Using IoT to optimize the machinery capacity utilization
Operating on the highly competed field of contract manufacturing, Stera wanted to be able to affect the scheduling of large machinery investments by optimizing the utilization of its machinery capacity.
- To create a solution that uses IoT (sensor log data) to visualize the utilization of machinery capacity
- To provide a solution that would be scalable to other factories as well
BIGDATAPUMP implemented a solution where sensors produced video surveillance information on the machinery operations, components, as well as movement on the corridors. We developed a standardized Analytics Engine, where all collected data, both from sensors and other sources, was transferred. Analytics Engine is a secure cloud-based comprehensive solution for large amounts of data storage and analysis.
- Building an end-to-end concept and an IoT-solution
- Setting up the data platform (cloud based)
- Dashboard framework & visual design and BI development using QlikSense
- Web-based user interface creation using d3.js technology
- Maintenance and further development of the solution
Data was produced into visual reports using the QlikView tool. The reports described the key performance indicators: machinery operating times and utilization, as well as the traffic in the corridors. In the future, the analysis can be extended to cover the accessibility and safety of the corridors.
- The user-friendly visualizations allow for analyzing the originally abstract log data with a glance.
- The solution also enables optimizing capacity utilization and making more accurate plans upon the machinery investments’ schedule.
About Stera Technologies
Stera Technologies is a group specializing in serial production of mechanics and electronics operating in Finland, Estonia and India. Stera Technologies was looking into investing in new machinery worth millions of euros. To support the investment decision, the company wanted to analyse the current operating efficiency and the utilization of the existing machinery.