From Reactive to Proactive: Machine Learning Drives Better Business Outcomes Case StudyCHALLENGE Failures of the hypercompressors in an LDPE process were resulting in high maintenance costs and the risk of missing orders. SOLUTION Aspen Mtell was deployed on the unit to increase the notification period. For a problem with the HP packing seal, it was able to provide 48 days of notice by including additional upstream sensors from the HP recirculation process. BENEFITS This pilot provided proof of three significant capabilities: • Longer-lead-time detection of repeating failures • Transfer of learning • The ability to capture fast-moving failures of advance warning for central valve failure 27 days We have embarked on a digital journey, and the ability to bring transparency to al

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