The process of determining statistically derived boundaries that define acceptable variation in a process or system is crucial for monitoring performance. These boundaries, established from process data, help distinguish between common cause variationinherent in the systemand special cause variation, indicating a problem needing investigation. An example involves a manufacturing line where the weight of a product is measured; the defined boundaries identify if a deviation in weight is normal fluctuation or requires corrective action.
Establishing these boundaries provides a structured framework for process monitoring and improvement. Historically, this approach has been instrumental in enhancing quality control across various industries, leading to reduced waste, improved efficiency, and increased customer satisfaction. By providing a clear, data-driven basis for decision-making, this process minimizes subjective interpretations and promotes consistent responses to process variations.