Tag Archives: condition monitoring

McLanahan helps customers improve maintenance programs with new condition monitoring package

McLanahan has developed a condition monitoring program to help customers keep an eye on the health of their machines.

McLanahan developed the condition monitoring package for three primary reasons: to allow customers to understand the health of their machine, to allow McLanahan technicians the ability to dial into the machine remotely and to pass any data back to the McLanahan engineering team to improve future machine designs.

“It allows us to better understand the condition of the machine out in the field so that we can better service our clients in terms of purchasing spare parts or scheduling maintenance on the machine,” Daniel Fairwebster, Electrical Design Manager, explained.

“Condition monitoring is typically a slow-moving animal, so we’re looking at trends over a long period of time to actually see how the machine is performing, but because it’s a real-time operating system, we do have the data immediately, so if there is something that happens unexpectedly, we do get that data and can generate a report as it happens.”

The condition monitoring program is a modular package that consists of sensors strategically placed around the machine. These sensors are connected to a remote data communication device that sends the data back to McLanahan. From there, McLanahan technicians interpret the data and share it with the customers to improve their maintenance programs.

“Customers can then take their maintenance strategy from planning just based on a calendar event to actually determining whether the machine does require some form of maintenance,” Fairwebster said. “They can potentially push out maintenance windows or they could bring them forward, depending on the condition of the machine. That can help reduce unplanned downtime and the like.”

The condition monitoring package can be added on any existing machine or installed as part of a new build, according to McLanahan. It can be tailored to fit any size operation and to monitor a variety of machine component conditions, including temperature, vibration, pressure and more.

“The McLanahan condition monitoring package can be installed on the full suite of McLanahan equipment, from the smallest machine to the largest machine,” Fairwebster said. “We can offer a machine with a basic level of package, which a basic level of instrumentation, and we can scale it up accordingly as required.”

He concluded: “The McLanahan condition monitoring is our commitment to our customers that we are supporting them to reliably operate our equipment, and we’re utilising that to improve our machines in the future.”

AspenTech Mtell Agents getting ahead of the mine maintenance game

AspenTech is looking to turn condition monitoring procedures in the minerals processing plant on their head by providing prescriptive maintenance tools powered by machine learning that offer the earliest possible issue detection along with the required context to allow operators to act.

“After more than a decade of working on Mtell, we understand how to slot into an operation to make sure our data is clear, prescriptive and acted on,” Mike Brooks, Global Director of APM Solutions at AspenTech told IM recently.

Aspen Mtell® has been a gamechanger for industries such as metals and mining, according to the company, performing prescriptive maintenance by forecasting degradation and equipment failures, alerting staff in advance of when a failure could occur, identifying potential causes and the scope of any failure, and providing advice on the corrective action to avoid or mitigate the impending failure.

This is leading to increased operational efficiency, resulting in improved energy efficiency and reduced emissions, according to the company.

Unlike other mining-related predictive maintenance proponents, AspenTech and Aspen Mtell have been using machine learning for over a decade, using the benefits of this technology to improve on the condition monitoring and firefighting maintenance procedures in place at industrial sites.

“By obtaining sufficient domain knowledge and packaging it into a solution, we have created a product that is able to detect patterns in the data, track any anomalies and contextualise these anomalies on the basis of past performance and previous incidents,” Brooks explained.

This process involves detecting failures, “hidden failures” (spikes or changes in behaviour not associated with an event) and when an asset is offline from past operating data and contextualising this within what is considered ‘normal’ operating conditions. From this, data analysts create “Failure Agents” and “Anomaly Agents” to spot potential failures and watch for changes in normal operating behaviour.

Once these Agents have been trained from historical data, they are deployed to monitor live equipment feeds with all deviations labelled as anomalies and detected by the appropriate Agent.

If an anomaly does not match the signature of a deployed Failure Agent, the anomaly triggers an alert requesting an inspection to determine the cause. The results of the inspection will categorise the anomaly as either a new variation of “normal” or a new never-before-seen failure pattern.

