Statistical Process Control

Statistical Process Control with Variable & Attribute Charts

Created byVineet Kumar Pandey

Last updated 11/2025

Hindi

What you'll learn

What is SPC
What is Statistical Process Control
SPC in Variable & Attribute Measurement
Process Capability Method & Formulae
Variation & Stable Process

Course content

1 section • 7 lectures • 1h 59m total length

Introduction11:48
SPC most commonly refers to Statistical Process Control, a quality control method used in manufacturing and other industries to monitor and control processes by using statistical methods to analyze real-time data. It helps identify and reduce variation to improve quality and efficiency, using tools like control charts to detect problems before they lead to defects
SPC 223:48
SPC 312:37
Statistical Process Control (SPC)
What it is: A method of quality control that uses statistical techniques to monitor and control a process.
How it works: Data from a process is collected and plotted on a control chart to show the variation. This data is analyzed to distinguish between "common cause" (natural) variation and "special cause" (assignable) variation.
Purpose: To achieve continuous process improvement by reducing variation, improving efficiency, and ensuring products are made to specification.
Application: Widely used in manufacturing, but also applied in other industries like healthcare, to monitor and control processes in real-time.
Key Benefit: By monitoring processes in real-time, SPC can detect potential problems early, preventing defects and reducing waste, rather than inspecting quality issues after production is complete.
SPC 46:09
1. Statistical Process Control (SPC)
This is the most frequent meaning, particularly in manufacturing, engineering, and service industries. It is a data-driven quality control methodology that uses statistical methods to monitor, control, and improve a process or production method by identifying and eliminating sources of variation.
Key aspects of Statistical Process Control include:
Goal: To ensure a process operates consistently and within acceptable limits, minimizing defects, waste, and the need for inspection.
Tools: The primary tool is the control chart, which graphically plots process data over time against statistically derived upper and lower control limits (UCL and LCL) and a center line (mean).
SPC 533:23
SPC 614:18
SPC 717:04

Requirements

Basic understanding of manufacuring

Description

Statistical Process Control (SPC)

Statistical Process Control is a data-driven quality control methodology used to monitor, control, and improve a process or production method by eliminating variation. It is widely used in manufacturing, engineering, and service industries to ensure consistent quality and efficiency.

Key aspects of SPC:

Methodology: It involves collecting real-time data from a process and analyzing it using statistical techniques.
Control Charts: The primary tool of SPC is the control chart, which is a graph with a center line (mean) and upper and lower control limits.
Variation Analysis: SPC helps distinguish between two types of process variation:
- Common cause variation: The natural, random variation inherent in any stable process.
- Special cause variation: Unnatural or assignable variation that stems from external sources or specific events (e.g., equipment malfunction, operator error) and indicates that the process is out of control.
Objective: The goal is to detect special cause variations early to take corrective action, minimize defects, reduce waste (scrap and rework), and ultimately improve product quality and consistency.
Proactive Approach: Unlike traditional quality control methods that inspect finished products, SPC is a predictive, prevention-based technique focused on the process itself.
Statistical process control (SPC) or statistical quality control (SQC) is the application of statistical methods to monitor and control the quality.

Who this course is for:

Any Manufacturing Professional