quality tools 2
DESCRIPTION
ereTRANSCRIPT
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
02468
10121416
Pow
er u
p
Boo
t up
Sin
k te
st
Cas
eda
mag
e
Key
boar
dda
mag
e
Mon
itor
dam
aged
Bun
dled
s/w
incl
uded
Type
Qu
anti
ty
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
02/0
2/03
03/0
2/03
04/0
2/03
05/0
2/03
06/0
2/03
07/0
2/03
08/0
2/03
09/0
2/03
10/0
2/03
11/0
2/03
12/0
2/03
13/0
2/03
14/0
2/03
15/0
2/03
16/0
2/03
17/0
2/03
18/0
2/03
19/0
2/03
20/0
2/03
21/0
2/03
22/0
2/03
23/0
2/03
24/0
2/03
25/0
2/03
26/0
2/03
27/0
2/03
28/0
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
02468
10121416
Pow
er u
p
Sin
k te
st
Key
boar
dda
mag
e
Bun
dled
s/w
incl
uded
Type
Qu
anti
ty
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