Quality Tools 2

The 7 Basic Quality Tools

Michele Cano

Agenda

• Introductions• Basic Tools – Ishikawa• Exercises• Discussion & Video

………………….Lunch……………………….• Problem solving (Global 8D and TRIZ)• Case study • Discussion

Why use tools?

• Measure

• Improve

What are they?

The seven basic tools according to Ishikawa are:• Check sheets• Flow charts• Graphs & Histograms• Pareto diagram• Cause and effect diagram• Scatter diagram• Control chart

1.Check sheets

• What is a check sheet?

• A form or sheet used to record data.

Function of Check Sheets

According to Ishikawa 1982, check sheets have the following functions:

1. Production Process distribution checks

2. Defective item checks

3. Defective location checks

4. Defective cause checks

5. Check-up confirmation checks

6. Others

Example of a simple check sheet. (for car valet operation)

Car type

Car registration

Ford Focus

W357 PHR

Interior vacuumed √

Upholstery cleaned √

Dash board cleaned √

De odorised √

Body washed √

Washed waxed & Polished √

Under car washed √

Wheels washed √

Tyres blacked √

Comments: Front bumper badly scratched on delivery, this can not be covered

Performed / Checked by J Bloggs

Date 2 May 2008

Example of a simple process check sheet. (attributes)

Model XYZC217 Batch

failures 1 2 3 4 5 6 7 8 9 10

Power up1 2 1              

Boot up6 4 2 1         2  

Sink test2   1     1     1  

Case damage  1   1     2      

Keyboard damage                   

Monitor damaged    1       2      

Bundled s/w included  3     1         3

Checked bypj

am jj [j lm

lm

rm pj

am pj

Flowcharts

PROCESS MAPPING

• Process mapping is an essential first step.

• It identifies all of the process activities, sequence and responsibilities.

• This can either be in a written format, or as a flowchart.

Flowcharts

PROCESS MAPPING (Written format)Enquiry handling Activity Responsibility Associated documents

1. Customer enquiry received and logged onto system

Sales Director Customers enquiry Customers drawing Work instruction S10

2. Enquiry briefly overviewed and allocated to sales estimator for through.

Sales Director

3. If it cant be done, return to customer

Sales Director Customers enquiry Customers drawing

4. If it has been made before, prepare a new quote based on previous job and current pricing, otherwise go to step 10.

Sales Director Customers enquiry Customers drawing Previous job file Current price list

5. Send to customer for acceptance

Sales Director Quotation

6. Review quote Customer Quotation 7. Quote is acceptable Customer Quotation 8. Log as order and

create order package

Quotation Customer drawing Work instruction S30

9. Pass to Production control

Sales Director Order package

10. Allocated to sales estimator

Sales director Customers enquiry Customers drawing

11. . Etc. 12.

13. 14. 15. 16.

Flowcharting

• Flowcharting is a graphical tool for analysing processes.

• Constructing flowcharts leads to a better understanding of processes.

• Better understanding of processes is a essential for improvement

Flowcharts

Some standard symbols

Start or end

An activity

a decision point in the process.

a point at which the flowchart connects with another process.

An off page connection

All records are identified

FLOWCHART

SM01 Enquiry Handling / Quotation Process

Sales director EstimatorCustomer

Customer sendsenquiry

Sales departmentreceives enquiry

Enquiry enteredinto the electronic

Quote log &Unique serial

number entered

Can thisenquiry beQuoted ?

Enquiry allocatedto Estimator

No

Quote preparedfrom Price guide

Quote customer

Customerinformed that we

are unable toquote

No

Prepare Quote

Have theitem (s) beenmade before?

Yes

Raise estimatesheet & plan

process

Organize contractreview to cover

QualityContractual &Manufacturing

aspects

Exercise

Draw a flowchart for one of the following processes:

– Making a cup of coffee

– Enrolling students

– Wiring a plug.

3. Graphs & Histograms

Graphs, either presentational or mathematical are used to allow understanding and analysis of collected data sets.

Graphs

BAR CHARTS

• This is the data set totalled up and shown graphically.

