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Statistical Process Control (SPC)

Introduction

This repo contains some personal notes about SPC basic concepts.

SPC is a method of quality control which employs statistical methods to monitor and control a process. The aim is to ensure that the process is operating efficiently within specified conditions and reducing variation about a target value.

SPC is a sector of statistics dealing with the effort of improving quality constantly. It is extensively used in industry to keep manufacturing processes under control, but its tools are also used in various fields of science such as medicine, environment, economics, text analyses and informatics. The most valuable tool of SPC is control charts. These charts give a graphical appearance of the process giving the ability to any manager with or without the knowledge of statistics to immediately understand if the process is under control or not.

Contents

This repository provides a notebook with basic concepts about uni- and multivariate statistical process control tools. Among them, we review:

  • Shewhart control chart
  • Uni and multivariate CUMSUM control charts
  • Uni and multivariate EWMA control chart
  • Chi-square control chart
  • Hotelling T^2 chart

The notebook makes a comparative using a set of R libraries and customized python code.

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