Newmont expands predictive maintenance
Is further integrating Dingo PM solutions into global mines Metal Tech News – December 9, 2020
Last updated 12/8/2020 at 3:54pm
Newmont Corp., the world's largest gold mining company, has forged a partnership with Dingo, the global leader in predictive maintenance, to ensure the optimal health of Newmont's fleet of heavy equipment without putting equipment out of commission for time consuming and often unnecessary preventative maintenance checks.
Newmont is among the many global mining companies that are increasingly turning to predictive maintenance devices and software to track the health of equipment and schedule maintenance and repairs at ideal times for both the equipment and the operation.
"Reactive maintenance costs enterprises billions each year in lost production. The ultimate goal is not to replace machines or parts too early but service them at the right time," Vankata Naveen, disruptive tech analyst at GlobalData, explained earlier this year. "This can be done optimally using AI-powered predictive maintenance leading to reduced downtime, extended equipment life, improved safety and increased return on investment."
Australia-based Dingo leverages a unique blend of award-winning predictive maintenance technology, human expertise, and a global equipment database to provide the insights and decision-support to keep equipment operating in peak condition.
Dingo predictive maintenance solutions currently manages the health of more than US$13 billion worth of heavy equipment, a sum that is expected to increase as it works even closer with Newmont.
A global partnership announced by Dingo and Newmont on Dec. 8 further cements an already well-established relationship that has delivered significant benefits by improving asset health and availability, reducing risk, and reducing costs by extending the life of components.
"We're proud to expand our longstanding relationship with Newmont," said Dingo Executive Chairman Paul Higgins. "Our software, coupled with our services, provide its global operations with increased visibility into the health and performance of equipment, which helps Newmont identify opportunities for continuous improvement and increase operational efficiency systemwide."
Under this renewed partnership, Newmont will expand the use of Trakka, an award-winning predictive analytics solution developed by Dingo that utilizes artificial intelligence and machine learning to predict impending equipment failures, allowing companies to proactively perform corrective maintenance actions that minimize downtime and optimize the life of heavy equipment.
Trakka will be used to manage the workflow generated from Newmont's operations support hubs in Perth, Western Australia, and Denver, Colorado, which will provide continuous support to seven connected mining sites and hundreds of users.
"With Dingo's Trakka platform, Newmont will have a single source of truth to inform its predictive maintenance programs across the entire organization," said Jason Hill, senior director operations support hubs, Newmont.
Newmont's asset health analysts use Trakka to view and evaluate condition monitoring data from various sources, including onboard machine health data, operational data, fluid analysis, visual inspections, and work history. This predictive analysis helps identify the corrective actions required to keep equipment running in optimal condition. The recommendations from Trakka flow directly into Newmont's work management process through its integration with ERP (enterprise resource planning) software.
This integration is expected to streamline and standardize Newmont's global predictive maintenance processes, tools, and services worldwide. The global gold miner said this centralized view will accelerate the adoption of consistent maintenance strategies, helping reduce costs and mitigate risk, while creating safer working conditions.
"Trakka will enable our people to tap into the power of data to drive continuous improvements," said Hill. "The common platform allows us to identify best practices and detect emerging issues. Taking the appropriate action, in either case, is critical to continuously improving our business. We look forward to working closely with Dingo to transform how we approach maintenance in support of maximizing production at the lowest possible cost."