Spc training

Quality Improvement: Problem SolvingPrepared By: Mr.Prashant Kshirsagar
Senior Manager-QA

-: Objective of
Training :-
• History of SPC
• Basics of SPC
• Benefits of SPC
• Importance of Product Quality in
Business
• PDCA Approach in SPC
• 7 QC tools with excel software
• Benefits of each tool in application
Quality Improvement: Problem Solving

SPC: Quality Consistency & Improvement

In 1924, a man at Bell Telephone
Laboratories was conducting
research on methods to improve
quality and to lower costs. He
developed the concept of control
with regard to variation, and came
up with Statistical Process Control
Charts which provide a simple way
to determine if the process is in
control or not. His name was
Dr.Walter Shewart. He eventually
published a book titled “Statistical
Method from the Viewpoint of
Quality Control” (1939).
-: History of SPC:-

 What is Process?
-It is a series of actions/steps taken in combination
of material, people, equipment and procedures to
achieve a particular product.
 What is Statistics?
-The science of collecting, organizing, analyzing
and interpreting data in order to make a decision.
-:BASICS OF STATISTICAL
PROCESS CONTROL:-

 Statistical process control (SPC): defined as the use
of appropriate statistical techniques to understand our process & control
a process or production method.
WHAT IS STATISTICAL
PROCESS CONTROL?
It helps to see, “When a process is working
correctly & when it is not.”
 Why do we need to control the process?
a) To discover the issues due to variation in
process & to find the solutions b) To reduce
defects c) To achieve consistency in Process
d) To satisfy customer
In Process Control, the focus is on process
inputs and output seems un-important
because, a) Output can’t be changed directly
b) Only inputs can be directly changed
c) The quality of final output depends
entirely on the inputs. The output provide
information about process capability for the
customer’s point of view.

• Reduced scrap, rework, and
warranty claims
• Maximized productivity
• Improved resource utilization
• Increased operational
efficiency
• Decreased manual inspections
• Improved client satisfaction
• Reduced Manufacturing Costs
• Improved & Consistent
Product Quality
• Improved Safety
• Improved Energy Saving
What are the
Benefits of SPC?

Why Is Quality Important
for a Business? (Video)
• Meet Customer Expectations: Customer expect you to deliver Quality products so that
delivered product should work well into their application. Customers aren’t going to
choose you solely based on Price, but often on Quality. In fact, studies have shown that
customers will pay more (e.g. Mobile) for a product or service. If you fail to meet
customers' expectation then, they will quickly look for alternatives.
• Satisfy Customer & Increase Profitability: Quality is critical to satisfying your customers
and retaining their loyalty so they continue to buy from you in the future. Quality
products make an important contribution to long-term revenue and profitability. They
also enable you to charge and maintain higher prices.
• Establish Your Reputation: Quality reflects on your company’s reputation. Poor quality
or product failure that results in a product recall campaign can lead to negative publicity
and damage your reputation.
• Meet or Exceed Industry Standards: It helps to achieve quality standards accreditation
e.g. ISO 9001 and IATF16949 etc. It helps you to win new customers giving prospects
your company’s ability to supply quality products.
• Manage Costs Effectively: Poor quality increases costs. Cost of analyzing non-
conforming goods or services to determine the root causes and retesting products after
reworking them. In some cases, you may have to scrap defective products and pay
additional production costs to replace them. If defective products reach customers, you
will have to pay for returns and replacements and, in serious cases, you could incur
legal costs for failure to comply with customer or industry standards.

