For decades, industry has managed the maintenance of its equipment in two ways: repairing it when something breaks down (corrective maintenance) or checking it regularly to prevent breakdowns (preventive maintenance). Both approaches have their logic, but neither answers one fundamental question: exactly when will this piece of equipment fail?
Predictive maintenance was developed precisely to answer that question. In recent years, its adoption across Spanish and European industry has continued to grow.
What is predictive maintenance?
Predictive maintenance is an advanced asset-management strategy based on continuously monitoring the condition of equipment in order to anticipate failures before they occur. Unlike corrective or preventive maintenance, it uses ongoing data analysis, IoT sensors and predictive models based on artificial intelligence.
In practical terms, sensors are installed on equipment to monitor variables such as temperature, vibration, electricity consumption and noise in real time. The data are analysed continuously and, when the system detects an anomaly that signals a potential failure, it raises an alert. The technician intervenes before the machine stops.
A company in Vallès Occidental began its transition to predictive maintenance by monitoring the vacuum motors in its central sterilisation system. Within three months, it detected vibration deviations that indicated wear in a main bearing. The planned preventive repair cost €300, compared with the €2,500 a complete breakdown would have cost.
How does it differ from preventive maintenance?
It is a common question. The key difference lies in the intervention criterion.
Preventive maintenance follows a fixed schedule, regardless of the equipment’s actual condition. It is carried out every X hours or every X months, whether there are signs of wear or not.
Predictive maintenance responds to the equipment’s actual condition. Interventions are not made according to a timetable, but when the data show that they are needed.
This has a very practical implication: predictive maintenance avoids both the unexpected stoppages associated with corrective maintenance and the unnecessary interventions that can result from preventive maintenance scheduled too frequently.
Predictive maintenance should be measured by its real impact on the factory: fewer unexpected failures, greater availability, lower maintenance costs and better planning.
What are its benefits for industrial companies?
The principal benefits of industrial predictive maintenance include maintenance-cost reductions of up to 25%, an extension of equipment life by 20%, and the fact that emergency repairs can be up to 15 times more expensive than planned interventions.
Fewer unplanned stoppages. If a fault is detected in time, the company can schedule the intervention and avoid the shutdown. If it is detected too late, the familiar additional costs and production losses arise.
Better planning of technical resources. Detecting wear patterns before they escalate into critical failures reduces spending on unnecessary spare parts, makes better use of technical staff time and lowers operational stress.
Greater worker safety. Equipment that fails unexpectedly can create hazardous situations. Anticipating the failure significantly reduces incidents on site.
Traceability and control. The most widely used indicators are MTBF (mean time between failures), MTTR (mean time to repair), asset availability and maintenance cost per asset. Effective predictive maintenance raises MTBF, lowers MTTR and reduces dependence on corrective maintenance.
Why are more and more companies adopting it?
Predictive maintenance has stopped being a distant promise and is becoming a tool that can increasingly be applied in real factories. In 2026, the change is not only that there are more sensors or more data, but that the technology is becoming more accessible, more connected and more useful for maintenance, engineering, production and digitalisation.
PwC found in 2025 that 43% of C-level executives in heavy industry and energy were already investing in predictive maintenance for equipment.
And the trend will not stop. The adoption of predictive maintenance will shift from a competitive advantage to a fundamental requirement for remaining relevant in the market. Organisations that fail to integrate these capabilities will face higher costs, less agility and a reduced ability to meet market demands.
Which industrial sectors are adopting it most?
The automotive sector, due to the complexity of its supply chains and high degree of automation, is making extensive use of predictive maintenance to guarantee just-in-time production. It is not alone: chemicals, food production, aerospace, energy and metal construction are all sectors where predictive maintenance is gaining ground rapidly.
What technical profile does a company need to implement it?
This is where many companies encounter their main obstacle. Predictive maintenance does not work through technology alone: it needs qualified technicians who can interpret data, diagnose anomalies and act accurately when the system raises an alert.
For this strategy to work, the maintenance technician must have real factory experience, knowledge of mechanics, electrical systems, pneumatics and hydraulics, and the ability to work with digital monitoring systems.
This is a profile that is increasingly in demand and, as we already know, increasingly difficult to find in the market.
At MetalBraga, we have the maintenance technicians your company needs
At MetalBraga, we have supplied industrial maintenance technicians to companies throughout Spain for many years. We understand the real requirements of the role and make sure that the technician joining your plant has the experience and certifications needed to contribute to your maintenance strategy from day one.
If your company is investing in predictive maintenance and needs the right technical team to implement it, contact us!