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7/31/2019 7qc Tools Explanation
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7 QC TOOLS
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Quality
A subjective term for which each person has his or her own
definition. In technical usage, quality can have twomeanings:
1. The characteristics of a product or service that bear on its
ability to satisfy stated or implied needs.
2. A product or service free from deficiencies.
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Can also be termed as
A measure ofexcellence
Quality
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Quality - an essential and distinguishing attribute of something.
Attribute - an abstraction belonging to or characteristic of an entity
Appearance, visual aspect - outward or visible aspect of a thing
Attractiveness, attraction - the quality of arousing interest; being attractive or something
that attracts;
Uncloudedness, clarity, clearness - the quality of clear water;
Ease, easiness, simplicity - freedom from difficulty or hardship or effort.
Suitability, suitableness - the quality of having the properties that are right for a specific
purpose.
Excellence - the quality of excelling.
Characteristic - a distinguishing quality
Simpleness, simplicity - the quality of being simple or uncompounded
Meaning of Quality
http://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/attributehttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/appearancehttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/visual%20aspecthttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/attractivenesshttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/attractionhttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/uncloudednesshttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/clarityhttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/clearnesshttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/easehttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/easinesshttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/simplicityhttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/suitabilityhttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/suitablenesshttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/excellencehttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/characteristichttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/simplenesshttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/simplicityhttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/simplicityhttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/simplenesshttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/characteristichttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/excellencehttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/suitablenesshttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/suitabilityhttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/simplicityhttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/easinesshttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/easehttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/clearnesshttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/clarityhttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/uncloudednesshttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/attractionhttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/attractivenesshttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/visual%20aspecthttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/visual%20aspecthttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/visual%20aspecthttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/appearancehttp://www.kecconnect.com/Quality%20Assurance/Shared%20Documents/Others/TPM-TQM%20-%20Study%20Material/attribute7/31/2019 7qc Tools Explanation
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Meaning of Quality
Q = PE
P = Performance or result
E = Expectations
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Many people think that quality costs money and adverselyeffects profits. But these costs are the costs of doing it wrong
first time .
Quality in the long run results inincreased profitability.
Quality, Cost & Profit relationship
Cost
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Cost
Quality and Profit : Traditional thinking
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Quality and Profit : Paradigm shift
Cost
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1.Higher production due to
improved cycle time and
reduced errors and defects
2.Increased use of machine
and resources.
3.Improved material use from
reduced scrap and rejects
4.Increased use of personnel
resources
5.Lower level of asset
investments required to
support operations.
6.Lower service and support
costs for eliminated waste,
rework and non value added
activities.
QUALITY
Higher productivity Increased
profitability
due to :
Larger sales
Lower production costs
Faster turnover
Quality and Profit
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Quality and Profit
If the organization does not offer high
quality product or service , it will soon go
out of business . But just having high
quality will not be enough , because yourcompetitors will also have the high quality.
To win , companies will need to
offer high quality for a lower price
than their competitors.This requiresorganizations to identify and reduce their
quality costs
HighQuality
Lowerprice
C2A2C
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Offer high quality for a lower price than their competitors.
Reduce quality costs
Stop producing defective thru
Process up-gradation
Improving quality of analysis to identify and eliminate root causes
Taking necessary countermeasure as when required
Usage of right analytical tools
Designing robust problem solving process
CHELLANGES
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PROBLEM SOLVING PROCESS
Evaluating solution
(6)
Implementingsolution
(5)
Selecting & planning
solution
(4)
Generating potential
solutions
(3)
Analysing problemcauses
(2)
Identifying &
selecting problem
(1)
PROBLEMSOLVING
PROCESS
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IDENTIFYING AND SELCTING PROBLEM
Write Statement of the problem(s)
Define Gap Between Actual & target
Prioritize
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ANALYSIS PROBLEM AND CAUSES
Collect Data Sort symptoms & Causes (effects)
Brain Storm
Fishbone - cause & effect analysis
Prioritize
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GENERATING POTENTIAL SOLUTIONS
Brainstorm
Build on each others ideas
Analysis potential helps & hinders
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SELECTING AND PLANNING SOLUTION
Prioritize solutions
Clarify tasks / Action plan
Resource / Costs Present proposals
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IMPLEMENTING SOLUTION
Establish controls
Maintain Commitments
Plan Contingencies
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EVALUATING SOLUTION
Monitor results
Restart Process if necessary
7 QC TOOLS
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7 QC TOOLS
Used to identify,analyze and resolve problems
Simple but very powerful tools to solve day to
day work related problems
Find solutions in a systematic mannerWidely used by Quality Circle members world
over
7 QC TOOLS
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Check sheets
Histograms
Pareto charts
Cause & effect diagram (Ishikawa diagram)
Scatter plot
Defect concentration diagram
Control charts
7 QC TOOLS
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Check sheets are formats used to collect and organize
dataData can be collected easily and concisely
Data data is collected on the characteristic of
interest.