-: PDCA
APPROACH :-
Definition of problem
Analysis of problem
Identification of causes
Planning countermeasure
Implementation
Confirming effectiveness
Standardizations
WHAT
HOW
WHYPLAN
DO
CHECK
ACT

-: 7 Quality Control Tools:-
1. Check sheets
2. Stratification
3. Pareto chart
4. Cause and
effect diagram
5. Histogram
6. Control chart
7. Scatter
diagram

-: 1st Quality tool:
Check Sheet :-

 What is the purpose of Check Sheet?
a) Tool for collecting and organizing measured or
counted data b) Data collected can be used as input
data for other quality tools c) Data Collections are
based on answering the questions of What, Why,
When, Where, Who & How (5W1H)
 Why check sheet is needed?
- As per “Quality Management principle” of IATF
16949: 2016 & ISO 9001: 2015 is focusing on factual
approach for decision making. Without check sheet there
is no way to identify problems, continuous improvement
& ensure to meet the customer requirement.
Hence, check sheet is needed.
 When to Use a Check Sheet?
a) To collect data repeatedly by the same person or at
the same location b) To collect data on the patterns of
events, problems, defects, defect location, defect causes,
etc. c) To collect data from a production process
-: Check
Sheet :-
(video)

Excel hyperlinkRevised format of
Inprocess report of september
19.xlsx
Benefits:
• Collect data in a
systematic and organized
manner
• To determine source of
problem
• To facilitate/simplify
classification of data
(stratification)
• It helps to ensure
successful analysis of the
problem SPC: Quality Consistency & Improvement
-: Check Sheet :-

-: 2nd Quality Tool:
Stratification :-

 Definition:- It is a system of formation of layers,
classes, or categories. Data collected using check
sheets need to be meaningfully classified. Such
classification helps gaining a preliminary
understanding of relevance and dispersion of
data so that further analysis can be planned to
obtain a meaningful output. Meaningful
classification of data is called stratification.
When to Use Stratification?
- When data come from several sources or
conditions, such as shifts, days of the week, suppliers
or population groups.
- When data analysis may require separating different
sources or conditions.
- Example: 1) Variation of object in three different
machines 2) Age stratification of two different country
3) Division of society, etc.
- Excel hyperlinkIMP Stratification-diagram trial
template.xlsx
-: Stratification :-

-: 3rd Quality Tool:
Pareto Chart:-

• Vilfredo Pareto (1848-1923) Italian
economist developed this principle.
• 20% of the population has 80% of
the wealth
• Juran used the term “vital
(Significant) few, trivial (In-
significant) many.” He noted that
20% of the quality problems caused
80% of the dollar loss.
• Purpose: The purpose of a Pareto
diagram is to separate the significant
aspects of a problem from the trivial
ones.
-: Pareto Principle (Video) :-

-: Pareto
Chart
Benefit :-
Excel hyperlinkIMP Pareto for final
NC internal rejection.xlsx
 Benefits:
 Improved Decision Making
 Improved focus on the inputs that
will have the greatest impact.
 Enhanced Problem-Solving Skills
 Enhanced Organizational
Efficiency
 Provides an easy way to compare
before and after snapshots to verify
that any process changes had the
desired result.

-: 4th Quality Tool:
Fishbone Diagram :-
SPC: Quality Consistency &
Improvement

-: Fishbone Diagram :-
The Cause and Effect diagram analysis was first developed by
Professor Kaoru Ishikawa of the University of Tokyo in the 1940s’,
It is also known as the ‘Fishbone Diagram’ or the ‘Ishikawa
Diagram’ or the ‘Cause-and-Effect Diagram’.
 Description - The fishbone diagram identifies many possible causes for an effect
or problem. It can be used to structure a brainstorming session. It immediately
sorts ideas into useful categories.
 When to use a Fishbone Diagram?
- When identifying possible causes for a
problem. Especially, when a team’s thinking
tends to fall into roots. It can be identify by
‘6M’ techniques:
i) Methods
ii) Machines (Equipment)
iii) Manpower (People)
iv) Materials
v) Measurement
vi) Management, Environment… etc., SPC: Quality Consistency & Improvement

-: -: Fishbone Diagram
Example :-
Excel hyperlink5 Why analysis.xlsx
 Rating of identified causes:-
- Degree of actual cause: Very likely/possible (V); Somewhat likely (S); Not likely (N)
- Easy to check: Very easy (V); Somewhat easy (S); Not easy (N)
The causes that receive VV responses are investigated first since
these are most likely to be the cause of the problem and are the
easiest to check. In this case, the "Battery" received the only VV.

