AI-Based Compressor Management Application Case Study - Bilig Opex
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AI-Based Compressor Management Application Case Study

Reducing Air Sourced Production Interruptions in the Foundry

Customer’s Business Problem:

Production interruptions due to compressor failure in our customer’s foundries were a problem that affected efficiency. This was causing production targets to fall behind, delivery delays and increased costs. The reason for the compressor stop could not be known until the inspection at the compressor head, and the precautions taken were insufficient due to different reasons.

Kompress AI Solution:

The Kompress.AI smart compressor management solution allowed the customer to remotely monitor the compressor and receive alerts when threshold violations occurred at any value. In this way, some of the causes of downtime could be eliminated with early intervention.

After the installation of our solution, it was observed that the compressor could not keep the temperature at the recommended levels due to frequent fan failure, which caused the compressor to stop. It was also understood that the ambient temperature in the facility was not controlled. Since the fan failure is encountered when the ambient temperature is usually too high, it was interpreted that this situation indirectly caused the compressor to malfunction.

If the discharge temperature rises above 95 degrees according to customer settings, it gives a warning. The fan turns on when it reaches 100 degrees. If the fan does not start or stops, the temperature starts to rise. Kompress.AI gives alarms at 105 and 110 degrees and suggests turning off the compressor. (Automatic shutdown is also planned by making an IoT connection).

Savings Provided:

The compressor maintenance team primarily saved 30% on maintenance-related costs. Downtime leading to reduced production efficiency in the foundry was significantly reduced, freeing up approximately 12 full staff shifts per year.

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