• It immediately identifies the major defects for all to see.

Defects

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Graphs

• The below graph shows a factory output for February. This time it shows specific dates which could be analysed.

0102030405060708090

100

01/0

2/03

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2/03

Output %

Average

Feb production output

Graphs

• The graph below shows the major cause for customer complaint, the use of the pie chart and the colours enforce the message.

Customer complaints 2007by qty

20

60

5

15

Product quality

Shipped Late

Shipped early

Shipped wrong goods

Rules for Graphing

• Use Clear titles an indicate when the data was collected

• Ensure the scales are clear, understandable and represent the data accurately.

• When possible use symbols for extra data.

• Always keep in mind the reason why the graph is being used.

Exercise Graphs

• You are the marketing director of XZY automotive, a new Scottish company. You have organised a local survey to rate your car against other small cars.

• 30 people were polled and the results are shown below.

• Xzy, ka, Clio, Clio, ka, fiesta, xzy, ka, 206, xzy, fiesta, fiesta, xzy, polo, fiesta, 206, 206, polo, 206, fiesta, fiesta, fiesta, polo, xzy, polo, fiesta, xzy, xzy, ka, xzy.

• You recognise the power that graphs produce. And you have decided to Graph the results as part of you marketing drive. Explain your choice of graph.

What is a Histogram?

• The Histogram is a graphical representation of data that is a dimensional measurement of one feature.

What is a Histogram?

• This is the computer defect data set totalled up and shown graphically, but is it a histogram?

Defects

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Type

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Checks/only record failures Total

Power up 4

Boot up 15

Sink test 5

Case damage 4

Keyboard damage 0

Monitor damaged 3

Bundled s/w included 7

What is a Histogram?

• The answer to the previous question is NO

• The Histogram is a graphical representation of data that, is a dimensional measurement of one feature.

When is a Histogram Used?

• To look at one particular set of results

• To check for patterns in a process

• To examine large amounts of data

Histograms• The following data was collected when measuring the bow

(warp) of a plastic component. The specification is 0 to 8 x10-3 mm.

• At a glance this tells you very little, but it can be plotted as a histogram because we have quantities data with target limits.

Bow measurements2 5 8 8 2

4 6 6 6 4

4 7 6 6 4

8 7 7 5 9

0

1

2

3

4

5

6

0 1 2 3 4 5 6 7 8 9

Mor

e

ThouF

req

ue

nc

y

HistogramsBin Frequency

0 0

1 0

2 2

3 0

4 4

5 2

6 5

7 3

8 3

9 1

More 0

What is a Histogram?

ExerciseExercise

• Sort the following data into appropriate sets, then plot them.

• The limits are 3 volts ± 0.1

• What can you deduce from this?

What is a Histogram?

ExerciseExercise

3.00 2.80 2.85 2.80 2.853.00 2.80 2.75 2.65 2.902.80 2.85 2.90 2.95 2.852.85 2.90 2.85 3.00 2.902.85 3.05 2.95 3.05 2.952.85 2.95 3.00 2.80 2.852.90 2.70 2.85 2.85 2.902.90 2.90 2.80 2.85 2.852.85 3.00 2.85 2.85 2.752.80 2.90 3.05 2.85 2.85

4. Pareto Analysis

Pareto

What is Pareto Analysis?

• Pareto analysis is a method for prioritising data.

• It consists of a Bar Chart displayed either in order of frequency or relative cost.

Pareto

Example:

The information to be represented on a Pareto diagram should alreadyhave been collected in some sort of record.

Houshold repairs over the last 10 years

Problem frequencyCost £ per occurance

Total cost £

Light bulb fails 100 0.6 60Broken central heating pump 1 190 190Broken window 2 50 100Leaking taps 16 2.5 40Faulty central heating boiler 1 3000 3000Leaking radiators 3 15 45

Pareto

Pareto ChartThe data are then displayed graphically. Firstly in terms of frequency.....

