SmartLog Case Studies Predictive Maintenance for Industrial Chillers
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Predictive Maintenance for Industrial Chillers

Predictive Maintenance for Industrial Chillers - SmartLog Industrial IoT Case Study
Analytics & Modeling - Predictive Analytics
Analytics & Modeling - Real Time Analytics
Functional Applications - Enterprise Asset Management Systems (EAM)
Networks & Connectivity - LoRa
Sensors - Pressure Sensors
Sensors - Temperature Sensors
Equipment & Machinery
Predictive Maintenance

For global leaders in the industrial chiller manufacturing, reliability of the entire production process is of the utmost importance. Chillers are refrigeration systems that produce ice water to provide cooling for a process or industrial application. One of those leaders sought a way to respond to asset performance issues, even before they occur. The intelligence to guarantee maximum reliability of cooling devices is embedded (pre-alarming). A pre-alarming phase means that the cooling device still works, but symptoms may appear, telling manufacturers that a failure is likely to occur in the near future. Chillers who are not internet connected at that moment, provide little insight in this pre-alarming phase.

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Thanks to an asset performance health index on our dashboard, chiller manufacturers are constantly provided insight in the health of their assets. Failures can be predicted, manufacturers are directly alerted in case of problems so they can be resolved re
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A failing device not only results in downtime, but as well in faulty chiller components. Chiller connectivity however, guarantees process stability, process reliability and energy efficiency, since all parameters (pressure, temperature, current values…) are monitored and visualized on our dashboard. This way, we can make a prediction regarding the amount of days within the failure is likely to occur.

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Asset Performance, Downtime, Fridge Temperature, Pressure, Production Efficiency
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[Efficiency Improvement - Asset Utilization]
Asset performance health index.
[Efficiency Improvement - Production Uptime]
Failures can be predicted.
[Efficiency Improvement - Issue Response]
Turnaround time for problem resolution will be reduced dramatically.
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