“zero defect” a buzz word or reality? - tcbvba.be fefco 2013 zero defect.pdf“zero defect” a...
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“ZERO DEFECT”
A buzz word or reality?Fefco Technical Seminar 2013
Wilbert Streefland
Technology Coaching BvbA
“There is nothing that is a more certain sign ofinsanity than to do the same thing over and over
and expect the results to be different”Albert Einstein
2
Zero Defect
• Conclusion
• Zero Defect & Innovation
• Zero Defect & Quality
• Zero Defect & Knowledge
• Zero Defect & Culture
• Introduction Zero Defect
3
Customer/Supplier & Zero Defect
• The customer presented his requirements
� Can the box plant supply accordingly?
• The machine suppliers showed what they have available
� Does this help to solve the current issues between customer and box plant?
ZD & Introduction
4
Introduction Zero Defect
• How many of you have made mistakes since waking-up this morning?
– If Zero � did you do anything?
• We all make mistakes every day!
• At best we can extend the time between consecutive mistakes
• The best way to achieve a longer time between consecutive mistakes is to record every mistake we make and learn how to avoid them
ZD & Introduction
5
Zero DefectDefinition
Infinite Time until the
next Defect to occur
ZD & Introduction
Zero Defect has no meaning
without Targets!
6
The impact of a defective product?
Use risk engineering:
• What will be the impact of a failing product?– Fatal accident or injury– Loss of production or product– Reputation damage
• How much do we invest to detect/avoid failing products?
• Analyse the product failing interval. This in time and number of products produced
• Do we provide training?
The biggest risk is: “Ignorance”
ZD & Introduction
7
Zero defect interpretations
1. Focus only on zero defect products send to the customer
2. Focus on all raw materials converted to zero defect products at maximum production speed
Interpretation 1 results in waste!
ZD & Introduction
� Customer ☺
� All ☺
8
The way to Zero Defect:
Process variability at target level
< (smaller)
Customer agreed tolerances
This for all property tolerances agreedwith the customer
ZD & Introduction
9
Zero DefectCustom or Standard product• Process capabilities set the standard for
what can be promised in terms of Zero Defect targets
• The process needs upgrading if it is not meeting customer requirements �Investment in higher level process! (Training, machines, retrofits etc.)
Never lower process performance
due to low customer demands!
ZD & Introduction
10
Zero Defect
• Conclusion
• Zero Defect & Innovation
• Zero Defect & Quality
• Zero Defect & Knowledge
• Zero Defect & Culture
Infinite Time until the next Defect to occur
• Introduction Zero Defect
11
Zero Defect & Culture
• Follow the airline principle:
– A pilot is never blamed if a major problem occurs so he will provide all information freely needed to
investigate the case
– The exception is in case of proven negligence, fraud
and or deception
• Management need to allow the making of mistakes �
else you can't detect and avoid them
No Blame Culture!
ZD & Culture
12
Zero Defect
• Conclusion
• Zero Defect & Innovation
• Zero Defect & Quality
• Zero Defect & Knowledge
No Blame!• Zero Defect & Culture
Infinite Time until the next Defect to occur
• Introduction Zero Defect
13
“Believing” or “Knowing”Why…?• ..is a box plant supplier allowed to
agree tolerances with a box plant customer not understanding the box plant process variability?
• ..is a box plant customer asking for Zero Defect products without a list of parameters and targets for these parameters?
• ..are box plants understanding so little and believing so much?
ZD & Knowledge
14
What is knowledge?
Theory
Knowledge and Insight
Experience
The right combination of
experience, evidence and theory allows to develop knowledge
and insight
ZD & Knowledge
Knowledge is valuable!• Document it• Use it for training
15
Long time between two defects
����Short time between
two defects
Relation between Knowledge and Defects
Knowledge about what you are doing
����Believing that you know what you are
doing
ZD & Knowledge
16
Zero Defect
• Conclusion
• Zero Defect & Innovation
• Zero Defect & Quality
Quantitative tests,
Observations, Training
• Zero Defect & Knowledge
No Blame!• Zero Defect & Culture
Infinite Time until the next Defect to occur
• Introduction Zero Defect
17
What is current practise?
