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Although most statistical process control techniques are designed to detect constant process shifts, time-varying shift patterns are more frequently encountered in industrial practice. In this paper, we propose an adaptive T2 scheme for monitoring processes with dynamic shifts. The new scheme preserves the optimality of directionally variant charts by updating a reference mean-shift vector recursively and can be easily adjusted to obtain high sensitivity across desired shift ranges. Simulation studies show that the adaptive T2 chart with EWMA forecasting of mean shifts outperforms most conventional charts in a dynamic environment and is also robust to parameter-estimation uncertainties.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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