Select one of our country-specific markets here:

English (USA)English (China)

The Impact of Predictive Maintenance on Your Business

Creating potential through the use of predictive maintenance

Predictive maintenance is one of the most popular application examples of artificial intelligence in the context of Industry 4.0.

Predictive maintenance of machines and systems is achieved through collection, storage, and analysis of huge amounts of data. The recorded process and machine data make forecasts possible and enable companies to prevent machine failures and malfunctions at an early stage and thus avoid downtimes.  

The challenge is that the initiatives and development projects often don’t lead to the desired result. 

How do I choose the right case of application, which prerequisites have to be established and what has to be considered when implementing a predictive maintenance solution? 

Find out more in our webinar on how to successfully lead predictive maintenance projects. 

Your Benefits

What Can I Achieve with Predictive Maintenance and What Are the Criteria for Success? 

  • Targeted increase in process efficiency by increasing the system availability. 
  • Optimization of maintenance cycles through needs-based and predictive maintenance. 
  • Reduction of maintenance costs through more efficient use of resources and optimized spare parts management
  • Increased transparency of the manufacturing processes through status and condition monitoring.

Contents & Key Learning

  • Find out how you can maximize the potential benefits of a predictive maintenance solution and identify the right case of application. 
  • Learn the advantages of predictive maintenance and the conditions needed to make it worth the effort. 
  • You will get an overview of the prerequisites that must first be created as well as the fundamental issues which must be considered for a successful implementation. 
  • Find out how a predictive maintenance project leads you to success in iterative steps and why it doesn't always have to be "artificial intelligence".


  • Managers
  • Decision-makers
  • Skilled workers from manufacturing companies