If it is the former, the Anomaly Agent will be updated with this new information to make sure no future false alerts with the same signature occur. If categorised as a new failure, a new Failure Agent will be deployed to allow for earlier detection in the future.

The more operating data the Aspen Mtell platform ingests, the more accurate the alert system becomes and the more context the solution can provide operators. Brooks said around a year’s worth of data often proves enough to know what ‘normal’ looks like while ensuring false alerts are kept to a minimum.

In some instances, Aspen Mtell has managed to get ahead of a potential failure on certain components by 4-6 months, allowing maintenance personnel to strategically schedule maintenance procedures and reduce unplanned downtime, according to Brooks.

“Not only are we able to identify the root cause and failure mode with alerts, but we can also often provide details of exactly what is needed to fix it based on past experience,” he said. Such information is particularly useful in an industry like mining, which has an ageing employee demographic that will, in the future, need to be replaced with a new generation of personnel.

“This is all part of our vision of the ‘Self-Optimizing Plant’,” Brooks said.

The Self-Optimizing Plant, as AspenTech puts it, is a self-adapting, self-learning and self-sustaining set of software technologies that work together to anticipate future conditions and act accordingly, adjusting operations within the context of the enterprise. The plant does this through pervasive real-time access to data and information, combining engineering fundamentals and artificial intelligence, and capturing and using knowledge to optimise across multiple levels, provide recommendations and automate actions securely in a closed feedback loop.

While the mining industry is still some way off adopting such a vision, AspenTech is getting nearer to convincing the sector of its potential future worth.

Brooks provided an example from a mining company with a worldwide presence that was having difficulty with frequent production interruptions caused by unexpected equipment failures as a case in point.

This company decided to deploy Aspen Mtell across a whole site to improve the reliability and availability of equipment, boost production yields and reduce maintenance costs.

On the secondary cone crusher at the operation in question, the Aspen Mtell application gave an extreme early warning and exposed a multi-dimensional pattern showing fast incremental changes, according to AspenTech. This provided the technicians with the required insights to detect the degradation issue and take the appropriate action, avoiding operational complications that can result in production and maintenance costs in the order of $100,000-500,000 per incident.

Similarly, Aspen Mtell was able to deliver a very early lead time and warnings of a bearing issues on the cone crusher, well in advance of the vibration detection system, allowing early action to service a minor issue before a catastrophic failure. This resulted in savings of around $75,000, according to AspenTech.

Equally, monitoring and catching potential bearing problems on conveyors allowed early replacement without the extended shutdowns associated with unplanned maintenance. Such avoidance is generally worth around $1-$1.5 million in operational costs, AspenTech says.

“The net results were that the company was able to better plan and schedule service and repairs on the mobile heavy haul trucks and the static ore processing, improving operators’ safety, extending component lifetimes, and increasing equipment availability besides improving on spare part/resource planning,” it said.

“The positive results encouraged the company to expand the Aspen Mtell application to other mining sites.”

Brooks says this specific company is one of a handful of miners realising the benefits of Aspen Mtell, with the mining sector fast becoming one of AspenTech’s key growth markets behind oil & gas.

And, with AspenTech having just completed the acquisition of Emerson’s OSI Inc and Geological Simulation Software business, there could be many more mining-related opportunities on the horizon.

Rexnord adds extra layer of condition monitoring to large gear drives

Rexnord Process & Motion Control (PMC) has introduced the latest addition to its line of Smart Condition Monitoring Systems, the new 1030, to continuously monitor large gear drives for oil quality, temperature and vibration, and improve uptime, cost efficiency and safety.

The 1030 can be fitted to nearly any gear drive with an oil port ¾ in (19 mm) or greater – typically on equipment with a 100 hp or larger motor, commonly used in mining, paper, cement, power and forestry industries.

“It delivers simple, robust 24/7 remote monitoring of critical assets to optimise total operating costs,” the company says.