• All box plants have a lab facility with measuring equipment
• For what is the lab facility used?
1. To check the board grade of a competitor box?
2. When there is a customer complaint?
3. To systematically monitor product performance?
ZD & Quality
Let’s look at the box plant process
18
Box Plant “Process”All elements need to “Pass” for Zero defect
Substrate Corrugating Printing Die Cutting Folding
•BCT•Erection•# Boxes•On time delivery•Etc.
•Fishtailing •Gap•Glue•Box Dimension•Etc.
•Colour•Grade•Moisture•Strength•Delaminating•Etc.
Box(Customer)
ZD & Quality
All elements need a quantitativeand measurable specification
•Board grade•Calliper•ECT•FCT•No Wash Boarding•No Warp•Bond•Etc.
•Colour to colour register•Dot size•Colour target•Colour variation•Bar-code readable•Defects•Edge Sharpness•Etc.
•Print to die cut register•Box Dimension•Scoring depth•Cutting•Cracking•Etc.
19
Box Plant “Process”All elements need to “Pass” for Zero defect
Substrate Corrugating Printing Die Cutting Folding Box(Customer)
If one element fails then the total box fails!
ZD & Quality
•BCT•Erection•# Boxes•On time delivery•Etc.
•Fishtailing •Gap•Glue•Box Dimension•Etc.
•Colour•Grade•Moisture•Strength•Delaminating•Etc.
•Board grade•Calliper•ECT•FCT•No Wash Boarding•No Warp•Bond•Etc.
•Colour to colour register•Dot size•Colour target•Colour variation•Bar-code readable•Defects•Edge Sharpness•Etc.
•Print to die cut register•Box Dimension•Scoring depth•Cutting•Cracking•Etc.
20
Zero Defect & QualityImportant about “Acceptable” Quality!
• Quality is a True/False property. Better than 100% is not possible � high quality is a buzz word!
• Measure properties at regular interval
• For destructive measurements use a product that is produced weekly– Do not take one measurement of all products– Take regular many measurements of a few
regularly produced products � it will provide the process quality assurance evidence needed for zero defect production
ZD & Quality
21
A closer look at variability and the impact reducing it
1. Determine process variability by systematic
measuring e.g. WARP
2. Reduce process variability by implementing
working standards and procedures (magenta curve). Resulting in:
• Increased product level
• Variation reduction
3. Lower specification while the product performance still meets customer demands
(Yellow curve)
0
5
10
15
20
25
30
35
40
45
0 20 40 60 80 100 120 140
Measured value
Fre
qu
en
cy
Y1
Target
V alue
Current
A verage
0
5
10
15
20
25
30
35
40
45
0 20 40 60 80 100 120 140
Measured value
Fre
qu
en
cy
Y1
Y2
Target
V alue
Current
A verage
0
5
10
15
20
25
30
35
40
45
0 20 40 60 80 100 120 140
Measured value
Fre
qu
en
cy
Y1
Y2
Y3
Target
V alue
Current
A verage
Step 1 Step 2
Step 3
•ZD & Quality
22
• It is a must to understand the relation between process variables and product quality
• A feed-forward closed loop is not common available yet!
Extending time between Defects
What is current practise?
• Measure properties
• Decide if properties are within customer tolerance
• Eject if not!
• Next product produced might need again ejection because process was not corrected
• Waste is produced �
What would be better to do?
• Agree tolerances
• Set “control” limits (lower than agreed tolerance)
• Measure properties, preferably in line
• Adjust process setting when outside “control” limits
• Next product is always within tolerance � No waste ☺
ZD & Quality
23
Zero DefectDo and Don’ts, 2 examples
1. Colour case � The wrong solution for a problem?
2. Folding case � Does measuring and ejecting solve the problem?
ZD & Quality
24
1 Colour CaseWhat has the largest impact on colour?
• On an off line printer a spectrophotometer and colour matching software was used to correct the ink formulation before starting production due to colour deviations
� This only corrects the consequence of a process defect but not the reason
• Downtime evaluation on this off line printer revealed:
– 33% colour related downtime of the total production time
• The implemented working procedure for correcting colour on the press is the source for high downtime
• Tests showed that the main problem for the start-up colour deviation was the screen roll specification and unpredictable status
ZD & Quality
The target:
Print all sheets “Zero Defect” starting with the first
25
Colour case solution• Screen roll related ink transfer problems result in:
– Unpredictable colour!
