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Statistical Process Control (SPC) in R: Monitoring and Quality Assurance

btd
8 min readNov 23, 2023

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Statistical Process Control (SPC) is a method for monitoring, controlling, and improving a process through statistical analysis. It involves using statistical techniques to identify and address variations in a process, aiming to ensure that it operates consistently within defined specifications. In R, various packages provide functionalities for implementing Statistical Process Control. Here’s a comprehensive guide covering key aspects of SPC in R:

1. Understanding Statistical Process Control:

  • SPC involves the use of statistical methods to monitor and control processes, ensuring they meet quality and performance standards.
  • Key Concepts: Control charts, process capability analysis, common cause variation, special cause variation.
  • Control Charts: Statistical tools used in quality control to monitor and maintain the stability of a process over time. Control charts graphically display the variations in a process over time and help distinguish between common cause variation and special cause variation. Commonly used types of control charts include X-bar charts for monitoring the central tendency and Range (R) charts for monitoring variability.
  • Process Capability Analysis: A statistical method…

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