Statistical Process Control (SPC)

Introduction :1. Statistical Process Control (SPC) is a technique pioneered by Dr Walter Shewhart in the 1920’s.  Dr Shewhart found that in any variation, there are two distinct sources
– Common or random cause
– Assignable or non random cause.
2.SPC control charts are useful in providing information to Process owner to advise them when and when not to adjust a process.
3.SPC was not fully utilised until after the 2nd  World War when Dr Deming introduced it to the Japanese Industry.
4.One of the key factors that have enabled Japanese companies to produced extremely high quality is the use of SPC.
5.It was not until the late 70’s that the American multinationals started to use SPC widely

Introduction:Some definition about SPC:
a)A statistical technique that is widely used to ensure that the process is meeting standards.
b)A technique using charts and graphs to check a production process to see if any way not functioning properly which could lead to poor quality.
c)An application of scientific method to control and improve manufacturing process.
d)A term used to describe the concept of using statistical tool to assist in controlling the quality of a process.

Benefits of SPC

  • Lower manufacturing costs
  • Correct standards
  • Stable processes
  • Realistic Specification
  • Less inspection
  • Decreased problem – to – solution lead time
  • Better customer relations
  • Reliable measures of capability
  • Improved forecasting
  • Improved product quality
  • Decreased cycle time

What’s capability index ?

What’s capability index ?

“Capability index” is a quantitative value to let us know information about a process performance ! It advises us of:

  • How stable a process is !
  • How capable of meeting specification a process is !

Why do we need capability index

  • To  have a quick understanding of process performance
  •  To be able to effectively predict yield, quality level and cost
  • To measure the effects of change in the system with greater speed and reliability
  •  To alter specification limits, it will have the data to back up its decision

Capability index application in SPC

Statistic Process Control

Statistic Process Control


The purpose & scope   

1.To assist in determining the following major problems of all gauging systems used throughout the manufacturing process

  • Precision
  • Variation
  • Acceptability

2.To furnish a comparison of the accurracy of one measuring device against another
3.Why is the accuracy of the gauge wrong?

  • Measurement errors
  • Incorrect usage
  • Equipment variation

4.The factors of the gauge system error

  • Accuracy
  • Stability
  • Repeatability
  • Reproducibility


  • The difference between the observed average of measurements and the true average of the same measurements.
  • Using the highest precision measuring device to get the true average.



  • The amount of variation in the gauge when the same parts and part characteristics are measured several times by the same person.





  • The amount of variation in the average of the measurements when different people use the same gauge on the same parts and part characteristics.



  • The periodic variations that occur due to enviromental changes,power fluctuations, wear or deterioration of the gauge .




Process Capability

1.Process capability is the ability of a process to meet specifications.  A process must be stable before its capability can be computed.

  • Not Capable
Not Capable

Not Capable

  • Capable


2.A capability index is a statistic that quantifies & describes the capability of a process

Inherent or Natural Variation

Inherent or Natural Variation
Due to the cumulative effect of many small unavoidable causes
A process operating with only chance causes of variation present is said to be “in statistical control”

Special or Assignable Variation

  • Due to

a)  improperly adjusted machine
b)  operator error
c)  defective raw material

  • A process operating in the presence of assignable causes of variation is said to be “out-of-control”
Understanding Variation

Understanding Variation

Sources of Variation

  • within unit(positional variation)
  • between units(unit-unit variation)
  • between lots(lot-lot variation)
  • between lines(line-line variation)
  • across time(time-time variation)
  • measurement error(repeatability & reproducibility)

What is SPC?


  • Anything that deals with the collection, analysis, interpretation & presentation of numerical data
  • Gaining information for making informed decisions


  • Combination of machines, tools, methods, materials & people employed to attain process specification
  • A similar procedure/event that is happening repetitively


  • To keep something within a desired condition
  • Make something behave the way we want it to behave


The use of statistical techniques such as control charts to analyze a process, take appropriate actions to achieve & maintain a stable process, & improve process capability.

SPC Trend Rules

How to Interpret a Control Chart?

control chart

control chart

Remark:It is based on the Normal Distribution.

SPC Trend Rules
Rule#1: A single point beyond either control limit
Uses: Detects very large/sudden shifts
False alarm rate: 0.27%

SPC Trend Rule#1

SPC Trend Rule#1

Rule# 2: 9 consecutive points on the same side of the centerline
Uses: Detects small shifts or trends
False alarm rate: 0.39%

SPC Trend Rule#2

SPC Trend Rule#2

Rule# 3: 6 consecutive points steadily increasing or Decreasing
Uses: Detects strong trends

SPC Trend Rule#3

SPC Trend Rule#3

Rule# 4: 14 (or more) consecutive points are alternating up and down.
Uses: Detects systematic effects, such as alternating machines, operators, suppliers, etc.

SPC Trend Rule#4

SPC Trend Rule#4

Rule# 5: 2 out of 3 consecutive points at least 2 std dev beyond the centerline, on the same side
Uses: Detects large changes
False alarm rate: 0.30%

SPC Trend Rule#5

SPC Trend Rule#5

Rule# 6: 4 out of 5 consecutive points on the chart are more than 1 std dev away from the CL
Uses: Detects moderate-sized changes
False alarm rate: 0.53%

SPC Trend Rule#6

SPC Trend Rule#6

Rule# 7: 15 (or more) consecutive points are within 1 std dev of the CL
Uses: Detects a decrease in process variation

SPC Trend Rule#7

SPC Trend Rule#7

Rule# 8:  8 (or more) consecutive points are on both sides of the CL, but none are within 1 std dev of it.
Uses: Detects an increase in process variation

SPC Trend Rule#8

SPC Trend Rule#8

What is Statistical Process Control?

Statistical Process Control Explained
Statistical Process Control (SPC) is a set of tools designed to help reduce variation by identifying the source of variation, taking appropriate corrective action, and verifying the results.

  • Dr. Walter Shewhart of Bell Labs developed a theory of Statistical Process Control in 1924.
  • During the ’20’s Dr. Shewhart presented his theories in a series of lectures that were published in a book , Economic Control of Quality Manufactured Product (1931).
  • SPC came into wide use during the 1940’s as a result of war production efforts.