Below are some industry-specific examples for a range of applications where machine data analytics and IoT analytics are useful.
Telecom & network equipment |
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Routers and switches are the backbone of datacenters and their continuous operations are a must. Because of the heterogeneous nature of these installations (mixed brands, models and software versions being common), unsupervised anomaly detection is the perfect solution for monitoring their operations and for service teams who need to investigate issues.
Speed up troubleshooting by having real-time or batch-processed machine data and log files analyzed for anomalies. Our integrated process mining technology allows to go above and beyond standard practices by not only detecting anomalies in numerical or other individual data sources, but also detecting anomalies in the execution of the process steps. The latter can be caused by e.g. abnormal system usage or by failures in other connected and interdependent systems. |
Industrial production equipment:
continuous processes
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In the manufacturing and process industry, machine data is everywhere: in quality databases, in production data from ERP / MES systems or data historians etc.
Gain real-time insights from sensors, devices and industrial systems like SCADA and historians. Monitoring the health of your assets and systems in real time is more and more wide-spread, but as we enter the Industry 4.0 era it is time to beyond that: predict and prevent where possible machine downtime, and use automatic anomaly detection solutions to help the human expert find the root-cause of production issues efficiently and successfully. |
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Industrial production equipment:
BATCH PRODUCTION AND DISCRETE MANUFACTURING
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Thanks to specific algorithms, Yanomaly can also detect issues with discrete manufacturing and batch processes.
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Industrial Printers & copiers
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Industrial printers and 3D printers are complex machines that need to perform flawlessly.
Machine fleets deployed in the field generate many log files and store data that can be leveraged for remote assistance and technical support, for predictive maintenance, for more realistic end-of-line testing and for additional insights to take into account in the design of future generation machines. |
Industrial Internet of Things and connected devices
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Traditional machine data and log file management tools were not designed for the vast amount of data generated by IoT devices, and are also not well suited to its variety, velocity, volume and variability.
Yazzoom's solution architecture is built to handle big data and is highly scalable. Find and fix problems across the massive data sets from multiple sources. Gain operational intelligence and take better business decisions. |
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Medical devices & healthcare equipment
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Manufacturers and integrators of medical machines nowadays can have controlled access to the equipment's health and performance, and use that to maximize patient throughput and minimize downtimes.
Prevent high value asset's failure and reduce support requirements. Gain insights over usage patters and client-specific interactions and use cases to better design and test your equipment. |
Rolling stock
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Continuously monitor and analyze fleets and rolling stock's performance to increase availability, improve safety and reduce maintenance costs.
Detect infrastructure issues from data gathered by the deployed fleet's sensors and localization systems. |
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EV CharGing STATIONS NETWORKs
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Get insights on usage for better deployment and network extension, predict issues and failure to optimize service planning.
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