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. For more details, please download the PDF or feel free to contact us.
Inquire About This Product
basic information
**Four Features of Monone** 1. Dedicated Microphone The microphone is directly attached to the device, allowing it to collect sound conducted through metal directly. 2. Model Creation Using Only Normal Sounds Normal sounds are used for machine learning to create a model. Abnormal sounds are not needed, and the deviation between the measured sound and the model is assessed. 3. Adoption of Two Algorithms Two feature extraction algorithms, for fluctuating sound analysis and FLAC, are implemented and can be selected according to the inspection target. 4. Consulting Services We offer consulting services provided by experienced specialists.
Price range
Delivery Time
Applications/Examples of results
【Examples of Monone's Application Scope】 Abnormal sound detection can be utilized in various scenarios. 1. Use in manufacturing equipment - Production plants (food, pharmaceuticals, chemicals, energy) - Semiconductor equipment (semiconductor devices, integrated circuits, sensors, actuators) - Machine tools (machine tools, cutting tools) 2. Use in product maintenance - Automobiles, railway vehicles, wind turbines, etc. 3. Use in final inspection - Motors, industrial machinery, home appliances, etc.
catalog（2）
Download All Catalogs
Company information
Since our establishment in 1970, we have been involved in the planning, development, maintenance, and operation of information systems in various fields for many customers, including the ENEOS Group. With the motto "From the seabed to space," we continue to work together with our customers in the spirit of "INTO HAPPINESS," contributing to society through the technical expertise we have refined together with them. Please feel free to consult us if you have any requests.
![[Data Science Utilization Case] Fault Prediction Detection in Wind Power Generation Facilities](https://image.www.ipros.com/public/product/image/bce/2000962725/IPROS47024191747341687844.png?w=280&h=280)