Dan Plach, Rexnord PMC Director of Digital Solutions, said: “This is a comprehensive solution for customers with multiple brands of large gear drives, and can be used throughout your facility.”

Key benefits include:

  • Proven maintenance savings, enabling demand-based oil changes, reducing the need for scheduled maintenance;
  • Increased safety, minimising hands-on equipment inspections in challenging locations;
  • Improved uptime, avoiding asset failures through cost effective preventive maintenance; and
  • Easy integration, with programmable logic controllers (PLCs), allowing end users to quickly initiate remote monitoring via EtherNet/IP®, Modbus® TCP/IP or PROFINET® standards.

The Smart Condition Monitoring System has been engineered with proprietary algorithms to allow continuous monitoring, enabling maintenance managers to easily compare sensor data against models of healthy gear drive operating conditions, Rexnord explained. Abnormal conditions trigger automated alerts to onsite Andon lights, the PLC control system, and the Rexnord Connect Portal, delivering early warnings to clients that significantly improve uptime.

“The system puts data in context, enabling customers to focus on outcomes; teams know what action to take when and why,” it added.

Plach said: “The 1030 is the only universal large gear drive solution with oil quality, temperature and vibration monitoring capabilities. It tracks the humidity level as well as oil quality over time.”

The company added: “Customers know when to change oil or carry out preventive maintenance, better manage personnel and budget while avoiding unplanned downtime. Having the 1030 system in place may also reduce the number of spare units facilities need to keep on hand in case of breakages, freeing up much-needed space and budget, allowing customers to be more agile.”

Rexnord says it offers scalable options to fit specific applications, with future enhancements to Model 1030 including the addition of auxiliary sensors.

Progesys to bring Asystom predictive maintenance tech to Canada, Brazil mining sectors

Asystom and Progesys have announced an international partnership whereby Progesys will implement Asystom’s predictive maintenance technology across the mining, metal and oil and gas sectors in Canada and Brazil.

Progesys offers project management consultancy and transition-to-operations services to a vast international market. Its origins stem from the aluminium industry and now delve into energy, hydrocarbons, mining, infrastructure, transportation and more.

“Progesys effectively blend their management capabilities with field technical know-how to lead their clients’ operations to success,” the company said.

The Asystom solution monitors and analyses any rotating machine and helps to predict anomalies, wirelessly and non-intrusively, with a simple installation. Sensors communicate through a LoRa (Long Range network, and data is encrypted end-to-end. Asystom’s sensors monitor not only heat and vibration, but ultrasound too, meaning customers have the earliest possible alert of drift (before any damage has occurred). They run on standard batteries (so no need for additional wiring) for up to 10 years without intervention.

“An additional advantage of Long Range is that, due to its low frequency wireless transmission, the sensors can be positioned up to 1 km away from the LoRA gateway,” the company said. “Data is processed at the Edge on the sensors, and then the information is transferred and stored in the cloud through an encrypted secure network and then accessible through web applications.”

Andre Naccache, Managing Director at Asystom, said: “This a very positive next step in Asystom’s successful continued global expansion. Partnering with Progesys will enable us together to allow clients’ projects to achieve their fullest potential.”

Rami Faour, VP Business Development at Progesys, said: “Customers are looking for flexible solutions to meet the changing needs of their organisations. The Asystom solution allows industry customers to increase their production by up to 25%; this is due to the solution’s capabilities of predicting equipment failure and transmitting all data in real-time to any location of the client’s choosing. The information and alerts are then presented on a comprehensive dashboard, making it easy for our clients to see their data.”

talpasolutions to go ‘full throttle’ into new industries with latest investment

Essen-based technology company talpasolutions has raised €4.5 million ($5.5 million) in its latest round of financing to help further accelerate its expansion in key industries such as mining, construction and logistics.

