MINE MAINTENANCE
A hard-rock mine in North America recently trialled the new Nexsys lip system on a Komatsu P & H ® 4100XPC rope shovel, with the results proving interesting reading.
Previously the mine ran the ESCO Whisler Plus system with great success over conventional Whisler-style lip systems but it was on the lookout for machine upgrades to improve its operation.
The Nexsys system operated for 15 months before requiring a lip rebuild compared with 10 months for the Whisler Plus system. In addition, the total time required for the adapter fit area rebuild was reduced from 225 hours to 31.5 hours – a sizeable 86 % improvement, the company claims.
Enhancing the asset management engine
RPMGlobal has been looking to help miners, contractors and heavy original equipment manufacturers( OEMs) drive better maintenance outcomes since 2002: the year it released AMT.
Now in its 24th year of existence, users are benefitting from the latest update, AMT 9, which, RPM says, introduces powerful new features including AI-generated insights, a high-performance reporting environment and an extensive list of system-wide enhancements that help teams reduce costs,
increase equipment availability and make smarter decisions faster.
AMT is built around RPM’ s proprietary Dynamic Life Cycle Costing( DLCC) engine, which automatically forecasts the future expenses, equipment downtime, workforce requirements and parts consumption for every asset and component. With AMT 9, this foundation becomes even smarter, more accessible and more scalable, according to the company.
One of the most significant advancements is AMT Insights, an in-built virtual consultant that uses the power of AI to continuously monitor AMT data and present incisive intelligence, generating practical, high-impact recommendations that deliver tangible value.
The company told IM:“ The core DLCC engine in AMT 9 … has been strengthened by the new AI-driven tools we have released. The algorithm behind DLCC remains the same; a deterministic, engineering-driven cost model based on component life assumptions, maintenance strategies and expected operating patterns. What the AI features do is summarise the DLCC findings in an easy-to-consume way.”
For example, AMT Insights now analyses historical behaviour, detects DLCC trends, flags data inconsistencies and highlights emerging risk patterns that would normally take analysts hours or days to uncover manually, the company explains.“ Rather than redesigning DLCC, we’ ve‘ embedded a consultant’ that reviews the results, finds items to address and recommends ways to deliver real value,” it added.
AMT Insights can also automatically highlight cost-variance patterns and their future impact.“ For example, on an engine task for a given asset, it identified recurring overruns and projected a $ 38,000 variance for the next cycle,” the company said.“ On a transmission task for the same model, it flagged an unusual 91 % parts overrun and then highlighted, collectively, a potential $ 4.8 million future exposure.
“ Instead of just reporting numbers, it points planners to where the real issues are, so they can adjust scopes, pricing, or strategies before the next rebuild.”
AMT 9 also makes reporting faster and easier with a new high-performance Data Mart to let teams run detailed reports and build dashboards, without affecting day-today system performance. This is, RPM says, especially helpful for larger organisations, or those using AMT across multiple sites, where speed and stability matter most. The latest version also includes integration with a major OEM’ s service option system, giving its equipment dealers instant access to the latest approved service data. This live connection streamlines budgeting, quoting and maintenance