T-squared chart is the multivariate SPC chart based on Hotelling T-squared statistic to monitor joint deviation from a multivariable process center - it compresses correlated variable behavior into one anomaly indicator.

What Is T-squared chart?

• Definition: Chart of covariance-scaled distance between each observation vector and the in-control mean vector.
• Mathematical Role: Accounts for variable correlation so normal co-movement is not falsely flagged.
• Signal Output: Produces a single statistic with control limit for multivariate out-of-control detection.
• Deployment Scope: Common in equipment health monitoring and advanced process-control environments.

Why T-squared chart Matters

• Joint Fault Detection: Finds abnormal combinations that single-parameter charts may miss.
• Dimensionality Reduction: Simplifies high-dimensional monitoring into actionable alarm logic.
• False-Alarm Control: Correlation-aware scaling improves signal quality in coupled systems.
• Operational Speed: One composite index enables faster frontline decisioning.
• Quality Safeguard: Early multivariate anomaly detection limits excursion propagation.

How It Is Used in Practice

• Baseline Modeling: Estimate mean vector and covariance from stable reference operation.
• Limit Setting: Define control threshold by confidence level and sample context.
• Contribution Analysis: Decompose alarm events to identify dominant variable drivers.

T-squared chart is a core multivariate SPC instrument for correlated-process monitoring - covariance-aware anomaly scoring improves detection coverage in complex manufacturing systems.