Regardless of how good your process is, there is always some variation. By monitoring the process over time, scientists and engineers can identify when the variation is becoming excessive and take steps to reduce it, so they can identify potential problems before they start affecting the product.
An important consideration in process monitoring is knowing when to react and how to differentiate the signals from the noise. Protecting product quality is central to the role of a process engineer/scientist, however, it is rare that there is only one source of variation that requires attention. Prioritizing process improvement projects using data-based risk metrics from process capability analysis reduces cost, and improves efficiency and product safety.
Your Key Learnings include selecting between control chart types based on process performance, how to set control limits, and when to update; and how to use process capability metrics to communicate the risk of OOS and to prioritize improvement projects
- Byron Wingerd, Life Sciences Systems Engineer, JMP
Malcolm Stevens, Principal Account Executive, JMP
- Emily Frieben, Developmental Editor, Wiley Interdisciplinary Reviews (WIREs)