“Thanks to the investment, we are going full throttle into new industries,” Sebastian-Friedrich Kowitz, Co-Founder and CEO of talpasolutions, said. “Over the coming months, we will continue to develop our platform and work on acquiring more international partners and customers. Our goal is to make the Internet of Things a reality in the global heavy industry as well.”

talpasolutions offers software that connects mobile heavy machinery, collects data, and translates machine data into concrete actionable insights for machine manufacturers and operators. It helps companies optimise their machine performance, reduce unplanned downtime and improve safety.

It has tied up with GHH to power the equipment maker’s inSiTE solution.

“talpasolutions enables heavy equipment owners and machine manufacturers in the heavy industry to leverage machine data that would otherwise have been lost,” Kowitz said. “Both the participation of the new investors and the renewed commitment of our existing investors demonstrate confidence that our chosen path is the right one.”

GHH sheds light on underground mining equipment operation with inSiTE

GHH is looking to help mining and tunnelling companies digitise their operations with a new analytics solution that can be used on any brand of equipment.

GHH inSiTE, powered by talpasolutions, provides a digital performance and condition monitoring tool, as well as a baseline for the future of digitally optimised mining operations, the company says. It is used to gain operational safety and cost control without the complexity often associated with acquiring and analysing such data.

Product Manager, Dr Felix Straßburger, said smart management was the future of the industry allowing mining companies to increase their return on investment.

Together with a vast team of external experts, GHH has created a digital analytics platform solution that, it says, transparently depicts on-site operations.

The system receives input directly from machines on site. Location, payload, distances, consumption, exhaust gas values, temperatures and much more are recorded and relayed. While this data has long been held on many machines, a comprehensive consolidation, evaluation and presentation platform was not available, according to Straßburger.

This is where GHH inSiTE comes into play, the company says.

“The software is regarded as a powerful tool that is adaptable and scalable, and thus designed to be future-proof,” it said.

“The connection to common IT infrastructures is guaranteed. All components are connected to each other via the network.”

Receiving this data in close to real time at control rooms, operators have all machine information available to them via PC, tablet or smartphone.

“If something goes wrong, or a change of schedule is required, they can intervene immediately,” the company says.

Even before the market launch, GHH took a major customer on board in 2019 to put the solution through its paces. The results were so convincing that an order was placed in mid-2020, with the contract covering a considerable part of the plant and equipment – around 150 machines.

During trials, the customer was able to achieve fuel savings of 7% and an efficiency increase of 12% in the monitored sub-fleet alone, according to GHH.

Optimising mining operations with used oil analysis

To gain a competitive advantage, it is imperative to get the most out of your hydraulic fluid, Petro-Canada Lubricants’ Neil Buchanan* says.

It starts by selecting the right oil. This means not only using a high-performance hydraulic fluid, but choosing the correct viscosity for each pump and motor, as well as considering the temperature range the fluid must operate in.

For a mining operation, with the sheer range of equipment used – from 260 t haul trucks, to hydraulic shovels, front end loaders, right through to drills, bulldozers and cranes – and the tough conditions it is exposed to, there are a lot of individual components to consider and decisions to make; all the more reason to maximise the use of your fluid.

But it is not just about oil selection: what you do with the oil when the system is running can be equally important.

Running regular used oil analysis as part of a maintenance program can provide operators the opportunity to catch an impending failure before it becomes catastrophic. Unplanned downtime costs time and money; used oil analysis can help avoid it.

The basic principles

Used oil analysis enables operators to monitor and optimise the life of a system and its hydraulic fluid. Typically carried out in a simple three-stage process, used oil analysis involves taking a representative sample of the fluid, sending it to a qualified used oil analysis laboratory and then interpreting and acting on the recommendations of the results.

Most mines undertake used oil analysis, but, when incorporated into a reliability centred maintenance program, the process can enable lubricant technical service advisors and mine personnel to evaluate trends over time, which not only helps to get ahead of system failure but provides a basis for better informed maintenance decisions.

Monitoring key properties

Regularly monitoring the key properties within the hydraulic fluid can give an insight into hidden and potentially harmful contamination, invisible to the naked eye.

