Aero-engine test cells play a critical role in verifying engine performance, ensuring compliance with Original Equipment Manufacturer (OEM) standards, and safeguarding operational reliability. Maintaining correlation between a local test cell and the OEM-approved reference cell is essential, as even small deviations in measurement accuracy or aerodynamic behavior can compromise the validity of test results. Traditionally, correlation is sustained through costly and infrequent master-engine tests, yet this approach is limited by resource availability, operational disruption, and the potential for correlation drift between calibration cycles. This thesis investigates the use of trend monitoring integrated with Statistical Process Control (SPC) as a practical and cost-effective framework for maintaining test cell correlation. The study is based on Aero Norway’s CFM56-5B test cell operations and utilizes an extensive dataset of historical engine runs, including both baseline correlation data and routine post-maintenance test records. A set of key parameters was identified as representative of both aerodynamic integrity and measurement stability, including inlet depression (ΔP vs. N1), fan operating line (PT17Q2 vs. W2K2), thrust–pressure and thrust–airflow relationships, thrust vs. N1 scaling, corrected airflow vs. N1, compressor inlet temperature (CIT) balance, and thrust margin. SPC control bands (±2σ) derived from baseline correlation data were applied to each parameter to detect deviations, quantify variability, and distinguish between systematic biases and true aerodynamic deterioration. The results demonstrate that Aero Norway’s test cell remained stable and in-correlation throughout the monitoring period. Observed systematic offsets, such as higher measured airflow and PT17 pressure deviations, were linked to known instrumentation differences (e.g., sector probe configurations, hose routing, inlet ramps) rather than genuine aerodynamic drift. Core thrust parameters aligned closely with baseline references, with anomalies attributable to short-term measurement or operational transients. Engine-level diagnostics confirmed uniform inlet temperature distribution and consistently adequate thrust margin. The findings confirm that SPC-based trend monitoring provides a reliable means of safeguarding correlation validity, detecting anomalies early, and reducing reliance on costly OEM re-correlation. Recommendations are proposed for integrating this framework into Aero Norway’s routine operations, thereby enhancing the long-term sustainability of correlation management.

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