The right data could be captured with all necessary facts
included e.g.
as when it happened ?
how many ?
what customer ?
CHECK SHEETS
TYPES CHECK SHEETS
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Check sheets for production process distribution
Defective item check sheet
Defect cause check sheet
Check sheet for work station evaluation
Check sheet for design information accuracy
Check sheet for vendor reliability
TYPES CHECK SHEETS
CHECK SHEETS
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CHECK SHEETS
Type ofdefects
Check Sub-Total
Scratch 3
Dent 7
Flow mark 11
Short Shot 2
Total 23
Component name : ABC
Date of Production:22-Aug-03
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Histogram is the Frequency data obtained from
measurements displaying a peak around a certain valueand represented in form of polls
The variation of quality characteristics is called
Distribution
Purpose of drawing a Histogram is to understand the
Population
HISTOGRAM
Population
Sample
HISTOGRAM
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12
23
43
27
9
0
50
1160-170 170-180 180-190 190-200 200-210
Histogram for distribution of Center Distance (mm)
HISTOGRAM
HISTOGRAM A HISTORY OF PROCESS OUT PUT
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HISTOGRAM A HISTORY OF PROCESS OUT PUT
0
2
4
8
10
12
14
16
6Frequency
47 48 49 50 51 52 53 54kg
Distribution
PARETO CHART
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Based on 80/20 rule (or ABC analysis)
Pareto(V.Pareto,an Italian economist) discovered this universal
law-80% of anything is attributed to 20% of its causes 80% of the
wealth is held by 20% of the population.
80% of our income goes into 20% of our needs.
80% of road accidents occur on 20% of the road. 80% of the absenteeism in a company is due to 20% of
workmen
Significant few & in-significant many
PARETO CHART
PARETO CHART
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PARETO CHART
Pareto analysis begins by ranking problems from highest to
lowest in order to fix priority
The cumulative number of problems is plotted on the vertical
axis of the graph against the cause/phenomenon
Pareto by Causes e.g. Man,Machine,Method etc
Pareto by Phenomenon e.g.Quality,Cost,Delivery
Tells about the relative sizes of problems indicates an
important message about biggest few problems, if corrected,
a large % of total problems will be solved
PARETO ANALYSIS
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63.8
81.4
96.2 100.0
0
500
1000
1500
2000
2500
3000
Noofp
eices
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Cum.
Percentage
DEFECT QTY 2064.0 567.0 480.0 122.0
CUM % 63.8 81.4 96.2 100.0
SHORT SHOT SILVER SINK MARK FLASH
PARETO ANALYSIS
CAUSE EFFECT (FISH BONE) DIAGRAM
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CAUSE n EFFECT (FISH BONE) DIAGRAM
This diagram (resembles skeleton of a fish) helps to separate out
causes from effects and to see problem in its totality
Its a systematic arrangement of all possible causes,generatedthru brain storming
This can be used to :
Assist individual / group to see full picture.
Serve as a recording device for ideas generated.
Reveal undetected relationships between causes.
Discover the origin/root cause of a problem
Create a document or a map of a problem which can be posted in the work
area.
CAUSE n EFFECT (FISH BONE) DIAGRAM
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The problem categories considered are :
Man, Machine, Method, Materials, Equipments & Environmental.
EFFECT
MACHINE METHOD ENVIRONMENT
MAN MATERIAL EQUIPMENT
CAUSE n EFFECT (FISH BONE) DIAGRAM
SCATTER DIAGRAM
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SCATTER DIAGRAM
The scatter diagram is used for identifying the relationships andperforming preliminary analysis of relationship between any two
quality characteristics.
Clustering of points indicate that the two characteristics may be
related e.g.Increasing in component weight with increase in hold time
during plastic injection molding ( + ve co-relation)
Increase in toughness components with decreasing injection
pressure (-ve co-relation) during molding
SCATTER DIAGRAM (POSITIVE CORRELATION)
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SCATTER DIAGRAM (POSITIVE CORRELATION)
SCATTER DIAGRAM (NEGATIVE CORERLATION)
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SCATTER DIAGRAM (NEGATIVE CORERLATION)
SCATTER DIAGRAM (NO CORERLATION)
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SCATTER DIAGRAM (NO CORERLATION)
DEFECT CONCENTRATION DIAGRAM
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DEFECT CONCENTRATION DIAGRAM
This is used to understand the potential defect prone area of
the parts produced The Concentration Diagram check sheet carries the diagram
of the problematic part,defects whenever observed to beupdated in the same using tally marks
Based on the distribution of defects countermeasures are taken
at process/system level This tool is very useful to solve problems like Scratch,
Dent,Breakage thru handling improvement
For plastic molded parts this tool is used to identify stress
points,weak joints,effect of gate shape/position on the qualityof parts etc.