– Unpredictable dot gain!
• Change the screen roll specification to an ink film thickness and line count allowing:– Releasing the ink
– Being cleanable
• Implement strict screen roll cleaning procedures
• Check everyday the screen roll on cleanliness
ZD & Quality
Colour related downtime reduced to 0%!
Colour was printed with Zero defect
26
2 Folding Case• What is the problem?
• Inline data collection• In depth Analysis
• Gap fishtailing simulation
ZD & Quality
Lead Edge1
2
3
8
60
28
Folding data of 3,200 boxesLead/Trail edge Gap
Le ad Edge
0
50
100
150
200
250
300
350
400
Fre
qu
en
cy
Le a d Edge Tre nd
0
2
4
6
8
10
12
14
16
18
20
1
128
255
382
509
636
763
890
1017
1144
1271
1398
1525
1652
1779
1906
2033
2160
2287
2414
2541
2668
2795
2922
3049
3176
Gap
in
mm
T r ail Ed g e
0
50
100
150
200
250
300
350
400
Fre
qu
en
cy
Tra il Edge T re nd
0
2
4
6
8
10
12
14
16
18
20
1
12
8
25
5
38
2
50
9
63
6
76
3
89
0
101
7
114
4
127
1
139
8
152
5
165
2
177
9
190
6
203
3
216
0
228
7
241
4
254
1
266
8
279
5
292
2
304
9
317
6
Ga
p i
n m
m
ZD & Quality
29
Fishtailing
• Is this approach OK or is it “Lottery” data?
• What happens to the faulty product?
• What can be done to reduce variability?
• What is really happening?
Fis h T ailin g
0
100
200
300
400
500
600
Fre
qu
en
cy
Fish ta i ling Tre nd
-10.00
-8.00
-6.00
-4.00
-2.00
0.00
2.00
4.00
6.00
8.00
10.00
1
13
2
26
3
39
4
52
5
65
6
78
7
91
8
104
9
118
0
131
1
144
2
157
3
170
4
183
5
196
6
209
7
222
8
235
9
249
0
262
1
275
2
288
3
301
4
314
5
327
6
Fis
h t
ailin
g in
mm
ZD & Quality
30
Feeding skewed board using trim knife
Skewed 1°
Skewed
Skewed feeding of board in combination with trim knife:
• Lead edge gap = Trail edge gap ���� within target
• Can we detect fishtailing by only measuring gaps?
• How does the box look after squaring?
No Skew
ZD & Quality
Skewed 1°
31
In depth folding analysis(No trim knife used!)
