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Objectives of this workshopDescription of Problem
The rejections of paper manufactured by a company exceeds 30%. The magnitude of the problem has increased recently. Problem is observed at the end of the paper production process where the entire paper produced is tested for its quality.
Rejection36%
Rs18 croreper annum
Acceptedproduct
Others
Product“A”50%
Holes
Thin Spots
Black Spots
Highest contribution to rejections
Most serious
Drawn to scale
1% rejection corresponds to a revenue loss of Rs 50
lakh pa
Scope the problem
HOLES ARE THE MAJOR CONTRIBUTORS TO REJECTION.PROBLEM IS SCOPED TO: REJECTION OF PAPER CAUSED DUETO PRESENCE OF HOLES
The pet theory of the personnel in the plant was: “Roller Number 1 is root cause”
“It picks up fibre or something and leaves a hole”Capex of Rs.2 crore would be required to replace the roller with a larger one.
We take a systematic problem solving approach, that uses:• only data and no opinion• strict logical analysis• experimental confirmation
THE DATA OF %DEFECTS OVER A PERIOD OF TIME INDICATED THAT THE PROBLEM IS OF VARIATION TYPE.
Problem
Is Present in Problem
Is Absent in Problem
1. What
2. Where
3. When
4. Quantity
Is/Is-Not Matrix: Data Collection Format
Problem Present AbsentWhat is the unit with defect
Paper Not applicable
What is the defect on the unit (this is the defect under study)
Holes Not applicable
What other defects are present on the defective unit
None Not applicable
What other defects are absent on the defective unit
Not applicable
Profile, Thickness, GSM, Porosity, etc..
Data Obtained on “What”
Yellow is where data is available in this case
Hole
The Holes in the Paper
Hole
The paper with holes does not have any other
problems
HoleDetector
Problem Present AbsentWhere – on which part of defective unit
Anywhere across machine profile
Not present at any specific location
Hole
M/C
wid
th
RollerNumber
1
Data Obtained on “Where”
View across width of machine
Red: Medium size holeBlue: Large size hole
WIDTH OF MACHINE
The Holes in the PaperWhere is present?
Problem Present AbsentWhere – on which part of defective piece
Anywhere across machine profile
Not present at any specific location
Hole
M/C
wid
th
RollerNumber
1
Absence of specific location, and presence of random spread suggests
that the holes are not machine related, but related to something that contacts
machine anywhere randomly
Problem Present AbsentWhere - on which part of defective piece
Anywhere across machine profile
Not present at any specific location
Where – on which product variety Imported RM,
More hardwood.
Indian RM,
Less hardwood.
Where – after which operation, and not before which operation
Cannot measure Cannot measure
Where – on which machine or line Only one m/c available
Only one m/c available
Where – in which plant/ area Not checked Not checked
Data Obtained on “Where”:
Input feed to the process is randomly
distributed
Corroboration: Holes are
correlated with type of input into process
Data obtained in “where” indicates that:Holes do not appear to be correlated with machine
andHoles appear to be correlated with something
randomly distributed across the process.
Problem Present
Absent
When – draw time line and show occurrences of defect
When – in which shift and which part of the shift (hr/min)
When – in which month; in which season
When – in which year Yellow is where data is available in this case
Detailed Problem Specs Sheet for “When”
Problem Present
Absent
When – draw time line and show occurrences of defect
No clear pattern,trend or
periodicity
When – in which shift and which part of the shift (hr/min)
No pattern visible
When – in which month; in which season
When – in which yearYellow is where data is available in this case
Detailed Problem Specs Sheet for “When”
0.00
0.50
1 .00
1 .50
1
Ser ies1
TREND TR-5000 ULMA % REJ ECTION
0
510
15
2025
30
3540
45
5055
60
TREND TR-5000 ULMA % REJ ECTION
0
5
10
15
20
25
30
35
40
45
50
55
60
TREND TR-5000 ULMA % REJ ECTION
0
5
10
15
20
25
30
35
40
45
50
55
60
Data on “When” – Time line
1
2
3
Today
No clear patternno build ups, no periodicity
None of the recorded machine parameters and none of the
recorded input parameters correlate with the ups and downs in the
rejection percentage on the time line, when compared for the same
grade of material.
Problem Present
Absent
Quantity – How much (how deep/wide…) are the defects
Quantity – How many defective pieces in the batch
Quantity – How many defects on defective pieceYellow is where data is available in this case
Detailed Problem Specs Sheet for “Quantity”
Problem Present AbsentQuantity – How much (how deep/wide…) are the defects
Approx circular holes, which are most common
Not steaks, tears,
Quantity – How many defective pieces in the batch (roll)
Many Not zero
Quantity – How many defects on defective piece
Data Obtained for “Quantity”
Physically search for “mura”
(inconsistency) in input material
Found foreign bodies in head
box input!
Found no contamination in recycle water!
Found no contamination in
input raw materials
Found no contamination in chemicals and other streams
Found foreign bodies in fresh
water!
Hypothesis:Foreign bodies from
fresh water lead to holes
Testing of Hypothesis
Experimental confirmation:• Experiment : Stop fresh water: Rejections should reduce
Roll No Grade Meters Holes small
Holes medium
Holes large
Dark Sp small
Dark sp medium
Dark sp large
Thin sp small
Thin sp medium
Thin sp large
Bobbinsreject
% bobbins reject
234 TR 3 21111 2 70 57 0 0 0 335 142 29 56 With fresh water
235 TR 3 26251 2 30 41 2 0 0 114 67 14 39 With fresh water
236 TR 3 28214 1 33 30 0 0 2 137 78 19 49 With fresh water
244 TR 3 21,676 3 28 15 0 0 0 66 34 4 14 5% No fresh water
Experimental Testing of Hypothesis
Conclusion
Foreign particles from fresh water are primary chronic causes of holes,
resulting in rejections
Machine parts, including “roller number 1” aggravate the problem, and are causes of instability problem (cyclic trend), resulting
in rejections.
Countermeasures
•Reduce contamination in fresh water
This is a sporadic problem of holes in shape of cracks
This is a instability problem.Not to be confused with chronic problem.
Cause for this is different, and known.
Difference between Sporadic and Shift
Sporadic
Shift
We are solving this
Now the real challenge is on!
1. Completing the countermeasures2. Sustaining the gains3. Preventing and immediately correcting
sporadic problems
Should become redundant
Can you meet it?
8D approach makes no assumptions.It starts with data, from scratch on blank slate.
It uses logic to narrow down the area of search for the root cause.
It does not require only technical expertise.It also requires reliable data.
It obtains data by asking a series of questions.The questions are in strict sequence.
Learning’s