Viscosity, the fluid’s resistance to flow, is one basic property measured in used oil analysis. However, viscosity is a lagging indicator, proceeded by additive depletion and oxidation which increases the fluids acid number (AN). Acid number was previously referred to as total acid number (TAN).

Another property that should be regularly monitored is oxidation, which occurs when the fluid is exposed to high temperatures and air (oxygen) and is common in hydraulic systems. The rate of oxidation doubles for every 18°F increase from 150°F, which highlights the importance of hydraulic oil temperature to its life. The impact of oxidation is a darkening of the oil, an increase in viscosity and potential sludge, varnish and deposit formation.

Using the data

Perhaps the most important step – and the one that will give operators the greatest advantage – is to effectively manage and interpret the fluid data accrued from the analysis quickly to enable effective decision making. Digital diagnostics and customised asset management reporting are two of the tools used to secure rapid sample results. Utilising oil diagnostics keeps an operation one step ahead by using the latest technology to proactively track where maintenance is needed and predict where it will be needed in the future.

While used oil analysis is widespread among the mining industry, not every mine is using it to the full extent they could. Using oil analysis as a predictive tool can help operators ensure they get the maximum life possible from their hydraulic fluid and move away from time consuming, reactive maintenance.

*Neil Buchanan is Senior Technical Services Advisor for Petro-Canada Lubricants, a HollyFrontier business

Leveraging condition monitoring for preventative maintenance strategies

As IM goes to press on its January 2021 issue, which includes its annual mine maintenance focus, McLanahan is stressing the importance of condition monitoring in the plant, which, it says, can lead to a well-oiled preventative maintenance plan that reduces equipment downtime.

Now more than ever, proactive maintenance and shutdown planning is crucial to maximising plant efficiency, McLanahan says. Maintaining uptime is paramount for achieving production outcomes and ensuring equipment will perform optimally.

At a bare minimum, equipment is now expected to integrate into the processing plant and, as such, must be able to interact both physically and digitally with up-stream and downstream nodes.

“The purpose of condition monitoring is to monitor equipment during operation to check its ‘health’,” McLanahan says. “Monitoring is scalable and customisable to each plant, process, and individual pieces of equipment, depending on the needs of the customer. Standard variables to monitor include vibration, temperature and power draw.”

Condition monitoring aims to reduce reactive maintenance and move towards preventative and predictive maintenance by setting base lines, identifying anomalies and producing performance trends. This process is faster, data driven and facilitates superior decision making, according to McLanahan.

Previously, equipment maintenance was designed around planned shutdown periods. Any data available was obtained and analysed manually. Alternatively, maintenance that fell outside of planned shutdowns was due to unexpected failures. As plants grow and the amount of equipment on site increases, it is very difficult to scale this manual process to meet the needs of today’s mining producers.

Packages that utilise off-the-shelf sensors and monitors help to set benchmarks for equipment monitoring standards. These devices deliver data to a local control box, which can forward the data to an often cloud-based database for viewing by the client and the equipment manufacturer.


The type of condition monitoring system chosen needs to be based upon identifying the needs of the plant or equipment, McLanahan says. By analysing the existing data available, goals can be developed to determine which variables should be measured.

Some of these operational goals include:

  • Decrease unplanned downtime;
  • Improve throughput;
  • Identify bottlenecks; and
  • Reduce maintenance costs.

The actual sensors are often quite basic and small. For example, the most popular vibration sensor type is an accelerometer, which, as the name implies, measure acceleration levels. Vibration sensors require mounting of the transducer to the vibrating item. This has the advantage of moving with the item, such as a bearing case, to measure absolute motion. With an accelerometer, how effectively it is mounted to the machine is critically important to ensure accurate measurement.

For wear measurement, the sensor could include a laser scan of the wear material surface from a fixed data point and compared with ‘as new’ baseline. Or, it could be a metal or optic fibre probe inserted into the wear liner that responds to an electronic pulse with the resistance value base on the probe length.