DEFECT CONCENTRATION DIAGRAM
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DEFECT CONCENTRATION DIAGRAM
Component name : XYZ
Concentration diagram for Scratches produced ion 21-Aug-03
Total no of defective produced is 11 Nos
Area of
concern
Control Chart
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Control Chart
Quality control charts, are graphs on which the quality
of the product is plotted as manufacturing or servicingis actually proceeding.
It graphically, represents the output of the process and
uses statistical limits and patterns of plot, for decision
making
Enables corrective actions to be taken at the earliest
possible moment and avoiding unnecessary
corrections.
The charts help to ensure the manufacture of uniform
product or providing consistent services which
complies with the specification.
Elements of Typical Control Chart
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Elements of Typical Control Chart
1. Horizontal axis for sample number
2. Vertical axis for sample statistics e.g.mean, range, standard deviation of sample.
3. Target Line
4. Upper control line
5. Upper warning line
6. Lower control line
7. Lower warning line
8. Plotting of sample statistics
9. Line connecting the plotted statistics
Elements of Typical Control Chart
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1 2 3 4 5
Target
Lower control line
Upper warning line
Lower warning line
Sample Number
Upper control line
Lower control line
SampleS
tatistics
Elements of Typical Control Chart
Interpreting Control Chart
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Interpreting Control Chart
The control chart gets divided in three zones.
Zone - 1 If the plotted point falls in this zone, do notmake any adjustment, continue with the process.
Zone - 2 If the plotted point falls in this zone thenspecial cause may be present. Be careful watch forplotting of another sample(s).
Zone - 3 If the plotted point falls in this zone thenspecial cause has crept into the system, and correctiveaction is required.
Zones for Mean Control Chart
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Zones for Mean Control Chart
1 2 3 4 5 6 7
Sample Number
UCL
Target
LCL
UWL
LWL
Zone - 3
SampleMe
an
Zone - 2
Zone - 3
Zone - 2
Zone - 1
Action
Action
Warning
Warning
Continue
ContinueZone - 1
Interpreting Control Chart
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UCL
1 2 3 4 5 6 7 8
Sample Number
Statistic
s
UWL
LCL
Target
LWL
p g
Point outside the Control limit
Control Chart Views Process in Real Time
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Control Chart Views Process in Real Time
Time Intervals
Rang
e
Mean
LCLx
Output of the process in real time
Target
Target
UCLx
UCLr
Change in Location of Process Mean
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Change in Location of Process Mean
43 48 49 50 51 52 5344 45 46 47
Process withmean at Target
Process withmean at more
than target
Process with
mean at less
than target
Case When Process Mean is at Target
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Case When Process Mean is at Target
43 48 49 50 51 52 5344 45 46 47
Target ProcessMean
Chances of getting a reading beyond U & L is almost nil
42
UL
- 3 s +3 sU - L = 6 s
Case - Small Shift of the Process Mean
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43 48 49 50 51 52 5344 45 46 47
Target
ProcessMean
Chances of getting a reading outside U is small
Small shift in process
42
Shaded areashows the
probability of
getting
a reading
beyond U
UL
U-L = 6 s
Case - Large Shift of the Process Mean
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Process
Mean
g
43 48 49 50 51 52 5344 45 46 47
Target
Chances of getting a reading outside U is large
Large shift in process
42
Shaded areashows the
probability of
getting
a reading
beyond U
UL
U-L = 6 s
Change in Spread of Process
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g p
43 48 49 50 51 52 5344 45 46 47
Larger spread due
to special causes
Spread due
to common causes
Special cause & Common cause
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Special cause & Common cause
Special/ Assignable cause : Causes due to negligence
in following work instructions, problem in machinesetc.This types of causes are avoidable and cannot
be neglected.
Common cause : Causes which are unavoidable and
in-evitable in a process.It is not practical to eliminate
the Chance cause technically and economically.
