The goal of the project was to enable predictive maintenance for cargo handling equipment using artificial intelligence. Veracell offered the know-how to utilize artificial intelligence-based life cycle models in predictive analytics. The model predicts which part of the machine is at risk of breaking. With this information, parts can be replaced in advance during periodic maintenance.
The project focused on the application of different forecast models and data preprocessing methods and finding the best modeling approach.
Survival (lifecycle) and random forest models were used in the modeling.
The results and the generated code serve as a basis for the further development of the models and the selection of the modeling approach.
The project focused on the application of different forecast models and data preprocessing methods to find the best modeling approach. Veracell implemented models that domain experts thought would be most useful, and supplemented Kalmar's data science team with specialized expertise in lifecycle modeling. The results and the generated code serve as a basis for further development and the selection of the best modeling approach.
We took advantage of Kalmar's data platform and quickly started developing the models. After years of data platform development, a lot of data processing had already been done before the project started.
"From Veracell we found a professional team that we had been looking for to advance our lifecycle modeling. The results of the project are promising and lead us towards a production solution.", Tomi Krogerus, Senior Manager of Analytics and AI
"From Veracell we found a professional team that we had been looking for to advance our lifecycle modeling. The results of the project are promising and lead us towards a production solution."
- Tomi Krogerus, Senior Manager of Analytics and AI
These glimpses are just the tip of the iceberg. Together, let's turn your "what-ifs" into "how-tos," shaping a future we dare to dream.
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