• ruhlaSmart Predictive Maintenance

    Predictive maintenance: for 
    efficient maintenance strategies

    Predictive maintenance

    Precise forecasts through advanced technologies

    Companies are faced with the challenge of optimizing their maintenance processes in order to minimize downtime and reduce costs. Predictive maintenance, supported by machine learning (ML), artificial intelligence (AI) and smart tools, offers an innovative solution to reduce downtime and increase the efficiency of maintenance activities. 

    Predictive maintenance refers to the forward-looking planning of maintenance measures based on data analysis and predictive models. Instead of relying on fixed maintenance schedules, which are often inefficient, predictive maintenance enables needs-based maintenance based on the actual condition of the machines or systems. With ruhlamat MachineHub, you can plan your machine maintenance proactively and smartly.

    Predictive maintenance at a glance

    Predictive maintenance at a glance

    Predictive maintenance - your benefits

    System Availability
    Increased system availability

    By detecting potential failures at an early stage, companies can reduce unplanned downtimes and improve the overall availability of their systems.

    Optimized Maintenance
    Optimized maintenance planning

    Predictive maintenance enables companies to plan maintenance activities better and use resources more efficiently by carrying out maintenance work exactly when it is actually needed.

    Extended service life of systems

    Preventive maintenance allows potential problems to be rectified in good time, which leads to a longer service life of the systems and thus increases investment security in the long term.

    Cost savings
    Reduced maintenance costs

    By carrying out maintenance work in a more targeted and efficient manner, companies can reduce maintenance and repair costs as fewer unplanned breakdowns occur and expensive emergency repairs can be avoided.

    Quality Standars
    Increasing safety

    Early detection of potential safety risks helps to prevent accidents and breakdowns, which protects both employees and equipment and supports compliance with safety standards.

    Improving product quality

    By continuously monitoring and optimizing equipment, companies can stabilize production processes and increase the quality of their products, which in turn 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.

    Richard Stegmann

    Manager Digital Solutions
    Richard Stegmann