Case Study

UReason Supports Damen In First Steps Towards Predictive Maintenance

2 min. read

UReason’s APM software and Balluff’s CMTK-hardware help Damen translate predictive maintenance project into practice.
UReason’s APM Studio solution offers advanced predictive maintenance methods which give you accurate insight and predictions on how your assets are performing. Damen Shipyards is now able to put their predictive maintenance testing efforts into practice by rolling out their PdM solution onto the first ship.

 

Damen shipyard

The Situation

Damen Shipyards is an international shipyard group, offering maritime solutions, through design, shipbuilding, ship repair and related services in over 35 shipyards in 5 continents. The international maritime solutions provider delivers over 175 ships yearly with a turnover of 2.5 billion Euros in 2021. Damen provides high-value services to their ships with their Triton and DMMS platforms, which offers the owners and crew insights into onboard sensor data, to optimize operational performance.

The company delivers fuel usage, safety, sustainability and efficiency, maintenance information through their platforms based on sensor data. Damen wanted to implement predictive maintenance instead of real-time condition monitoring by using their sensor data to more accurately and proactively using AI.

The Challenge

Before the project was part of the Innovation program by TechnoHub  called Smart Metrology & Manufacturing, Damen already used the sensor data onboard to deliver value through real-time condition monitoring. However, maintenance was still done based on maintenance intervals, running times or real-time asset condition. Even real-time condition monitoring only offers a certain amount of certainty, where unforeseen and inexplicable alarms or malfunctions can take place. Damen wanted to use their onboard sensor data to work towards ‘predictive maintenance’ using Artificial Intelligence.

The Solution

UReason offered APM Studio to support Damen together with Balluff’s Condition Based Monitoring Toolkit-hardware, this enabled Damen to:

  • Simulate a part of the system with critical components in a controlled environment, showing the effects of small imbalances in the propeller-shaft which causes vibrations in the data which the algorithm can now detect to train the model.
  • Roll out a newly trained algorithm on board of the first ship, assessing small deviations in the data provided by cooling water pumps.
  • Run real-time analysis of the root causes of the malfunctions or alarms.
  • Create dashboards & insights that can be used to predict maintenance and failure using Big Data analytics and AI.
APM Studio Dashboard of Advanced alarm management
Using APM Studio, Damen was able to analyse new data, train new models and start the first pilot onboard a vessel

The Benefits

The benefits of Damen were realised in different fields:

  • Reduction of specialized personnel onboard of the vessels, which saves costs of staff and travel. Increase of reliability and efficiency of the personnel’s maintenance activities.
  • Reduction of maintenance costs.
  • Exploration of the possibility to offer more value to their customers with smart use of the data on their vessels.
  • Opportunities to expand their AI-models and predict deviations in the data of assets.

Learn More About This Solution

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