Excel hyperlinkIMP Fish Bone
diagram template.xlsx
Benefits:
• Breaks problems down into bite-
size pieces to find root cause
• Fosters/Encourage team
work/participation
• Common understanding of factors
causing the problem
• Road map to verify picture of the
process
• Follows brainstorming relationship
• Indicates possible causes of
variation
• Increases process knowledge
• Diagram demonstrates knowledge
of problem solving team
-: Fishbone
Diagram :-

-: 5th Quality
Tool:
Histogram :-
Product of TWO greek word i.e.
“Histo”+ “gram”= Histogram
‘Anything + ‘something
set written’
Upright’
Bin=Range
Frequency

-: Histogram :-
• Description -
Histograms are graphs of a distribution of data
designed to show centering, dispersion (spread) &
shape (relative frequency) of the data. They are used to
understand "Is process capable?”
- What is of Process capability?
It is the ability of a process to meet customer
requirements.
• When to Use a Histogram?
1) When the data are numerical 2) Want to see the
shape of data’s distribution 3) When analyzing
whether a process can meet the customer’s
requirements 4) Analyzing the output from a
supplier’s process 5) To see the process change has
occurred from one time period to another.
- Process Starting: Pp & Ppk are used for preliminary
process studies & based on a small sample of the process.
First introduced in 1891

-: Plotting of
Histogram :-
Plotting of Histogram:-
Excel hyperlinkIMP Capability Study with Histogram Excel Template (Recovered).xlsx
 Sample Size: A histogram works best when the sample size
is at least 20Nos or more. If the sample size is too small, each
bar on the histogram may not contain enough data points to
accurately show the distribution of the data.
 No. of Bars in Histogram:
As a thumb rule, the no. of bars in histogram are the square root of the number of data points
by rounding the value. For example: a) 25 data points = 5 bars b) 100 data points = 10 bars
Number of
Data Points
from report
Number of
Bars in
Histogram
20-50 6
51-100 7
101-200 8
201-500 9
501-1000 10
1000+ 11-20
Value outside spec
1σ = 32%
2σ = 5%
3σ = 0.3%
50% 50%
2% 14% 34% 34% 14% 2%

Normal Distribution: The data is evenly distributed about
the center of the data i.e. called symmetrical distribution.
Left skew: The data in the following graph are left-
skewed. Most of the sample values are clustered on the
left side of the histogram.
Right skew: The data in the following graph are right
-skewed. Most of the sample values are clustered on the
right side of the histogram.
Outliers: The isolated bars at the ends identify outliers.
The data values are far away from other data values, can
strongly affect your results. Try to identify the cause of
any outliers. Correct any data-entry errors/measurement
errors Or any special causes. Then, repeat analysis.
-: Interpretation of
Histogram :- LSL USL
LSL USL
LSL USL
LSL USL

Definitions :-
- Process Capability (Cp):
Cp is the capability, if the process was
perfectly centered between the specification
limits. A simple and straightforward
indicator of process capability.
- Process Capability Index (Cpk): Cpk is the
capability index, if the mean is centered
between the specification limits or not.
The ‘k’ stands for ‘Centralizing Factor.’
Example: “If you hunt or shoot targets with
arrow or gun try this analogy. If your shots are
falling in the same spot forming a good group
this is a high Cp, and when the sighting is
adjusted so this tight group of shots is landing
on the bulls-eye, you now have a high Cpk.”
“You must have a Cpk of 1.33 [4 sigma] or
higher to satisfy most customers.”
-: Histogram :-

-: Histogram :-
Stability
Capability STABLE
(In Control
UNSTABLE
(Out of Control)
CAPABLE
of meeting
specifications
Healthy Situation Situation OK but not
sable. Be alert until
process stable.
INCAPABLE
of meeting
specifications
Evaluate a new
process approach or
change the specs.
Major process
improvement is
needed.
Excel hyperlinkIMP Process
Capability Calculation.xlsx
Benefits:
• Allows you to understand at a
glance the variation that exists
in a process
• The shape of the histogram will
show process behavior
• The shape and size of the
dispersion will help to identify
hidden sources of variation
• Used to determine the
capability of a process
• Starting point for the
improvement process