Most Commonly Used Variable Control Charts
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y
To track the accuracy of the process
- Mean control chart or x-bar chart
To track the precision of the process
- Range control chart
Control Chart
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PART NAME GLASS RUN PART NO : MODEL : Page
THICKNESS SPEC MIN 1.10 TO 1.50 MAX REASON : PROCESS CAPABILITY STUDY AUDIT DATE 25/9/01
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 n d2 A2 D4
1 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.60 1.50 1.60 1.50 1.60 1.55 1.60 1.55 1.50 1.50 1 1.123 2.66 3.27
2 1.50 1.50 1.50 1.53 1.50 1.50 1.50 1.50 1.50 1.55 1.60 1.55 1.55 1.60 1.55 1.45 1.60 1.50 1.50 1.48 2 1.128 1.88 3.27
3 1.60 1.48 1.50 1.50 1.48 1.50 1.50 1.50 1.50 1.55 1.50 1.55 1.50 1.55 1.50 1.50 1.50 1.55 1.60 1.55 3 1.693 1.02 2.57
4 1.50 1.48 1.52 1.50 1.53 1.50 1.50 1.50 1.45 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.60 1.60 1.50 4 2.059 0.73 2.29
5 1.50 1.50 1.60 1.50 1.50 1.50 1.55 1.55 1.45 1.55 1.55 1.50 1.50 1.50 1.50 1.50 1.45 1.50 1.55 1.55 5 2.326 0.58 2.11
SUM X SUM X1+..+Xn 30.37
X 1.52 1.49 1.52 1.51 1.50 1.50 1.51 1.51 1.48 1.53 1.55 1.52 1.53 1.53 1.53 1.50 1.53 1.54 1.55 1.52 X SUM X1+..+Xn 1.519
R 0.10 0.02 0.10 0.03 0.05 0.00 0.05 0.05 0.05 0.05 0.10 0.05 0.10 0.10 0.10 0.10 0.15 0.10 0.10 0.07 R SUM R1+..+R 0.074
SIGMA R/d2 0.032
3 SIGMA 3 * R/d2 0.095
6 SIGMA 6 * R/d2 0.190
Cp = 2.11
Cpk=
MIN OF -0.20
Cpu OR
Cpl 4.41
Cpk =USL 1.500
LSL 1.100
FOR X
UCL = X + A2.R 1.561
LCL = X - A2.R 1.476
FOR R (D3 = 0)
UCL = D4.R 0.155
LCL = D3.R 0.000
PROCESS STATAUS
CONTROLLEDNOT CONTROLLE
XYZ Ltd
O
-0.050.000.050.100.150.200.25
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
R
-CHART
R UCL LCL CL
1.4001.4201.4401.4601.4801.5001.520
1.5401.5601.5801.600
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
X
-CHA
RT
X UCL LCL CL
How to draw?
Summary of Effect of Process Shift
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y
When there is no shift in the process nearly all the
observations fall within -3 s and + 3 s.
When there is small shift in the mean of process some
observations fall outside original -3 s and +3 s zone.
Chances of an observation falling outside original -3 sand + 3 s zone increases with the increase in the shift of
process mean.
Our Conclusion from Normal Distribution
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When an observation falls within original +3 s and -3 s
zone of mean of a process, we conclude that there is no shift
in the mean of process. This is so because falling of an
observation between these limits is a chance.
When an observation falls beyond original +3 s and -3 szone of process mean, we conclude that there is shift in
location of the process
Interpreting Control Chart
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Because the basis for control chart theory follows the normal
distribution, the same rules that governs the normal distribution
are used to interpret the control charts.
These rules include:
- Randomness.- Symmetry about the centre of the distribution.
- 99.73% of the population lies between - 3 s of and + 3 s thecentre line.
- 95.4% population lies between -2 s and + 2 s of the centreline.
Interpreting Control Chart
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p g
If the process output follows these rules, the process
is said to be stable or in control with only common
causes of variation present.
If it fails to follow these rules, it may be out of
control with special causes of variation present.
These special causes must be found and corrected.
Interpreting Control Chart
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UCL
1 2 3 4 5 6 7 8
Sample Number
Statistic
s
UWL
LCL
LWL
One point outside
control limit
Interpreting Control Chart
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UCL
1 2 3 4 5 6 7 8
Sample Number
Statistic
s
UWL
LCL
LWL
Two points out of three consecutive points
between warning limit and corresponding
control limit
Interpreting Control Chart
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UCL
1 2 3 4 5 6 7 8
Sample Number
Statistic
s
UWL
LCL
LWL
Two consecutive points between warning limit and
corresponding control limit
Interpreting Control Chart
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UCL
1 2 3 4 5 6 7 8
UWL
LCL
LWL
Seven consecutive points on one
side of the centre line
Sample Number
Statistic
s
Interpreting Control Chart
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UCL
1 2 3 4 5 6 7 8
Sample Number
Statistic
s
UWL
LCL
LWL
Seven consecutive points having
upward trend
Interpreting Control Chart
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UCL
1 2 3 4 5 6 7 8
Sample Number
Statistics
UWL
LCL
LWL
Seven consecutive points having
downward trend
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