This white paper explores how modern manufacturers use process control, statistical methods, and AI to move from reactive detection to proactive prevention. It explains univariate and multivariate statistical process control, control charts, and early warning systems used to monitor complex production environments. The paper highlights advanced techniques such as autoencoder-based anomaly detection, digital twins, and predictive modeling for real-time optimization. By integrating streaming data, analytics, and automation, manufacturers reduce waste, improve quality, increase efficiency, and enable smarter, more resilient factory operations.

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