Rockwell Automation Announces DLG Group’s Computerized Maintenance Management System Deployment to Drive 10% Downtime Reduction

Danish agri-giant deploys Fiix® CMMS software to boost maintenance productivity, optimize inventory and develop best practices

Rockwell Automation, Inc., the world’s largest company dedicated to industrial automation and digital transformation, announced its collaboration with DLG Group, one of northern Europe’s leading manufacturers of agricultural feedstocks and agri-products, targeting reduced downtime with Fiix® Computerized Maintenance Management System (CMMS).

Using Fiix software, DLG Group is modernizing its maintenance processes for greater efficiency, lower downtime and improved inventory management. Within a month of moving to a digitized maintenance-management workflow, the company is already seeing improvements in the meantime between failure (MTBF). Within a year, the company expects to achieve a 10% reduction in downtime.

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“DLG Group’s deployment strategy has been a model of best practice and innovation,” said Katarina Hart, country sales director, Nordics, Rockwell Automation. “Using Fiix CMMS, DLG Group is on target to achieve improvements in efficiency that will more than pay for the investment in the new system.”

As well as boosting the efficiency of the maintenance teams, the new system is also enabling DLG Group to develop new maintenance best practices. Across teams, sites and a wide range of varied systems, the company is collecting data on common issues, fixes and data-driven optimizations. Knowledge is no longer siloed in different sites, and it is now easy to rapidly share best-practices and critical fixes companywide.

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“Our factory managers are already seeing a clear benefit in being able to manage and optimize their maintenance queues in real time,” said DLG’s Continuous Improvement (CI) engineer, Alex Rasksen. “It improves their time-to-resolution but also their cooperation with other functions, such as the production planners. This has had an immediate benefit. And in the long term, we plan to build on that expertise to move to a fully data-driven, predictive maintenance setup.”