Statistical Process Control (SPC) is evolving to not just detect defects, but also to predict and prevent issues. Modern factories use more sensors and collect more data, allowing SPC to analyze real-time patterns and forecast potential issues.

Design of Experiments (DOE) helps improve products and processes more efficiently, providing a comprehensive understanding of influences on the end result.

Quality assurance professionals in manufacturing know that even a single non-conformance can result in rejected batches or regulatory violations. The Process Capability Index (Cpk) helps teams catch potential issues before they become costly problems.

Time series analysis enables manufacturers to track quality data, revealing patterns, trends, and anomalies to maintain consistent production standards. This method can be applied to daily production output or hourly quality measurements.

Monte Carlo simulation helps companies understand process variability and make informed decisions. It's beneficial for quality control in manufacturing.

In situations where resources are limited to gathering real data would be too expensive or impractical, Monte Carlo simulations can help forecast results and probabilities. 

The main difference between projects and programs is their scope and focus. Project management focuses on efficiently executing specific projects, while program management aligns multiple projects with overarching strategic goals.

Minitab Engage is a designed CI tool for initiating, monitoring, managing, and sharing innovation and initiatives from idea generation to execution.