For decades, process analytics instrumentation has been maintained using fixed calibration and service intervals—practices designed to ensure reliability, but often resulting in unnecessary maintenance, excessive labor demands, and avoidable process interruptions. As industrial operations face mounting pressure to maximize uptime with fewer resources, this traditional model is being fundamentally challenged.
Sensor intelligence and digital transformation are enabling a new approach.
Advances in embedded diagnostics and real-time data visibility now allow analytical systems to continuously evaluate their own condition and performance. This evolution supports a shift from time-based maintenance to condition-based (CBM) and ultimately predictive maintenance (PM), where action is taken based on actual need rather than predetermined schedules.
This presentation explores how modern analytical systems can effectively “self-report” their health, enabling teams to intervene only when required. This shift is reshaping process analytics across industries such as power generation, chemical manufacturing, and other continuous operations. By leveraging predictive diagnostics, organizations can reduce unnecessary calibrations, extend maintenance intervals, and redeploy skilled labor toward higher-value activities—all while improving measurement reliability.
The impact extends well beyond maintenance efficiency. Early identification of sensor degradation and process anomalies enables more proactive decision-making, reducing the risk of unplanned downtime, off-spec production, and safety events. In this model, process analytics evolve from a routine maintenance requirement into a strategic contributor to operational performance.
Drawing on real-world industry experience, this session will outline practical considerations for adopting predictive strategies, including data utilization, organizational alignment, and change management. Attendees will leave with a clear understanding of how to modernize their maintenance approach and leverage digital capabilities to drive measurable improvements in uptime, reliability, and overall plant performance.