-: 6th Quality Tool:
Control Chart :-

-: Control
Chart :-
 Purpose:-
The control chart is to study how a
process changes over time.
 Guidelines:-
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. These
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).
UCL
LCL
UCL
LCL
UCL
LCL

-: Control
Chart :-
 When to Use a Control Chart ?
- When controlling ongoing processes by
finding and correcting problems as they occur.
- When predicting the expected range of
outcomes from a process.
- When determining whether a process is
stable (in statistical control).
- When analyzing patterns of process variation
from special causes (non-routine events) or
common causes (built into the process).
-Excel software: Excel hyperlinkIMP Software
Average & Moving Range Control Chart.xlsx
-Manual Plotting-1: Excel hyperlinkIMP
Manual Individual X-bar and Moving range
chart.xlsx
-Manual Plotting-2: Excel hyperlinkIMP X-
bar and Range Control Chart example.xlsx

-: Types of Control Chart :-
e.g.Out of 150nos total 15nos defective =10%
Excel hyperlinkIMP
Attribute control c-
chart.xlsx
No. of children,
No. of invoice,
No. of defects, etc.

-: Interpretation of
Control Chart :-

 Common Cause of Variance: Also referred to as
“Natural Problems, “Predictable” and “Random Cause”
• Reducing common-cause variation usually requires
making fundamental/essential changes in your process
• Addressing the common cause variation will improve
the process performance.
• e.g. lack of clearly defined standard procedures, poor
working conditions, measurement errors, normal wear
& tear of drawing die, computer response times, etc.
-: Control
Chart :-
 Special cause of Variance: Also referred to as
assignable/Special cause and unpredictable variation:
• Get timely data so that you see the effect of the
assignable cause soon after it occurs.
• As soon as you see something indicates that an assignable
cause of variation has happened, search for the cause by
using, “Fishbone diagram & why-why analysis”
• Change tools to compensate for the assignable cause.
E.g. machine malfunctions/breakdown, a computer crashes,
there is a power cut, etc.
Drawing die wear
Wire Breakage
Stop
Warning
Run

SPC: Quality
Consistency &
Improvement
-: Control
Chart :-Benefits:
 Predict process out of control and out of
specification limits
 Distinguish between specific, identifiable
causes of variation
 Can be used for statistical process control
 Control charts allow operators to detect
manufacturing problems before they occur,
this greatly reduces the need for product
rework or additional product expenditures.
 Control charts serve as the early warning
detection system, telling you that now is the
time to go in and make a change.
 After analyzing a control chart, operators need
to determine whether to “do something” (i.e.
adjust a behavior in the process) or “do
nothing,” (i.e. let the process run as is).

-: 7th Quality tool:
Scatter Diagram :-

Purpose:
To identify the correlations
between a quality characteristic
& a factor that might be driving it
A scatter diagram shows the
correlation between two
variables in a process. These
variables could be a Critical To
Quality (CTQ) characteristic.
-: Scatter Diagram :-

-: Scatter Diagram :-
Procedure: Excel hyperlinkIMP
scatter_plots.xlsx
The more the points plotted are closer to the line, the higher is the
degree of correlation. The degree of correlation is denoted by “r”.
- Perfect Positive Correlation (r=+1): The correlation is said to be
perfectly positive when all the points lie on the straight line rising
from the lower left-hand corner to the upper right-hand corner.
- Perfect Negative Correlation (r=-1): When all
the points lie on a straight line falling from the
upper left-hand corner to the lower right-hand corner,
the variables are said to be negatively correlated.
- No Correlation (r= 0): The variable is said to
be unrelated when the points are haphazardly
scattered over the graph and do not show any
specific pattern. Here the correlation is absent
and hence r = 0.

-: Benefits of Scatter Diagram :-
-: School Scatter plot analysis :-
•It shows the relationship
between two variables.
•It is the best method to
show you a non-linear
pattern.
•The range of data flow,
i.e. maximum and
minimum value, can be
easily determined.
•Observation and reading
is straightforward/direct.
-:Car Speed Scatter plot analysis:-

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