In chemical manufacturing, reliability teams must manage critical machinery and instrumentation in a fast-paced, complex environment.

With equipment availability directly affecting safe and reliable production, teams need timely insight into emerging risks to make informed maintenance decisions.

During this webinar, Proman shared how one of the world’s largest methanol production facilities is applying Industrial AI to improve visibility into equipment degradation, abnormal operating behavior, sensor anomalies and developing failure conditions. Through real-world examples, attendees will learn how predictive alerts are reviewed and acted upon within maintenance workflows and how structured implementation and operational practices help sustain adoption and drive measurable business outcomes.

View this presentation to learn how Proman:

• Developed a strong foundation for success through a structured and methodical implementation approach.
• Applied predictive analytics across critical machinery and instrumentation to identify emerging equipment issues earlier.
• Incorporated alerts into maintenance workflows to support more informed decisions and help reduce the risk of costly downtime.
• Established best practices for scaling Industrial AI across complex production operations while sustaining adoption and long-term business value.

Join Proman as they discuss the decisions, lessons, and operational approaches that helped turn predictive insights into action, creating a stronger foundation for reliability across critical production assets.