Purification of water


  • Analyse the data situation of a mid-sized industrial machine producer and making older machines ready for remote analytics and predictive maintenance
  • Find a way to seamlessly integrate machine data into existing BI front-ends for analytics purpose


  • Sensor data from multiple disjunct sensors within the machine.
  • machine incident and log data
  • thermodynamic data (temperature, pressure) and change-log data
  • water quality data (sludge amount..)


  • Machine learning and statistical modelling algorithms
  • Big Data technologies for creating analytical boards and models
  • Python
  • Power BI

Business KPIs

  • Maintenance dates
  • Intelligent workforce planning
  • Automatic feedback from machines


  • Making non-IoT machines IoT-ready at extremely low costs
  • Laid out the foundation for further analytics and predictive maintenance as a new service, that our customer can offer to his customers
  • Having all data synchronized, we further created a BI cockpit, that made it possible for non-IoT machines to be monitored remotely in near real-time
  • Positive environmental impact on waste reduction and utilization
  • Overlooking a remote-access machine part improves operational effectiveness from maintenance to waste valorization