Statistical Process Control Software

What Makes A Good Statistical Process Control?

A statistical process control (SPC) system is designed to monitor and analyze processes in order to identify and correct problems before they become problems. SPC systems typically consist of three components: a process modeler, a data collector, and a data analyzer.

Process Modeler: A process modeler is responsible for analyzing the process and identifying any problems. It does this by defining the inputs and outputs of the process, determining the variation in the process, and modeling the process.

Data Collector: A data collector collects the data produced by the process. Data collectors collect information such as machine settings, production times, quality measures, and anything else that affects the process. Collected data is then analyzed by the data analyzer.

Data Analyzer: A data analyzer is responsible for analyzing the collected data. It compares the actual results to the expected results and identifies deviations from the expected results. From there, the data analyzer determines whether the deviation could affect the process. Once identified, the problem is corrected and the process continues on its path towards being perfect.

What Is Statistical Process Control Software Statistical process control (SPC) is a statistical technique used in manufacturing to ensure quality. SPC software helps operators monitor the quality of their processes so they can identify any problems before they affect product quality.