Purification of water
GOALS
- 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
Data
- 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..)
Analytics
- 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
Results
- 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