In either case, the signal can be captured for forwarding to a simple data logger through a fixed 24 V DC cable or a wireless signal. The complexity comes in using the correct software to ensure the raw data can be collected, correlated and presented in a format that is useful for the operator.


The goal of most producers is to increase production while lowering costs and avoiding downtime, McLanahan says. New technologies help producers meet these challenges by increasing operational efficiency, reducing costs, improving safety and extending the life of the asset.

As the system alerts operators to potential risks, equipment maintenance moves from a reactive to proactive strategy. When a plant experiences a breakdown, technical experts are required to solve the issue. “Manual intervention and prioritisation of this urgent job often results in a mismatch with the resources required, leading to cost and time issues,” the company says.

Predictive maintenance provides improved maintenance scheduling, with this maintenance able to be carried out at a convenient time so as not to interfere with production time. This allows for increased plant uptime and productivity.

Cost reductions surrounding maintenance, personnel and parts can also be achieved by using condition monitoring. When spare parts are ordered in advance, last minute increased freight charges are avoided, freight delays are reduced and the inventory management system is improved.

Improved operator safety is also a positive outcome for plants, not just for the safety of their site personnel but also through improvements to the equipment’s design. Site personnel can be removed from potentially hazardous areas of the plant, while engineers and service personnel can provide intelligent feedback on issues through having immediate access to equipment data. To decrease the amount of paperwork and manual data entry, these tasks can be integrated into the automatic data collection system to build tables, line charts and graphs of useable data.

Improved customer relations between the supplier and customer can also be achieved, as inconvenient breakdowns are avoided and communication improves between the two parties.


With the increasing number of equipment and process flows, the resulting amount of condition monitoring data will be enormous, yet this is also dependent on the frequency of data capture – capturing data every 10 seconds will produce more records than capturing data every 60 seconds.

When implementing a condition monitoring system, the downstream consequences need to be factored in. This includes the software, systems, processes and the people who analyse and interpret the data collected. There are always barriers to the adoption of new technology and, during the implementation process, the benefits of the system need to be highlighted, McLanahan says.

Sufficient training and an easy-to-use interface will help combat non-adopters and persuade a higher adoption rate of the new system, according to the company.

The data collected must also be distributed in a timely manner, with the analysis and learnings applied in a practical way. Plant operators must incorporate real-life maintenance scenarios with the automatic data collected to assist their operators to make safer, simpler and smarter cost-effective decisions. For example, analysing the thickness of wear liners will help to ensure the correct quantity are stored on site and how often they will need to be replaced.

Data security is also a consideration. As sites move from storing data on physical servers, often located away from the mine site, more of this is being stored on cloud-based systems. Data privacy and security are priorities for customers and must be considered in the implementation of any real-time data collection system.

Important factors to consider include:

  • Where will the data be stored – is it a local data centre, or is it a regional data centre in another time zone?
  • What is the backup/failover procedure?
  • What information is kept about my site and why?
  • How is the data transmitted?
  • Data transmitted is often unintelligible until the cloud dashboard software makes it so.

Preventative maintenance

Prevention is the best cure, and preventative maintenance is one of the main benefits of condition monitoring. The system serves as an early warning sign, which, if left unattended, can lead to a full-scale breakdown, resulting in a loss of production, unexpected costs and the replacement and removal of the offending equipment and parts.

Preventative maintenance strategies should also include an audit of assets to determine which spare parts (critical parts, wear parts or consumables) should be kept on site. By engaging with the OEM, further cost reductions can also be gained, McLanahan says. Used in conjunction with real-time machine health monitoring to determine preventive maintenance activities, high quality spare parts from the OEM give operators consistency and peace of mind.

Hastings Deering starts APM equipment journey with load and haul

Hastings Deering, a distributor of new, used and rental Caterpillar machinery and services, has launched an Asset Performance Management (APM) solution that, it says, bolsters the company’s strategy of helping customers use Cat equipment more productively.

