Predictive maintenance
Optimise maintenance processes and reduce costs
When machines and systems require maintenance, this often results in long downtimes and high costs. However, regular maintenance is important to avoid expensive repairs and unplanned downtime. The problem is that most companies work with fixed maintenance schedules. Here, the work is carried out at fixed intervals and is little or not at all adapted to the actual maintenance requirements of the machines. As a result, a lot of superfluous maintenance work is carried out. This results in unnecessary costs due to downtime and labour costs. The solution: predictive maintenance - demand-orientated maintenance planning based on machine learning, artificial intelligence and smart tools.
What is predictive maintenance and how does it work?
Predictive maintenance refers to the forward-looking planning of maintenance measures. It is based on comprehensive data analyses that evaluate the machine and system status in real time. At the same time, smart tools, artificial intelligence and the like calculate the optimum maintenance time based on prediction models. This reduces unnecessary downtime, saves costs and supports the longevity of the systems. We would be happy to support you in implementing predictive maintenance with AI in your company - for example with the integration of the ruhlamat MachineHub.
Predictive maintenance at a glance

Predictive maintenance - your benefits
Thanks to real-time monitoring and analysis, failures can be prevented before they occur. This reduces downtimes and improves the overall availability of the systems.
Thanks to predictive maintenance, companies can plan maintenance work more individually. This saves time and money because maintenance is only carried out when it is actually required.
Demand-orientated maintenance planning reduces the risk of system problems. At the same time, it supports the longevity of the machines and ultimately increases investment security.
As maintenance work is only carried out when it is actually necessary, unnecessary downtimes and work assignments are avoided. This reduces maintenance costs and prevents expensive emergency repairs and unplanned downtime.
Permanent real-time monitoring also uncovers potential safety risks. This helps to prevent accidents and breakdowns. Employees and systems are better protected. Compliance with safety standards is fully automated.
By recognising potential system problems before they arise, predictive maintenance also ensures the consistent quality of production processes. This reduces reworking costs and increases customer satisfaction.
FAQs Predictive Maintenance
What kind of data is needed for predictive maintenance?
Various types of data are used for predictive maintenance, including sensor data, operating data, maintenance histories and external data such as room temperature and humidity. This data is used to train models that can predict future maintenance needs.
How accurate are Predictive Maintenance's predictions?
The accuracy of predictions depends on various factors, including the quality of the data, the complexity of the equipment and the effectiveness of the models used. However, very accurate predictions can be achieved through continuous training and improvement.
How can my company benefit from predictive maintenance?
By switching to predictive maintenance, your company can not only increase your maintenance efficiency, but also improve your competitiveness by reducing downtime, lowering costs and increasing plant availability.
Get in touch with us
For more information about our predictive maintenance solutions and how they can support your business, please contact us for a personalized consultation.
