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Our product is a scalable, human-centric, no-code AI tool for condition monitoring, leveraging automatic anomaly detection and diagnosis technologies to enable the systematic implementation of Predictive Maintenance (PdM) by domain experts without AI expertise. By empowering engineers with direct access to AI, we bridge the AI awareness gap and offer capabilities beyond simple data analysis. Scalable and industry-agnostic, our tool supports retrofitting and continuous improvement projects across manufacturing industries like pharmaceuticals and automotive. With a simple UI, it requires only sensor data to train models and ensures reliability through real-time feedback. Our SaaS solution targets engineers, process experts, manufacturing heads, or any domain expert within the manufacturing unit, regardless of AI expertise.
+ Upload historical machine data from a .csv-file + automatic data visualization and data quality checks to improve data understanding + automatic creation of machine learning models + automatic validation of model results and generation of a PDF report for management + Link sensor data to our SaaS tool and run real-time anomaly-detection and -diagnosis with human feedback, to enable continuous improvement and systematic implementation of Predictive Maintenance
The solution can be easily integrated using common interface technologies in manufacturing (e.g. OPC UA, REST API, OsiSoft PI) It can be customized depending on requirements.
Following support services are offered: + awareness training of AI in manufacturing + training of usage of our tool + support during implementation + support post implementation until real-time anomaly detection / diagnosis + support to identify required Predictive Maintenance solution based on identified anomalies + support for process analysis with partner to identify required IoT sensors
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based on research the ROI for Predictive Maintenance solutions is 6 - 12months
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