dynamic control charts

**Dynamic control charts** is the **SPC framework for processes whose expected behavior changes over time or by operating state** - it monitors deviation from dynamic baselines rather than fixed static limits. **What Is Dynamic control charts?** - **Definition**: Control charts incorporating state, mode, or time-varying expected values and limits. - **Need Context**: Required when process behavior depends on recipe phase, load level, or control-setpoint transitions. - **Model Inputs**: Can use state-space models, regression baselines, or rule-based operating-region logic. - **Signal Objective**: Detect abnormal deviation relative to current dynamic expectation. **Why Dynamic control charts Matters** - **Better Fit**: Static charts can produce misleading alarms in inherently time-varying processes. - **Detection Precision**: Dynamic baselines isolate real anomalies from planned operating changes. - **Control Stability**: Reduces unnecessary interventions caused by misinterpreted normal transitions. - **Yield Protection**: Improves anomaly detection in recipe phases with narrow tolerance margins. - **Scalable Monitoring**: Supports modern APC environments with mode-dependent behavior. **How It Is Used in Practice** - **State Definition**: Segment process into operating modes with separate expected behavior models. - **Model Validation**: Verify dynamic baseline quality across full production envelope. - **Alarm Logic**: Apply mode-aware OCAP actions tied to deviation severity and duration. Dynamic control charts is **a critical SPC evolution for nonstationary process systems** - mode-aware monitoring improves both alarm relevance and operational confidence.