Hastings Deering Asset Support Supervisor, Kurt Pidgeon, says the new APM solution complements the company’s traditional value proposition.

“Hastings Deering has always been very effective with analysing the reliability and availability of equipment,” he says. “However, customers buy machines for productivity, so we decided to start providing productivity solutions to complement existing traditional reliability analysis that we perform.”

Starting with load and haul machinery and expanding into other operational areas, the APM solution delivers a wide range of reports and recommendations to improve productivity, according to the company.

APM is concerned with how the entire mining circuit is performing as a system, rather than a single facet of an operation, or individual machine, the company says.

“There are many information systems that aim to bolster productivity, but APM is unique in providing insights into how the whole circuit is performing as a system and specific recommendations on how to improve,” Pidgeon explains. “We help customers achieve their maximum sustainable production rate circuit-by-circuit as the mine plan evolves, as opposed to looking at one machine at a time.”

He added: “Analysing machine productivity has been done well for many years. Key performance indicators like truck payload have been a strong area of focus, for example. What if trucks are not the constraining factor on site and it is the load tool instead?

“Using APM, we focus on the broader mining operation so that we can better understand exactly where the improvement opportunities are.”

APM analyses the data from an entire mining operation to provide in-depth insights that lead to productivity and efficiency boosts, according to the company.

For Pidgeon, this means finding areas of improvement that may otherwise go unnoticed.

“Mining clients receive insights from the APM software via a team of specialists here,” he explains. “That leads to productivity improvements and efficiencies gained.”

Hastings Deering will soon expand the APM platform to other disciplines, such as drill and blast, with the aim of supporting the entire value chain of an operation.

“We’re about to start a module for the analysis for drill and blast processes,” Pidgeon says. “Further to this, we are developing analytical tools for each of the processes in mining.

“This will also include wash plant and material handling aspects to properly understand how one part of the value chain affects the performance of another. You need the complete picture to find the weakest link in that whole value chain.”

Remote operations have become critical to sustain mine operations this year in response to the restrictions enforced by the COVID-19 pandemic, and Hastings Deering has developed the APM solution to enable miners to analyse performance remotely when required.

“Remote management of mining is well accepted now,” Pidgeon says. “Working remotely in all facets of productivity monitoring is no different.

“It certainly enables clients to review site operations without having to be there. Mining is an industry where people work and live in different locations. Minimising travel if we can do so is an important thing to do at this time.”

Outotec to provide proactive condition monitoring system for grinding mills

Outotec is looking to maximise grinding mill availability with a new modular system that provides all control functions required for the safe operation of equipment, and its associated lubrication systems, as well as continuous condition monitoring.

The Outotec Mill Control System allows for advanced condition monitoring strategies, including remote expert support, to ensure maximum mill availability, the company says.

It proactively detects anomalies using diagnostic data from IO-Link instruments to determine instrument health and detect installation problems before they cause downtime, according to the company.

Remote connectivity hardware is included as standard, enabling connection to Outotec’s Connected Services for remote diagnostics and support. Plant owners can also take advantage of Outotec’s cloud-based Asset Analytics service to gain valuable insights over the condition and performance of their assets, the company says.

“The system uses standard hardware and software components that are common across Outotec product lines for improved availability of support resources and spare parts and meets all relevant EU safety directives and other key international safety standards,” Outotec said.

IO-Link technology, an international standard according to IEC 61131-9, enables digitalisation and smart instruments by allowing for extended diagnosis of sensors and actuators, and the use of IO-Link instruments contributes to time and cost savings as the single interface means fewer input/output spares are required, according to the company.

In addition to increased mill availability, Outotec says it Mill Control System significantly reduces the commissioning time and cost associated with implementing similar systems, provides a shorter engineering lead time and superior installation quality thanks to “simplified wiring and termination design” as well as standardised software and hardware modules; comes with reduced project risks as the complete solution is delivered under one contract; and ensures compliance and reduced risk with state-of-the-art safety-rated hardware.