RAMEN project makes predictive maintenance and AR accessible to Europe’s manufacturing companies

Predictive maintenance, paired with Augmented Reality will make tomorrow’s manufacturing more efficient, reliable, and intuitive. The Ramen project, Resilient Industrial Platform for the Advanced Visualisation of Predictive Maintenance, is one of EIT manufacturing’s 2020 activities. The project, which is run by a consortium consisting of LMS, Biba, Whirlpool and Comau, aims at bringing a new advanced software solution for machine monitoring and predictive maintenance to the market.

“Predictive Maintenance and Augmented Reality are some of the ingredients which will help Europe’s industry boost its competitiveness. These new technologies will help companies achieve a more efficient use of resources, as well as help plan and optimize their production and maintenance activities. Machine failures, causing production downtime, can be costly and jeopardize customer deliveries. We aim at introducing this Industry 4.0 technology package to Europe’s vast array of manufacturing companies”, said project lead Dr. Kosmas ALEXOPOULOS at the Laboratory for Manufacturing Systems & Automation LMS in Greece.

What makes RAMEN different from other similar solutions? Thanks to Augmented Reality, RAMEN will make predictive maintenance intuitive and easy to comprehend for different stakeholders in the manufacturing processes. User friendly interfaces will enable shop floor staff to take immediate action. The software package will provide a combination of intuitive visual display components for machine learning, analytics and predictive maintenance analytics.

“Several platforms are already existing, but our goal has been to develop a generic module that connect with many interfaces. The solution should be easy to plug-in to any industrial IoT platform. Also, with Comau as project business owner, we have a strong understanding of the existing market and needs as well as a rich potential customer network”, said Kosmas ALEXOPOULOS.

What are the next steps? So far, the project team has defined requirements, and concluded the overall architecture. User needs and expectations have been detailed together with Whirlpool, and currently the RAMEN solution is being developed. A first version for validation and testing is expected to be ready in autumn this year.

The plan is that the results will be integrated as add-on modules into Comau’s existing Industrial Internet of Things platform.

Upon completion, the new solution is expected to significantly improve operational excellence through measurable KPIs such as:

  • Improve Overall Equipment Effectiveness up to 20%
  • Reduce Mean Time Between Failure to between 20% and 30%
  • Reduce Total Cost of Maintenance between 15% and 25%

RAMEN EIT Manufacturing project Consortium:

LMS as project lead and AR solution provider

Biba as predictive maintenance solution provider

Comau as Business Owner

Whirlpool as end-user