Max 3.10 Max 2.00
Min -3.11 Min -5.00
Avg 0.00 Avg -1.90
Avg GP -2.14 Std 3.09
Avg GL 2.14
Std 2.23
Skew/m -3.51
Raw data
Cor. Data Cor. CPD,
PD Slot
Max 6.78 Max 1.92 Max 0.96 Max 1.47 Max 1.26 Max 0.57
Min -0.07 Correction Min -0.28 Correction Min -1.18 Correction Min -0.40 Correction Min -0.32 Correction Min -4.30
Avg 3.28 3.28 Avg 0.56 0.56 Avg 0.00 0.00 Avg 0.45 0.45 Avg 0.50 0.50 Avg -2.76 -2.76 2.32
Avg 1357 1.56 1.56 Avg Pos 3 0.20 0.20 Avg Pos 5 0.00 0.00 Avg Pos 7 0.64 0.64 Avg 1357 0.33 0.33 Prediction: -6.71
Avg 2468 5.00 5.00 Avg Pos 4 0.93 0.93 Avg Pos 6 0.00 0.00 Avg Pos 8 0.27 0.27 Avg 2468 0.67 0.67
Std 2.02 Std 0.49 Std 0.40 Std 0.38 Std 0.38 Std 1.03 1.03 1.06
Skew/m -4.52 Skew/m -0.96 Skew/m 0.00 Skew/m 0.49 Skew/m -0.45
Raw Data
CPD feed
corrected
PD feed
corrected
Cor. Data Cor. CPD,
PD Slot
Glue Lash A Avg -0.25 -0.17 0.16 0.24 0.19
Std 0.12 0.10 0.12 0.10 0.12
Glue Panel B Avg -0.21 -0.24 0.19 0.16 0.18
STD 0.07 0.08 0.08 0.08 0.08 Prediction Raw data
Cor. Data Cor. CPD,
PD Slot
Edge 1, 3, 5, 7: Max 1.81
Min -7.52
Edge 2, 4, 6, 8: Max 0.60
Min -5.77
Avg ALL: 2.56 -2.65
Avg Edge 1, 3, 5, 7: 3.08 -3.15 -4.72 -5.27
Delta Glue panel: Delta short panel: Delta long panel Delta glue Lash Std Edge 1, 3, 5, 7: 2.46 2.11 2.30
ALL: -2.72 ALL: -0.56 ALL: 0.45 ALL: 0.05 Avg Edge 2, 4, 6, 8: 2.03 -2.15 -7.14 -5.15
Edge 1, 3, 5, 7: -1.36 Edge 1, 3, 5, 7: -0.20 Edge 1, 3, 5, 7: 0.64 Edge 1, 3, 5, 7: -0.31 Std Edge 2, 4, 6, 8: 1.73 1.36 1.69
-4.07 -0.93 Edge 2, 4, 6, 8: 0.27 Edge 2, 4, 6, 8: 0.41Edge 2, 4, 6, 8: Edge 2, 4, 6, 8:
Panel Angel Results
Gap results
Drive Side Edge Pos 1b (Glue Panel)
-5 -4 -3 -2 -1 0 1 2 3 4 5
Error in mm
Drive Side Edge Pos 2b (Glue Panel)
-5 -4 -3 -2 -1 0 1 2 3 4 5
Error in mm
Slot 1, Pos 3, CPD Variation
-5 -4 -3 -2 -1 0 1 2 3 4 5
Error in mm
Slot 1, Pos 4, CPD Variation
-5 -4 -3 -2 -1 0 1 2 3 4 5
Error in mm
Slot 2, Pos 5, CPD Variation
-5 -4 -3 -2 -1 0 1 2 3 4 5
Error in mm
Slot 2, Pos 6, CPD Variation
-5 -4 -3 -2 -1 0 1 2 3 4 5
Error in mm
Slot 3, Pos 7, CPD Variation
-5 -4 -3 -2 -1 0 1 2 3 4 5
Error in mm
Slot 3, Pos 8, CPD Variation
-5 -4 -3 -2 -1 0 1 2 3 4 5
Error in mm
OS, Pos 1a (Glue Lash)
-5 -4 -3 -2 -1 0 1 2 3 4 5
Error in mm
OS, Pos 2a (Glue Lash)
-5 -4 -3 -2 -1 0 1 2 3 4 5
Error in mm
Edge to first colour PD, Glue Panel
-5
-4
-3
-2
-1
0
1
2
3
4
5
Edge 1357
Err
or
in m
m
Edge to first colour PD, Glue Lash
-5
-4
-3
-2
-1
0
1
2
3
4
5
Edge 1357
Err
or
in m
m
Gap, Pos 1
-12 -9 -6 -3 0 3 6 9 12
Error in mm
Gap, Pos 2
-12 -9 -6 -3 0 3 6 9 12
Error in mm
Fishtailing
-5
-4
-3
-2
-1
0
1
2
3
4
5
Err
or
in m
m
Slot Var., PD, Edge, Pos.: 5
-5
-4
-3
-2
-1
0
1
2
3
4
5
Err
or in
mm
Slot Var., PD, Edge, Pos.: 6
-5
-4
-3
-2
-1
0
1
2
3
4
5
Err
or in
mm
ZD & Quality
Note the feed skew problem!
