Business and operations systems are becoming increasingly integrated in the digital era. With accessible data and information, enhancing the business value of plants that utilize equipment for production has become more achievable. Improving equipment performance and availability leads to increased production, fundamentally enhancing overall plant value.
Rotating equipment plays a vital role in process industries, including chemicals, oil & gas, mining, water treatment, and power generation. When equipment availability or performance declines due to a developing defect, production losses occur in the form of downtime, reduced efficiency, and compromised quality.
In the digital era, rotating equipment and systems are monitored using a wide range of sensors to detect potential defects, automate analytics, and recommend mitigating actions. Automating sensor data collection and analytics enhances worker productivity by allowing personnel to focus on tasks that require human insight and decision-making.
Automated sensor systems provide several benefits, including lower maintenance costs, reduced manual data collection, extended equipment lifespan, lower capital costs, increased production output, improved sustainability, fewer safety incidents, and enhanced visibility into equipment health and performance.
This discussion focuses on the components of a digital predictive and prescriptive maintenance program and application, outlining the implementation process and presenting a case study.
