Predictive maintenance: how to prevent machine downtime before it happens
The problem with reactive maintenance
For years, industrial maintenance has followed a simple approach: intervene when something breaks. This model — known as corrective maintenance — has very high hidden costs: unplanned production downtime, emergency labour, spare parts purchased urgently.
Industry data estimates that one hour of downtime on an average production line costs between €5,000 and €50,000, depending on the sector.
What is predictive maintenance
Predictive maintenance uses data collected in real time — vibrations, temperature, electrical absorption, operating hours — to predict when a component is about to fail, intervening before it happens.
This approach should not be confused with calendar-based preventive maintenance (which involves scheduled replacements regardless of the actual state of the component): predictive maintenance is more precise and generates less waste.
Measurable advantages
\- Reduction of unplanned downtime by up to 80% in well-monitored plants
\- Increase in machine lifespan by 20–40%
\- Reduction of maintenance costs by 10–25% compared to preventive maintenance
\- Better planning of technical resources and spare parts
How to implement it
A predictive maintenance programme typically develops in three phases:
- Initial assessment: analysis of plant condition, identification of critical points, definition of parameters to monitor
- Instrumentation installation: IoT sensors, data acquisition systems, connection to the monitoring platform
- Intervention plan: definition of alarm thresholds, intervention protocols, technical staff training
The role of the technical partner
Implementing such a programme requires both plant engineering skills and data analysis capabilities. VF Group supports companies in the assessment phase and in the execution of planned maintenance interventions, providing specialised technical teams with experience in complex production environments.Z