Predictive maintenance is a technique that uses information analysis tools and
techniques to sight anomalies in your operation and attainable defects in
instrumentation and processes therefore you'll fix them before they lead to
failure. Predictive maintenance not only increases the health of your machines
but it also helps you to remain more focused towards your business,
predictive maintenance solution by SenseGiz will take care of your factory’s
equipment.
The manual process of monitoring the health of machines every 15 to 20 days
is eliminated using SenseGiz’s Predictive maintenance solution.
Monitoring-Temperature,
vibration of machines,
transformers and other
industrial assets.
Full life cycle remote
Monitoring for predictive
maintenance.
Methodology
( Easy to install, Plug and Play devices with remote access on web and mobile through the cloud )
Sensors
Plug and Play, wireless sensors installed on assets monitor real time vibrations.
Cloud
Critical data is transmitted securely to the cloud through our gateway.
Dashboard
Visualize this data anywhere through web and mobile and get real time alerts.
Sensors
Plug and Play, wireless sensors installed on assets monitor real time vibrations.
Cloud
Critical data is transmitted securely to the cloud through our gateway
Dashboard
Visualize this data anywhere through web and mobile and get real time alerts
Benefits
Overall machine performance parameter
monitoring.
Machine utilization report and alarm indication if
Idle for more than defined time slot.
Real time data processing and online Update
collection at the central server.
Automated Report, Customized Analytics and
dashboard and notifications of Processed Data.
Cost-effective Data transmission- 4G/LTE,
multiple-sim aggregation.
Measure the productivity by shift and operator
wise.
Vibration data can be streamed at regular intervals of time.
Data for all three axis can be seen on the dashboard.
Vibration analytics can be done using FFT on dashboard.
Analytics dashboard for vibration monitoring.
Set upper and lower threshold values.
Get alerted in case the threshold values are crossed.
Analyze historical data to see where frequent problems are taking place.