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In the dynamic and complex landscape of metals and mining operations, achieving operational excellence is crucial ...
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A leading global fertilizer manufacturer, known for producing complex NPK blends, wanted to enhance its quality control process.
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Meeting ultra-low sulphur diesel (ULSD) norms often forces operators to run with wide safety margins ...
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Tridiagonal.ai (T.AI) Joins Joint Development Agreement to Advance PETRONAS Carigali’s TriCipta AI with IBM through Engineering Domain-Driven AI Solutions
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Order fill projection AI

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Predicting the end-of-cycle (EOC) for a heat exchanger due to fouling is a persistent challenge for refineries. By proactively forecasting when a heat exchanger requires cleaning, refineries can implement risk-based maintenance planning, optimizing processing rates, and reducing operating and maintenance costs. Historically, engineers had to manually combine data entries in spreadsheets, spending hours or even days formatting, filtering, and removing non-relevant data, such as entries when equipment was out-of-service. Advanced analytics now streamline this process, enhancing efficiency and accuracy in maintenance planning.

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