House repairs 1998-2008

020406080

100120

Ligh

tbu

lb f

ails

Leak

ing

taps

Leak

iung

radi

ator

s

Bro

ken

win

dow

Bro

ken

cent

ral

heat

ing

Fau

ltyce

ntra

lhe

atin

gFault

Occ

ura

nce

frequency

Cum %

Pareto

... and then by cost.

House repairs 1998-2008 Total cost £

0500

100015002000250030003500

Faultycentralheatingboiler

Brokencentralheatingpump

Brokenwindow

Lightbulb fails

Leakiungradiators

Leakingtaps

Total cost £

Exercise Pareto

Plot the following data as a Pareto chart

Model XYZC217 Batch number

Checks/only record failures 1 2 3 4 5 6 7 8 9 10

Power up1 2 1              

Boot up6 4 2 1         2  

Sink test2   1     1     1  

Case damage  1   1     2      

Keyboard damage                   

Monitor damaged    1       2      

Bundled s/w included  3     1         3

Checked bypj am jj [j lm lm rm pj am pj

6. Cause and Effect Diagrams (Ishikawa)

A method for the identification of the root cause of a problem.

cause and effect

What is Brainstorming?

• A way to get creative ideas.

• A way to get everyone’s views.

• A way to generate alternatives.

cause and effect

Potential Uses (Brainstorming)

• For identifying areas for improvement.

• For finding potential causes of problems.

• For developing possible preventive actions.

cause and effect

Some Guidelines (Brainstorming)

• Give wild and unusual ideas.

• Aim for quantity.• Build on ideas of

others.• Encourage

participation.

• Evaluate or criticise.• Stop to soon.• Allow domination or

idea ownership.

Do’s Don'ts

cause and effect

Ranking

Ranking can be used after brainstorming to assess the teams Priority position on a list of ideas. The basic procedure is:

•Each person privately selects 3 to 5 items from the list•Each person ranks their selection in order of priority•The marks are then totalled for each item•The item having the highest total is then judged to have the highest priority

cause and effect

What is a Cause and Effect Diagram?

• The process of a cause and effect diagram consists of defining an effect in terms of possible causes and is normally carried out in the form of a Brainstorming session.

• The principal causes are typically Man, Materials, Methods or Machines.

• These are then reduced to sub-causes.

• Finally, the most likely causes are then circled and are subject to future examination.

• These relationships are displayed pictorially in the form of a fishbone structure.

cause and effect

Layout:

Man Method

Materials Machines

Effect

Sub-Cause

Sub-Cause Sub-Cause

Sub-CauseSub-CauseSub-Cause

6. Scatter Diagrams

A method for the identification the relationship (effect) between two

factors (Causes).

Scatter diagrams

What is it used for?

• Validating "hunches" about a cause-and-effect relationship between two variables.

• Displaying the direction of the relationship (positive, negative, etc.)

• Displaying the strength of the relationship

Scatter diagrams

Constructing scatter diagram

• In order to construct a scatter diagram you need two variables to be plotted against each other. One on the x axis the other on the y axis.

• The relationship is then plotted.

Variable a

Var

iabl

e b

relationship

Scatter diagrams

Constructing scatter diagram

• This process is continued, showing the effect of changes in one of the variables against the other variable.

Variable a

Var

iabl

e b

Scatter diagrams

Interpreting a scatter diagram

• The diagram below shows a Strong Positive relationship between the variables (an in crease in a results in a positive increase in b, which is almost uniform.)

Variable a

Var

iabl

e b

Scatter diagrams

Interpreting a scatter diagram

• The diagram below shows a Strong Negative relationship between the variables (an in crease in a results in a decrease in b, which is almost uniform.)

Variable a

Var

iabl

e b

Scatter diagrams

Interpreting a scatter diagram

• The diagram below shows a Weak Positive relationship between the variables.

Variable a

Var

iabl

e b

Scatter diagrams

Interpreting a scatter diagram

• The diagram below shows a Weak Negative relationship between the variables.

Variable a

Var

iabl

e b

Scatter diagrams

Interpreting a scatter diagram

• The diagram below shows a that there is no relationship between the variables.

Variable a

Var

iabl

e b

7. Control Charts

A method for monitoring a process for preventing defects.

