What is predictive maintenance and how does it differ from preventive maintenance?

Preventive maintenance services a machine on a fixed schedule, whether it needs it or not. Predictive maintenance uses the equipment’s real data, such as vibration, temperature or consumption, and models that detect deviations to anticipate problems before they impact production. You intervene when the data says so, not by date.

What data is needed for AI-based predictive maintenance?

The starting point is the data your plant already generates: sensor signals, operating history and records of stoppages or failures. Predictive models and the early warning system are built on that base. Each project starts by reviewing which data exists and which is worth starting to capture.

Does it work with older machines that have no sensors?

Yes. When a machine does not generate data on its own, it can be fitted with sensors and connected to the plant data platform. Industrial connectivity and interoperability is one of Captia’s working areas, so a project can cover everything from data capture to the alert itself.

Where does Captia offer predictive maintenance?

Captia Technology is based in Xàtiva (Ronda Séquia de Meses, 18, 46800) and works with industrial plants in Xàtiva, La Costera, València and across the Comunitat Valenciana. Being nearby makes plant visits easier during the analysis phase and system rollout.

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Predictive Maintenance and Early Alerts

Predictive models and early warning systems to anticipate problems before they impact production. The models watch equipment signals and raise an alert when behaviour deviates from normal, leaving margin to plan the intervention.

AI-based predictive maintenance and early alerts

AI-based predictive maintenance uses the data your equipment already generates to anticipate problems before they become unplanned downtime. Machines rarely fail without warning: a degrading bearing changes its vibration signature weeks in advance, a motor losing efficiency draws more current for the same work, a leaking hydraulic circuit takes longer to build pressure. Predictive models learn each machine's normal behaviour across its operating regimes and flag sustained deviations, turning those weak signals into early alerts with enough margin to plan the intervention.

The shift is from calendar-based preventive maintenance, which services equipment at fixed intervals whether needed or not, to condition-based decisions driven by real signals: vibration, temperature, energy consumption, pressure and the plant's own maintenance history. Alerts are qualified with production context to separate genuine deterioration from noise, and they can trigger actions through automatic rules or be explored with operational analytics. Projects start small: an analysis of critical equipment and available data, a baseline for one or two machines, then progressive rollout. The full approach is covered in our guide on industrial predictive maintenance.

How it connects to the system

Captia AI is a capability of Captia Technology. This solution relies on data Connect integrates and priorities Consulting defines.

Key concepts

AI-based predictive maintenance in Valencia and the Comunitat Valenciana

Captia Technology, based in Xàtiva, builds predictive maintenance systems for industrial plants in Xàtiva, La Costera, Valencia and the wider Comunitat Valenciana. The approach relies on the plant’s own data: sensor signals, operating history and predictive models that raise early alerts to anticipate problems before they impact production.

The difference with traditional preventive or corrective maintenance is conceptual. Corrective maintenance acts once the failure has already happened, and preventive maintenance intervenes on a fixed schedule regardless of the equipment’s actual condition. Predictive maintenance listens to each machine’s data and flags when behaviour deviates from normal, so interventions are planned ahead and only when needed.

When machinery does not generate data on its own, the project can include fitting sensors and connecting the equipment, an area Captia also covers through its industrial connectivity solutions. Working close to the plants we serve makes on-site analysis and rollout support easier. Predictive maintenance is also one of the use cases we cover in depth on our page about AI for industrial companies in Valencia, alongside operational dashboards and supervised agents.

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Frequently asked questions

What is predictive maintenance and how does it differ from preventive maintenance?: Preventive maintenance services a machine on a fixed schedule, whether it needs it or not. Predictive maintenance uses the equipment’s real data, such as vibration, temperature or consumption, and models that detect deviations to anticipate problems before they impact production. You intervene when the data says so, not by date.
What data is needed for AI-based predictive maintenance?: The starting point is the data your plant already generates: sensor signals, operating history and records of stoppages or failures. Predictive models and the early warning system are built on that base. Each project starts by reviewing which data exists and which is worth starting to capture.
Does it work with older machines that have no sensors?: Yes. When a machine does not generate data on its own, it can be fitted with sensors and connected to the plant data platform. Industrial connectivity and interoperability is one of Captia’s working areas, so a project can cover everything from data capture to the alert itself.
Where does Captia offer predictive maintenance?: Captia Technology is based in Xàtiva (Ronda Séquia de Meses, 18, 46800) and works with industrial plants in Xàtiva, La Costera, València and across the Comunitat Valenciana. Being nearby makes plant visits easier during the analysis phase and system rollout.