AI automates abnormal sound detection on behalf of humans! Contributing to product manufacturing defects, equipment malfunctions and failures, and smart maintenance of products.
Monone, which utilizes an AI algorithm trained on sound, detects abnormalities in objects and equipment quantitatively and with high precision, without relying on human experience or intuition. This enables reliable abnormal sound detection, leading to labor-saving maintenance and inspection tasks, as well as reduced inspection costs. Monone minimizes losses due to failures, ensures the stability of production processes, and greatly contributes to manufacturing digital transformation (DX).
**Why Monone?**
- **Early Trouble Detection:** Monitors machine sounds in real-time and detects abnormal sounds. This allows for early detection of equipment malfunctions and failures, reducing unexpected troubles and contributing to cost savings through efficient maintenance.
- **Improvement of Manufacturing Process Quality:** By detecting subtle abnormal sounds and defects, it is expected to enhance product quality. It strengthens quality control and prevents the production of defective products.
- **Increased Production Efficiency:** Early detection of troubles and preventive maintenance increase the normal operating time of machines, improving production efficiency and the overall efficiency of the manufacturing process.
- **After-Support:** Continuous support after implementation helps facilitate early utilization.
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