August 18, 2025
Smart sensors take maintenance to the next level at site in Spain
Successful maintenance is built on preventing problems before they impact production. This thinking guides us at Quant, and it is now becoming reality at Cromogenia’s site in Barcelona. We have taken a major step toward predictive, data-driven maintenance by installing Schaeffler’s smart vibration sensors on critical production equipment.
Quant’s experts proposed the implementation of a predictive maintenance system for customers as a logical next step to improve reliability and prevent production disruptions, especially in light of previous equipment challenges.
“As part of the start of our collaboration with Cromogenia in late 2024, we saw an opportunity to develop the site’s maintenance practices. The customer had previously performed vibration measurements manually quarterly, so continuous and intelligent monitoring felt like a natural evolution. Now, step by step, we are moving toward a modern, data-driven solution,” says Andreas Ekstrand Larsson, Operational Excellence Engineer at Quant.
The sensors were installed on equipment such as motors, pumps, and fans, selected based on their critical role in production. The system is currently in “learning mode,” continuously collecting condition data from the machines.
“Already at this early stage, the sensors have detected deviations that have drawn attention from the maintenance team. The system sends automatic email alerts identifying the most probable cause, enabling faster and more accurate responses,” says Igor Marzolla, Operational Excellence Engineer at Quant Spain.
quantpredict brings intelligence and predictability to maintenance
During installation, we encountered some practical challenges, including ensuring optimal surface conditions for sensor attachment and maintaining reliable connectivity.
“One sensor was initially out of range, but Schaeffler’s new-generation gateway devices provided a much better signal range, and the issue was quickly resolved,” Larsson explains.
At the core of the solution is quantPredict, Quant’s predictive maintenance platform. It consolidates sensor data and leverages artificial intelligence to identify trends, predict failures, and guide targeted actions.
“quantPredict transforms raw data into clear, actionable recommendations. For our customers, it brings meaningful improvements in plant reliability. Larsson says.
The project is still in its early stages. During May, an additional 10 smart lubricators will be installed across two neighboring production sites. This will help build a more comprehensive solution that strengthens production continuity and supports long-term maintenance development.
Toward more sustainable, efficient, and predictable production
Predictive maintenance also plays a key role in supporting sustainability. By identifying issues early, corrective actions can be planned in line with production schedules. This reduces unplanned downtime, prevents unnecessary environmental impact, and extends equipment life.
“When we can foresee a failure, we can prepare and align maintenance with production. This brings cost savings for the customer, and more predictable work for us,” Marzolla says.
We believe that as the system evolves, its value will become even more tangible.
“The collaboration has started well, and we are very interested in the potential of this new technology. It has been exciting to see how real-time data increases transparency on equipment condition and helps us plan maintenance better. We look forward to discovering what more the system can offer as more data becomes available,” says Maintenance & Investment Director, Joan Carles Massachs, Cromogenia Spain.
This project is a strong example of how digital tools, expertise, and customer collaboration can transform maintenance from reactive to predictive, while creating real, measurable value in production.
