data makes these process control systems much more powerful. With access to more data, machine learning and historical information, process control systems are becoming more stable and rugged. “The reason these programs are really starting to gain momentum now is because of the decreasing cost of the sensor packages,” Weaver said. “You see it everywhere. The radar systems for self-driving cars are reportedly dropping from $75,000 to $7,000. The sensor technology and sensors costs are so inexpensive at this point that engineers can instrument equipment that could not be economically justified in the past, increasing the ability to make data-driven decisions.”
With access to more data, engineers can better understand the interaction between equipment and processes than they had previously been able to do. “Many of the trivial, time-consuming decisions these specialists are currently making will be made automatically,” Hem said. “They will have additional time to focus on more complex problems. With many more data scenarios to work with, they will actually be able to do a better job.”
It’s estimated that 60% of maintenance outages are unplanned. These outages take the facility offline and production comes to a screeching halt. “Unplanned maintenance outages consume a lot of attention,” Weaver said. “They also increase the pressure on maintenance teams not to mention the costs. With the predictive aspect of IoT, they will know that a bearing or a liner is going to be a problem in a month or two. It takes those worries away.”
The maintenance organization transitions from fighting fires, moving from one crisis to another, to managing a more stable program, predicting and preventing unplanned shutdowns, Hem explained. “It starts with the basics and then develops step by step toward more sophisticated maintenance strategies, which are supported by digital technology. Part of this can be done without these systems, but these systems will ensure that it does get done,” Hem said.
“We are looking to partner with mining companies on a customized approach,” Weaver said. “Because of the inexperienced nature of the mining industry, we are taking a customized approach with each mine, where we look at the specific needs and how best to implement IoT at their operation. As FLSmidth is a full-flowsheet provider not only can we improve the performance of individual pieces of equipment, we can work across the flow sheet optimizing the benefits of IoT across the entire plant.”
FLSmidth can provide the sensor packages or we can assist with interpreting key operational data, Hem said. “If a mine does not have access to the operational data, the first step would be to install the technology and then develop maintenance strategies around it and keep it on a practical level,” Hem said. “Then we could begin to look at integrating data into process optimization decisions.
“There is enormous potential here. We have seen these technologies implemented in other industries. There is a 5% to 10% cost reduction just waiting to happen and these would be big numbers for the mining business. And, the cost to implement is not at all proportional to the savings.”
Over time most industries have experienced incremental improvements in productivity. A large part of the mining industry has seen its productivity decline due to decreasing ore grades. Implementing IoT, digitalization and data-driven decision making could reverse that trend.
Integrating Video Cameras and Expert Systems
Last year a white paper published on Skkynet.com described how the engineers at the San Cristobal mill used a DataHub to connect their DeltaV Professional Plus SCADA system to an SQL Server database in the corporate offices. Taking the project one step further, the engineers decided to connect their two SGS expert systems to DeltaV in a similar way. Located in the Potosi district of southwestern Bolivia, Minera San Cristobal is one of the largest silver-zinc-lead mining projects in the world.
Although the DeltaV system allows an operator to input setpoints and other values directly into the system, Mendizabal and his team wanted to apply an SGS Advanced Systems application to optimize two critical parts of the mineral refining process: grinding and flotation. Each expert system runs on a separate sever. To add to the challenge, the Flotation Expert System also requires real-time data input from two banks of 25 video cameras. These cameras monitor the size, speed, and other qualities of the bubbles as they lift the valuable mineral particles to the surface, where they can be skimmed off as foam. There is one bank of cameras for the zinc flotation circuit, and another for lead.
Each of these five systems-DeltaV, the Grinding Expert System, the Flotation Expert System, and the two camera systems- needed to be connected in real time. Fortunately, each system had an OPC server. What was needed was a way to bridge the OPC servers, aggregate their data streams, and tunnel the data across the network for the other systems. Based on his previous success using the DataHub, Mendizabal chose to apply it to this task. He already had a DataHub connected to the DeltaV system. So he just installed a DataHub on each of the SGS servers, and each of the camera system servers. Then he connected those four DataHubs to the main DataHub running on the DeltaV server.
“It didn’t take long at all to get the system configured,” Mendizabal said. “Since it is tunneling across the network, we avoided DCOM settings and networking issues entirely. The connection is completely secure and rock-solid.”
When the expert systems are switched on, the plant data flows from DeltaV to the Grinding Expert System and the Flotation Expert System. These systems continuously and intelligently adjust the values of the setpoints, and send them back in real-time to DeltaV, which passes them along to the relevant process. To make its calculations, the Flotation Expert System also takes into account the real-time data that is streaming in from the two Video Camera Systems.
“It is very important to know that when the expert system is controlling the plant we are trusting our production to the Data- Hub,” said Mendizabal. “We are very pleased with its performance, and highly recommend it for this kind of mission-critical work.”