Beyond Scheduled Calibration: Monitoring Measurement Integrity Between Calibration Events

Scheduled calibration establishes measurement traceability at defined intervals, but it does not by itself guarantee that an automated measurement system remains stable throughout the period between calibrations. Changes in instruments, cables, interfaces, fixtures, environmental conditions, or system configuration can gradually alter measurement behavior while remaining unnoticed until the next calibration or an unexpected test failure.

This presentation examines a practical framework for monitoring measurement integrity between scheduled calibration events. The approach uses reference baselines, repeated multi-point verification measurements, measurement uncertainty and repeatability considerations, and warning and action limits to identify meaningful changes in system performance.

Particular attention will be given to distinguishing measurement-system degradation from genuine changes in the device or component being measured. Trending measurements over time can also help identify whether a deviation is isolated, range-dependent, or indicative of a developing system-level problem.

The goal is not to replace formal calibration, but to complement it with continuous evidence of measurement-system health. The presentation will discuss how these principles can be incorporated into automated metrology workflows to improve confidence in measurement results, support earlier detection of drift, and reduce unnecessary troubleshooting caused by measurement-system instability.

About the presenter
Tatiana Krasik, Ph.D., IEEE Senior Member, is a measurement and automated test systems engineer whose work focuses on measurement integrity, calibration methodologies, measurement uncertainty, and reliability of automated test processes. Her technical background includes RF and microwave measurement systems, production test engineering, and the development of methods for detecting measurement-system drift and distinguishing equipment-related anomalies from true device failures. Her current work explores practical approaches to continuous measurement assurance between scheduled calibration events and the use of data-driven monitoring to improve confidence in automated measurement results.