32
Correcting the fishtailing for the feeding error
h values
-6
-4
-2
0
2
4
6
h i
n m
m
h Raw Data
h Skew Corrected
Note the impact of correcting
fishtailing data for the feed error!
Ejecting faulty boxes will not solve the problem!
ZD & Quality
33
Folding Case• Data collected inline will show if there is a
problem but not the problem source
• Detailed testing of production equipment is needed to find the problem source
• Ejecting bundles will avoid problems at the customer � Is that the best option for Zero Defect product?
• Do we know what folding tolerances are acceptable?
ZD & Quality
What about a folding error simulation?
34
What folding tolerances are machine suppliers promising and what is delivered?
• Check during machine commissioning if the supplier delivers what is promised?
• The next slide will show a mathematical simulation on how gap and fishtailing are affected by:– Feed variation
– Skew (Due to a feed skew)
– Slot position– Glue lash position
– Glue panel position
ZD & Quality
35
Folding Error Simulation
• How accurate is your FFG feeder and slot head positioning?
• Does your customer accept these gaps and fis
htailing deviations?
• Will the squaring unit c
orrect the fis
htailing error and not
increase the gap error?
• We have not yet looked at th
e influence of the folding arms!
ZD & Quality
36
Specification• Quantitative �
– Based on facts and figures
– Represent the objectives to achieve
– Realistic tolerance based on the capabilities of:
• Process
• Equipment
• Raw materials
• Measurable � Measuring equipment that has sufficient resolution to detect if the property is inside or outside the set tolerance
Measuring is done systematically and not only when there is a complaint!
•ZD & Quality
37
Always agree “SMART” targets
• S � Specific
• M � Measurable
• A � Achievable
• R � Realistic
• T � Timed
ZD & Quality
• It is easy to make this slide!
• Brain power is needed to
define “SMART” targets!
38
Zero Defect
• Conclusion
• Zero Defect & Innovation
SMART Target• Zero Defect & Quality
Quantitative tests,
Observations, Training
• Zero Defect & Knowledge
No Blame!• Zero Defect & Culture
Infinite Time until the next Defect to occur
• Introduction Zero Defect
39
Zero defect & InnovationThe paradox
• Innovation is based on the evolution of
correcting mistakes
• Would avoiding defects stop Innovation?
• According Murphy’s law it is likely that
(unknown) defects will continue to occur
At best we can extend the time between
the events!
ZD & Innovation
And… New technology might be needed to improve
40
Zero defect & InnovationWhat can be used now and in 2025
• How to produce Zero Defect if testing damages the product?
• Is it possible to investigate paper and board non destructive?
• We know CT scanning for medical use
• Inside Matters, a University Gent spinoff company, make CT scans of any material and/or object
CT scanning of paper and boardwill provide new ways for
detecting defects!
ZD & Innovation
44
Zero Defect
• Conclusion
New technology will support improvement
• Zero Defect & Innovation
SMART Target• Zero Defect & Quality
Quantitative tests,
Observations, Training
• Zero Defect & Knowledge
No Blame!• Zero Defect & Culture
Infinite Time until the next Defect to occur
• Introduction Zero Defect
45
# of defects
Co
st Production
Cost
Sales cost
Conclusion• Zero Defect might be a “ghost” objective at
best the time between two detectable defects can be extended
• Minimizing defects will reduce cost for all up to a certain level after that the customer and supplier have to understand the economics
• It requires:– Open fact based mind set
– Specifications that confirm quality targets
– No blame mentality
– Responsibility for what you claim
– Accepting the need for changes
– New technology
– Training and education
ZD & Conclusion
There are no shortcuts to Zero Defect only detours
0
46
Zero Defect
There are no shortcuts
to Zero Defect only detours
• Conclusion
New technology will support improvement
• Zero Defect & Innovation
SMART Target• Zero Defect & Quality
Quantitative tests,
Observations, Training
• Zero Defect & Knowledge
No Blame!• Zero Defect & Culture
Infinite Time until the next Defect to occur
• Introduction Zero Defect