MINE MAINTENANCE
Again , the Global PerformanceIQ Hub can act as a catalyst for speeding up this transition , leveraging data from local sites on a global level . It will be the analysis and distribution of this data – plus case studies showing its effectiveness – that will lead to further adoption , according to Meyer .
“ You ' re currently getting very early indicators that a failure is likely to occur , and eventually we ' ll get to knowing that there ' s a possibility of failure before there are any physical indicators ,” he said . “ This will then lead to the ability to determine a series of events that have happened that would have a bearing on the health of the equipment and where this may lead without taking action .”
This is where AI models that are in development will come in and be able to predict failures based on historical datasets , Meyer says . He is confident these measures and projects will ensure FLSmidth stays at the forefront of the digital maintenance side of the business .
“ I think FLSmidth has probably the most comprehensive digital solutions of anyone in our space . We have the capability , both on the asset health and asset optimisation side – across the entire flow sheet – to carry out data-driven decision making for our customers . We also have the advanced monitoring and customisation capabilities , so whether it ' s sensing technology , condition monitoring systems , or other advanced solutions , we can make a positive difference for our customers .
“ We have design and engineering know how , deep mineralogy and mineral processing knowledge , and the digital tools to differentiate ourselves from everyone else on the market .”
Asset health data under one roof
Predictive failure analysis is making significant strides in the mobile equipment field , where the large number and uniformity of assets at mine sites provide a wealth of data for analysis . Dingo , initially established to provide fluid analysis , has been advancing its digital monitoring capabilities into this predictive realm for years , enabling mine sites and OEMs to gain an understanding of component conditions .
Damien Covey , VP , R & D in Engineering , says Dingo is able to capture almost all condition monitoring data to assess the condition of components – all of which is stored in its Trakka ® platform .
Trakka is a powerful , cloud-based predictive maintenance software system designed to house all of asset health data under one roof . The solution provides operations with the tools , insights and decision-support to run a best-inclass asset health program , according to the company .
“ Recently , Dingo has been expanding the
“ Trakka ’ s Asset Health Program and supporting solutions such as intelligence equips maintenance and mine managers with actionable insights by continuously monitoring equipment health and component performance ,” Tom Mulherin says
offering to include telemetry data in the form of event and alarm information as well as raw sensor trends ,” Covey says . “ This data type supplements and confirms potential abnormal conditions seen in other data types , such as thermography , visual inspections , preventative maintenance inspections , vibration or fluid analysis .”
Covey says Dingo ’ s customers are already benefitting from its data access APIs by automatically aggregating Trakka data alongside other third-party system data such as ERPs .
“ This reduces the time customers need to wrangle data for monthly reporting , enabling them to spend more time instead utilising this data to make decisions ,” he explained .
The recent launch of intelligence™ , powered by Trakka , has gone a step further , Tom Mulherin , Senior Product Manager for Dingo , says .
“ Trakka ’ s Asset Health Program and supporting solutions such as intelligence equips maintenance and mine managers with actionable insights by continuously monitoring equipment health and component performance ,” he added . Using advanced algorithms and a team of experienced maintenance and reliability experts , intelligence detects early warning signs of potential failures , ensuring issues are addressed before they lead to unplanned downtime , according to the company .
“ For example , mining companies using our solutions have reported a 15 % reduction in unplanned downtime by identifying wear trends in high-risk components such as hydraulic pumps or engine bearings ,” Mulherin says . “ intelligence then provides up-to-date visualisations through easy-to-use reports , enabling teams to schedule maintenance at the optimal time , minimising disruption to production schedules .”
Dingo says the integration of intelligence into a mine ’ s asset health programs can lead to more than just uptime improvements , allowing them to gain a proactive maintenance culture that aligns with production goals , reduces costs and enhances safety across operations .
The Trakka app is part of a suite of tools designed to help mine sites manage and maintain equipment health , with two distinct but
equally important functions : Insights and Inspect . Trakka Insights™ enables users to see equipment health at a glance , recommending actions and then tracking progress through resolution ; while Trakka Inspect™ allows technicians to perform equipment inspections and condition reporting from the field – all from a mobile device .
Mulherin explains : “ Trakka ’ s Asset Health Program is all about performing the right actions once , by rectifying the actual fault effects with the right tools and people at the right time . Trakka ’ s recommendations go from the least intrusive to more intrusive corrective actions based on condition health seen in the wealth of data captured . Fleets are maintained based on condition , meaning assets that are in normal condition can continue to operate , resulting in less unnecessary downtime compared to a strict time-based program .”
Asked by IM about the highlights of a recent Trakka update , Covey referred to the Asset Health Report that , he said , is proving to be eye-opening for many mine sites .
“ Sites are often given generic condition ratings from data sources that do not accurately reflect asset or component health ,” he said . “ This report shows the difference in Trakka ’ s statistically and expert set Alert Limits , compared to data sources .
“ By sifting through the noise and clearly presenting these insights Trakka offers reliability engineers and asset health analysts more time to investigate infrequent and critical issues .”
Mining companies are also using a new Benchmarking tool within Trakka , powered by intelligence , to compare their own mean time to repair ( MTTR ) numbers with similar operations , potentially allowing them to extend component life past OEM or budgeted recommendations . “ Increasing component life , whilst still changing based on condition , can generate millions of dollars in savings ,” Mulherin says . “ Extending component life is only recommended when fleets are operated safely and the
24 International Mining | JANUARY 2025