Revolutionizing Grinding and Milling with AI-Powered Acoustic Monitoring
By Pavel Konečný, CEO & Co-Founder of Neuron Soundware
At Neuron Soundware, we are redefining process control within manufacturing through our AI and machine learning-powered technology. By interpreting machine sounds, we not only prevent production downtime but also optimize production processes, including the grinding of hard materials.
Optimizing the Grinding Process: A Case Study with Major Chemical Company
Our latest project involved optimizing the grinding process for bauxite in an industrial mill. The client’s challenge was achieving consistent quality across different batches within an 18-hour grinding cycle. Our mission was to find out if we could improve efficiency without compromising the quality.
The Inefficiency of Fixed Grinding Cycles
Traditionally, the fixed grinding cycle was a safe bet for consistency but often led to inefficiencies. Tests showed that while an 18-hour cycle guaranteed quality, the desired outcome was frequently achieved earlier, between 14-17 hours, leading to unnecessary energy use and time wastage.
Introducing the NSW IoT Process Monitoring Solution
To tackle this, we deployed our IoT sensor-equipped nGuard solution. By installing non-invasive sensors on mill components, our AI model analyzed the data with over 95% accuracy, identifying the right time to stop the grinding process for optimal quality.
Impressive Results: More than Just Time Savings
Our approach not only reduced the grinding cycle but also presented significant economic benefits:
- 304% ROI on the service provided by NSW.
- Monthly savings of €4,672 per machine.
- Average energy savings of 1218 kWh per run.
- 2h 58min average time savings per run, resulting in a more efficient production flow.
Beyond the Numbers: Autonomous Machine Control
Our solution stands out for its ability to autonomously control the grinding process, minimizing the need for personnel intervention. It’s a step forward in smart manufacturing, enabling immediate operational adjustments and cost savings:
- 292 € average cost savings on energy per run.
- Increased credibility as a reliable supplier due to consistent quality output.
Conclusion: Pioneering in Process Monitoring
NSW is the only solution that can detect the material quality during the grinding process, proving itself as a crucial tool in process monitoring. Our acoustic monitoring, combined with AI and ML algorithms, provides a real-time analysis that’s transforming the industry standards for grinding and milling machines.
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