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 is possible
By monitoring machine sounds in real-time and detecting abnormal noises, early detection of equipment malfunctions and failures is made possible, reducing unexpected troubles and contributing to cost savings through efficient maintenance.
- Improvement of manufacturing process quality
By detecting subtle abnormal sounds and defects, an improvement in product quality can be expected. 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
Continued support after implementation helps facilitate early utilization.
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