The purpose of this work was to highlight the importance of controlling process variability for successful quality assurance (QA). We describe the method of statistical process control for characterizing and controlling a process. Traditionally, QA has been performed by comparing some important measurement (e.g., linear accelerator output) against a corresponding specification. Although useful in determining the fitness of a particular measurement, this approach does not provide information about the underlying process behavior over time. A modern view of QA is to consider the time-ordered behavior of a process. Every process displays characteristic behaviors that are independent of the specifications imposed on it. The goal of modern QA is, not only to ensure that a process is on-target, but that it is also operating with minimal variation. This is accomplished by way of a data-driven approach using process behavior charts. The development of process behavior charts, historically known as control charts, and process behavior (action) limits are described. The effect these concepts have on quality management is also discussed.