This document outlines a Lean Six Sigma project to improve quality in the machine shop and brazing area of a rollator manufacturing process. The project aims to reduce dimensional variation in rollator frames and crossbars to decrease defects like cross folding and three wheeling. Success would mean an 80% reduction in rework/scrap and meeting delivery, production, and WIP reduction targets. Baseline data on outputs like scrap rates is available but more data needs to be collected from the processes to understand the root causes of variation. Completing new process controls in 4-6 months seems feasible if required equipment investments are approved. Stakeholders include suppliers, various process areas, customers, and others.

1. Improve Quality in
MS and Brazing
Rollators Area

2. DMAIC
1
DEFINE
IMPROVE

3. Project
Signature Page:
Sponsor: I commit to support the successful completion of this project by:
• Ensuring that the project is aligned with overall organization goals
• Providing personnel and resources
• Removing roadblocks and barriers
• Allotting time to hear progress reports from the team and provide meaningful feedback
Approval
Signed: Imelda Salas
Name Date
Director of Operations
Title
Champion: I commit to support the successful completion of this project by:
• Arranging Lean Sigma training for the team, as necessary
• Coordinating available resources and support
• Conducting frequent reviews of the team's progress
Signed: Javier Estrada
Name Date
Engineering and Lean Manager
Title
Team: We commit to contributing to the successful completion of this project by:
• Applying the Lean Sigma methodology to make sustainable improvements to key metrics
• Contributing our knowledge, ideas, and experiences
• Attending scheduled meetings and events
• Completing all assigned action items
• Communicating project progress to the Champion and Sponsor
Signed:
Gladys Quiroz Mfg. Engineer / Floor Support
Name Title / Role Date
Eusebia cedillo Quality Engineer / Floor Support
Name Title / Role Date
Jorge Sanchez Gral. Supervisor / Prodcution
Name Title / Role Date
Alejandro Perez Project Engineer / Projects
Name Title / Role Date
Jorge Castellanos Lean Department / Plant
Name Title / Role Date
Ramon Garcia Gral. Supervisor / Tool Room
Name Title / Role Date
Name Title / Role Date

4. Project contract
Lean Six Sigma Project Contract
Name of Project: Improve Quality in MS and Brazing Area - Rollator Models
Business Driver(s): Examples include Production Increase, Cost Reduction, Capital Avoidance
Estimated Start Date: 10/15/2010 Estimated Completion Date: 5/15/2011
Estimated COPQ: Metric(s) to be Improved:
List the metric(s) that you expect to affect and whether
Provide an estimated cost of poor quality. you expect them to increase, decrease, etc. (IPO
ouptuts)
Project Objective
Reduce the dimensional variation on the frame and cross bar of the rollators model.
Business Objective
Invrease Productivity, Delivery and Reduce Cost
Definition of a Defect:
Eliminate mis balance and three wheeling
In Project Scope: Not in Project Scope:
Tubing, Tube benders, Piercing, Notching and
Painting, purchased components and Final Assembly
welding
Vision of Success:
Apply some Lean Manufacturing concepts such as 5"S, Quick Set Ups, Overproduction,etc,. Then we will
recolect data from the equipment mentioned above in order to find the root cause using statatistic tools, the
reduce the variation of the processes.

5. Dolomite Rollator

6. Core Team
• Sponsor – Imelda Salas
• Champion – Javier Estrada
Black Belt – Mario Ruiz
Team members Support Members
– Gladys Quiroz ( Engineering) – Carlos Gonzalez (Finance)
– Eusebia Cedillo (Quality) – Hector Elizondo (Maintenance)
– Jorge Sanchez (Production) – Edilberto Reyes (HR & Safety)
– Alejandro Perez (Engineering)
– Jorge Castellanos (Lean Mfg)
– Ramon Garcia (Tool Room)
– Jesus Fonseca (Production)

7. PROJECT SCOPE
●
Objective: Reduce the dimensional variation on the
frame and cross bar of the rollator models
●
Business Objective: Increase productivity, delivery and
reduce cost
●
Problem Statement (s):
– Reduce rejects at the Final Assembly area
– Increase delivery time
– Increase production base on the resources assigned
– Reduce scrap

