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Predictive maintenance platform
Description
A system that allows managing and monitoring the technical condition of equipment at facilities that are crucial for the functioning of society and the economy.Problem
As companies grow, it becomes increasingly difficult to control familiar processes, which in turn consume more and more resources, both in terms of labor and finances. Current methods of diagnostics cannot accurately localize malfunction.Solution
Thanks to our proprietary sensors, it is possible to monitor parameters that are not accessible for control in default equipment, such as vibration, acoustic patterns, etc. Deep analysis of physical patterns is carried out using proprietary sensors, which unambiguously indicate a specific problem. Neural networks handle a huge amount of data and recognize sound anomalies in the acoustic image. The data is processed and decisions are made based on real data from specific equipment, allowing defects to be identified. The operator sees a notification about the detected anomaly, its cause, and based on this data, makes a decision about further actions.Description
A system that allows managing and monitoring the technical condition of equipment at facilities that are crucial for the functioning of society and the economy.Problem
As companies grow, it becomes increasingly difficult to control familiar processes, which in turn consume more and more resources, both in terms of labor and finances. Current methods of diagnostics cannot accurately localize malfunction.Solution
Thanks to our proprietary sensors, it is possible to monitor parameters that are not accessible for control in default equipment, such as vibration, acoustic patterns, etc. Deep analysis of physical patterns is carried out using proprietary sensors, which unambiguously indicate a specific problem. Neural networks handle a huge amount of data and recognize sound anomalies in the acoustic image. The data is processed and decisions are made based on real data from specific equipment, allowing defects to be identified. The operator sees a notification about the detected anomaly, its cause, and based on this data, makes a decision about further actions.
Financial Model
Time to launch the project: 6 months
Payback: 12 months
Interested in the project?
Geography
We have experience in working with clients in more than 20 countries: we understand how local legislation, mentality and experience influence technologies and innovation approaches
Our representations: Bahrain, China, Finland, Germany, Hong Kong, India, Indonesia, Italy, Kazakhstan, Malaysia, Singapore, South Korea, Switzerland, Thailand, Turkey, UAE, USA, Uzbekistan, Vietnam
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