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The plan–do–check–act cycle. PDCA or plan–do–check–act (sometimes called plan–do–check–adjust) is an iterative design and management method used in business for the control and continual improvement of processes and products. [1] It is also known as the Shewhart cycle, or the control circle/cycle.
The normal distribution is NOT assumed nor required in the calculation of control limits. Thus making the IndX/mR chart a very robust tool. This is demonstrated by Wheeler using real-world data [4], [5] and for a number of highly non-normal probability distributions.
W. Edwards Deming invited Shewhart to speak at the Graduate School of the U.S. Department of Agriculture and served as the editor of Shewhart's book Statistical Method from the Viewpoint of Quality Control (1939), which was the result of that lecture. Deming was an important architect of the quality control short courses that trained American ...
The PDCA cycle [3] Preventive action is any proactive method used to determine potential discrepancies before they occur and to ensure that they do not happen (thereby including, for example, preventive maintenance, management review or other common forms of risk avoidance). Corrective and preventive actions include stages for investigation ...
These methods are based on continuous monitoring of process variation. The control chart, also known as the Shewhart chart or process-behavior chart, is a statistical tool intended to assess the nature of variation in a process and to facilitate forecasting and management. A control chart is a more specific kind of run chart.
Walter Andrew Shewhart (pronounced like "shoe-heart"; March 18, 1891 – March 11, 1967) was an American physicist, engineer and statistician. He is sometimes also known as the grandfather of statistical quality control and also related to the Shewhart cycle.
Nelson rules are a method in process control of determining whether some measured variable is out of control (unpredictable versus consistent). Rules for detecting "out-of-control" or non-random conditions were first postulated by Walter A. Shewhart [1] in the 1920s.
Most statisticians of the Shewhart-Deming school take the view that special causes are not embedded in either experience or in current thinking (that's why they come as a surprise; their prior probability has been neglected—in effect, assigned the value zero) so that any subjective probability is doomed to be hopelessly badly calibrated in ...