Control charts

What are control charts• Control charting is the most technically sophisticated tool

of the 7 quality tools.

• It was developed in the 1920s by Dr. Walter A. Shewhart of the Bell Telephone Labs. Dr. Shewhart developed the control charts as a statistical approach to the study of manufacturing process variation.

• The purpose was to improve the process effectiveness and therefore reduce costs.

• These methods are based on continuous monitoring of the process variation.

Control charts

Why use control charts• A Control chart is a device for describing in a precise

manner what is meant by statistical control.

• it helps the process perform consistently and

predictably.

• it can minimise the variation in output.

• it can help to achieve lower product costs.

• it can help to increase effective capacity.

• it can help to meet customer expectations

Control charts

Types of control charts• You will come across two types of Control

Charts used in SPC (Statistical Process Control).

1.Attribute SPC

2.Variable SPC

Control charts

Attribute control charts• Attribute data is based upon two conditions (pass/fail, go/no-

go, present/absent) which are counted, recorded and analysed.

• Control chart techniques are important for the following reasons:

Attribute-type situations exist in any process.

Attribute-type data is already available in many situations – (existing inspections, repair reasons, reject segregation & sorting) In these cases, no additional data collection is required, you just have to convert the data into chart form.

Where new data must be collected, attribute information is usually quick and inexpensive to obtain.

Control charts

Variable control charts

• Control charts for variables are used to control the variation of processes in cases where the characteristic under investigation is a measurable quantity.

Control charts

Variable control charts

• Xbar&R CHARTS.

• Xbar&R charts are used as a pair;

Control charts

Example of an Attribute control chart

Control charts

Example of a variable control chartMoving Range Variable Control Chart (Sub-group Sampling)

Process Characteristic Oven temperature X Bar 181 R Bar UCL R Frequency

Upper Spec: 185.0 Lower Spec 175.0 Upper Control Limit Lower Control Limit 60 Piece Capability Study

X1 182.0 182.0 183.0 176.0 183.5 184.0 183.5 183.0 183.0 170.0 176.0 182 182.5 176.0 183.5 183.0 183.0 184.0 183.0 184.0 183.5 176.0 176.0 176.0 182.0 176.0 178.0 176.0 186.0 187.0 182.0

X2 183.0 176.0 183.0 176.0 176.0 183.5 182.5 182.0 183.0 173.5 176.0 176 182.0 183.5 184.5 184.0 183.5 184.0 183.0 186.0 184.5 183.0 183.0 176.0 176.0 176.0 175.0 176.0 185.0 186.0 176.0

X3 176.0 183.0 184.0 183.5 184.0 182.5 182.0 176.5 184.5 172.0 183.5 176 176.0 184.0 182.5 182.5 180.0 180.0 182.0 184.0 184.0 184.0 183.0 183.0 176.0 175.0 174.0 183.0 183.0 186.0 183.5X4X5

X bar 180.3 180.3 183.3 178.5 181.2 183.3 182.7 180.5 183.5 171.8 178.5 178.0 180.2 181.2 183.5 183.2 182.2 182.7 182.7 184.7 184.0 181.0 180.7 178.3 178.0 175.7 175.7 178.3 184.7 186.3 180.5R 7.0 7.0 1.0 7.5 8.0 1.5 1.5 6.5 1.5 3.5 7.5 6.0 6.5 8.0 2.0 1.5 3.5 4.0 1.0 2.0 1.0 8.0 7.0 7.0 6.0 1.0 4.0 7.0 3.0 1.0 7.5

Op R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc R.Mc

TimeDate 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4 5/4

NEW CALCULATED LIMITS

X bar 180.823 R Bar 4.6094 UCL X 185.524 LCL X 176.121 UCL R 30.089 Cp 0.61 Cpk 0.51 Sigma 2.7274

ESPC coating

0.05.0

10.015.0

UCL

170

172

174

176

178

180

182

184

186

188

190

UCL

LCL

USL

LSL

xbar

1

2

3

4 & 5

X b

arR

bar

Problem Solving

• 5 Why

• Global 8D

• TRIZ