Business Situation and Requirements
Production assets in oil and gas fields operate in harsh, remote environments, both offshore and onshore. These conditions often cause equipment failures, frequent downtime, and reduced asset performance. Disconnected systems and limited real-time visibility make it harder to monitor operations and respond quickly, impacting efficiency and production targets.
Mechademy aimed to build a smart monitoring and anomaly detection system for oil and gas refineries. The goal was to use AI and machine learning to detect faults early and predict failures. They wanted a reliable, scalable solution to improve asset performance and reduce downtime. To achieve this, they partnered with Unthinkable for its expertise in AI and industrial IoT.
The client chose Unthinkable for its experience in building advanced monitoring systems.
Their key requirements included:
Develop an AI-based software solution that works seamlessly with existing data historians or condition monitoring systems.
Detect equipment issues and underperformance early, often before traditional protection systems can respond.
Use machine learning and performance modeling to gain deeper insights into turbomachinery health.
Analyze data from multiple sensors, such as acoustic sensors, accelerometers, and infrared thermography, to spot sub-optimal operations.
Track trends and compare performance with models to monitor equipment more effectively.
Display key insights through an easy-to-use, customizable dashboard with visualizations like bar charts, pie charts, and line graphs.
Provide both a high-level overview and detailed drill-down views of plant performance to support better operational decisions.
