Statistical Process Control (SPC) was initially developed over 65 years ago by Walter A. Shewhart as a method to improve or achieve quality control in a manufacturing process. In this method, statistical tools like frequency distribution, histograms, scatter diagrams and Pareto charts are used to view and reduce process variation, thereby reducing defects and waste from the production line. Although SPC is a cost-effective and thorough method of determining and predicting significant deviations in a production environment, quality control managers routinely face inconsistent results when implementing this method manually. Human error is a major source of inaccuracy along various points in the process. For instance, misinterpretation of the display readout, incorrect transcription onto printed documents, and even weighing the wrong sample can skew overall statistical results.
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