Mtell helps a midstream oil and gas company to identify failures and avoid expensive downtime

May 30, 2018 | Case Study

A midstream oil and gas operator was struggling with unexpected downtime. The company’s rotating equipment was the primary cause of downtime, with each downtime event costing around $1 million. To reduce these incidents, the company engaged Mtell, a predictive maintenance software company that provides services for a wide range of industries, including oil and gas, chemicals, rail, and wastewater. Mtell develops machine learning models that ingest data from industrial facilities to identify potential sources of failure that could lead to downtime. Its software can process a variety of equipment and is not limited to rotating equipment, which played well for its oil & gas customer, which had a diverse set of equipment including boilers, incinerators, compressors, and pumps.

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