Implementation of AI-models for Predictive Maintenance
Codellent
Category
Overview

AI-models developed
Re-training with MLOps implemented
Second response time
Challenge
The process of maintaining ships has always been a delicate balance. On one hand, protective coatings must be serviced to avoid costly failures and inefficiencies. On the other, taking a vessel out of service too early can mean unnecessary expense and lost revenue. Striking the right balance is especially complex at sea, where operating conditions vary constantly and the true state of coatings and equipment is often hidden beneath the surface. This is where predictive maintenance enters the picture.
Solution
In an industry where margins are competitive and downtime is costly, predictive maintenance transforms maintenance from a reactive cost into a strategic advantage. To improve the maintenance process Codellent helped Hempel scope, design and implement a Data & AI foundation containing near real-time import of data, domain data with measurements, automated AI-model flows, AI-model re-training and business system integrations.
The Result
The project has been a pioneer in the journey of more innovative service solutions helping optimize processes, improve quality in decisions and distributing advanced insights and knowledge.