statistical quality control & sqc tools

Anjuman-I-Islam’s, Kalsekar Technical Campus Copyright 2016 © Afaqahmed

Prof Afaqahmed M J


Introduction to SQC

•Statistical Process Control (SPC) is a collection of tools that when used together can result in process stability and variability reduction

•Statistical Quality Control (SQC) is the term used to describe the set of statistical tools used by quality professionals.


W. Edwards Deming invited Shewhart to speak at the Graduate School of

the U.S. Department of Agriculture, and served as the editor of Shewhart's

book Statistical Method from the Viewpoint of Quality Control (1939) which

was the result of that lecture.

Deming was an important architect of the quality control short courses that

trained American industry in the new techniques during WWII.

Deming traveled to Japan during the Allied Occupation and met with the

Union of Japanese Scientists and Engineers(JUSE)in an effort to introduce SQC

methods to Japanese industry

HISTORY


Benefits of Statistical Quality Control

1) It provides a means of detecting error at inspection.

2) It leads to more uniform quality of production.

3) It improves the relationship with the customer.

4) It reduces inspection costs.

5) It reduces the number of rejects and saves the cost of material.

6) It provides a basis for attainable specifications.

7) It points out the bottlenecks and trouble spots.

8) It provides a means of determining the capability of the

manufacturing process.

9) It promotes the understanding and appreciation of quality

control

THE SEVEN MAJOR TOOLS ARE 1) Histogram or Stem and Leaf plot 2) Check Sheet 3) Pareto Chart 4) Cause and Effect Diagram 5) Defect Concentration Diagram 6) Scatter Diagram 7) Control Chart Anjuman-I-Islam’s, Kalsekar Technical Campus Copyright 2016 © Afaqahmed


1. CHECK SHEET •Manual Graphical Method of data collection

• It collects data in organized manner

•No of defects / sample is generally shown

• It gives acceptable range

•Tick mark is made against defect

HOW TO CONSTRUCT CS

Define problem / process

Define suitable period

Design Check Sheet based on data

Develop a CS which is easy to understand

Perform data collection

Analyze

Training

Plotting


2. FLOW CHART • It shows sequence of operation in a process

• It can be drawn in no. of ways like pictures, symbols, line diagram etc.

• May be drawn to represent entire process / part of process

FLOWCHART SYMBOLS


3. HISTOGRAM • It shows variation of set of data in pictorial form

• It Displays frequency distribution

• On X- axis No. of Defects

Y – axis Frequency of occurrence

• Width of all rectangles is same but height varies

• It shows the pts. where max variation is occurring.


4. PARETO CHARTS • Based on 20-80 rule based on Vilfredo Pareto 1897

• A small % of any given group (20%) accounts high amount (80%)

• It used to decide order of problems generated in industry to be tackled.

• 80% of trouble caused by 20% problems

• Shows which defect causes max. rejection

Need When analysing data about the frequency of problems or causes in

a process.

When there are many problems or causes and you want to focus

on the most significant.

When analysing broad causes by looking at their specific

components.

When communicating with others about your data.



5. Cause Effect / Fish Bone Diagram/ Ishikawa

• How an unaccepted part is produced?

• Analyze the production process against defective part produced.

• Defects may occur due to machine, method, materials, measurement, men etc.

• Steps

I. Define a problem

II. Select method i.e. CE

III. Draw the problem base and Centre arrow

IV. Specify major sources

V. Identify possible causes

VI. Analysis and Solution


6. SCATTER DIAGRAM

A scatter diagram, also called a scatterplot or a scatter plot, is a visualization of the relationship between two variables measured on the same set of individuals.

Steps involved

1. Select Two factors

2. Collect data in large nos.

3. Draw a graph with independent variable on horizontal axis and dependent variable on vertical axis.

4. If the data clearly form a line or a curve, you may stop. The variables are correlated.


7. Control Charts The control chart is a graph used to study how a

process changes over time. Data are plotted in time order.

A control chart always has a central line for the average, an upper line for the upper control limit and a lower line for the lower control limit.

Lines are determined from historical data. By comparing current data to these lines, you can draw conclusions about whether the process variation is consistent (in control) or is unpredictable (out of control, affected by special causes of variation).

Control charts help us learn more about processes

•Separate common and special causes of variation

•Determine whether a process is in a state of statistical control or out-of-control

•Estimate the process parameters (mean, variation) and assess the performance of a process or its capability



WHEN TO USE A CONTROL CHART?

1. Controlling ongoing processes by finding and correcting

problems as they occur.

2. Predicting the expected range of outcomes from a process.

3. Determining whether a process is stable (in statistical

control).

4. Analyzing patterns of process variation from special causes

(non-routine events) or common causes (built into the

process).

5. Determining whether the quality improvement project

should aim to prevent specific problems or to make

fundamental changes to the process.


X-bar and R charts

•The X-bar chart - used to detect changes in the mean between subgroups

•tests central tendency or location effects

•The R chart - used to detect changes in variation within subgroups

•tests dispersion effects

statistical quality control & sqc tools

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