7qc tools explanation

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/attribute


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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.



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The problem categories considered are :

Man, Machine, Method, Materials, Equipments & Environmental.

EFFECT

MACHINE METHOD ENVIRONMENT

MAN MATERIAL EQUIPMENT


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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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.



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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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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



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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


Interpreting Control Chart


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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



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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



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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.



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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.



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90

UCL

1 2 3 4 5 6 7 8

Sample Number

Statistic

s

UWL

LCL

LWL

One point outside

control limit



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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



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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



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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



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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



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95

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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