8. Project Timeline

9. VOC
Customer Interview
1. What process are we working on?
• Rollators (Machine Shop & Brazing)
1. What is the process objective (voice of the customer and/or business)?
• Reduce and Eliminate rework and scrap due cross folding and three
wheeling
1. Has the customer been interviewed to confirm the VOC?
• Yes
1. What is the project business objective (COPQ)?
• While eliminating this type of defects we minimize the chances of shipping
bad product to our customers. We will also improve our safety and
ergonomics eliminating the risk for a long term injuries. We can increase
our production velocity, reduce the inspection time and material handling.
1. What does success look like (project goals)?
• Hit Target: What is the target?
– Feb 2011 for hand off training and Owner sign off
• Minimize: to what level, cost or effort?
– 80% Rework / Scrap reduction for cross folding and three wheeling
• Robustness: To what degree?
– Maxi and Legacy Rollators regardless of the customer

10. VOC
6. How long had this issue been present?
Employee and supervisors interviews states that three wheeling has been since
product initiated production, and cross folding control became due a some customer
complains.
What has been done about it so far?
Some tooling and process correction and 100% inspection at final assembly thru kaizen
events.
7. Construct an Input, Process, Output diagram of the process. Outputs need to be
measurable, in units, and possibly normalized. Use continuous data when
possible. All outputs need to represent the voice of the customer or business.
SUPPLIER INPUT PROCESS OUTPUT CUSTOMER
Target
Materials Raw Material
H.Resources SOP's Delivery increase 95% <= 2 Days Government
Process Eng. Manpower Machine Shop Airlines
Maintenance Training Scrap Reduction 70% Parks
Industrial Eng Equipment Brazing Farmacies
Prod. Sup. Machines FPY 98% Warehouses
Safety Parameter Homecare
Utilities WIP Reduction 60% DC’s

11. VOC
8. Do you have baseline data for the outputs?
• Yes, there are scrap and first pass yield reports
• Measurements of the product were given but new parameters needed to be
set up due to new tooling for bender equipment.
9. Can the project be completed (new controls in place) in 4-6 months?
• Yes, it can be completed
10. What are the problem statement(s)?
• Cross folding
• Three wheeling
• Dimensional capability
11. Do you have an idea of what is causing these issues?
• Yes, potential dimensional variation during the machining and welding
processes.
Can that be supported with data?
• Not at this time, we have to collect data from the source.
12. What prevents us from being in the desired state?
• Machine capabilities
• Process operator dependable
13. Is this process within our realm of influence?
• Yes, if a major investment is required a Cap Ex must be issue and approved
prior implementation

12. VOC
14. Who are the stakeholders in this process?
Suppliers Process Customers Others
Participants
Warehouse Cutting Paint Line Production Control
Planning Bending Final Assembly Quality
Production control Punching
Maintenance Welding
Tool Room Piercing
Engineering
15. Who should be on the project team?
• Core Team – multi-task employees with experience in this
product.

13. Value Stream Map (Current
state)

14. Cost of Poor Quality
$70,000 Total $119,997
$60,000
$50,000
$40,000
$30,000
$20,000
8
3
8
19
13
08
60
46
16
$10,000
,4
,1
,5
3,
0,
4,
$2
$6
$8
$1
$4
$3
$-
F.A. Rework F.A. Scrap cost Brazing Brazing Scrap Bend Rework Bend Scrap
cost Rework cost cost cost cost
Yearly rework cost: $35,663
Yearly Scrap cost: $84,335

15. Units
In
c or
r ec
0
1000
1500
2000
2500
3000
3500
4000
500
t Be
Se nd
t -u
pf
M
3508
at ai
lur
er
ial e
857
re
lat
Be ed
nd
fl a
tn 503
es
To
ol s
in
440
gd
en
t
209
we Ox
l id
di e
ng
92
f ai
lur
Ba e
d
68
fo
In rm
c or in
r ec g
t
40
len
Defects Pareto
gt
M h
37
et
al
de
nt
25

16. Bend Defect Pareto
90%
77% Incorrect Bend degree
80%
70%
60%
50%
40%
30%
20% 13%
7%
10% 3%
0%
Bender D-11 Press P54 Welding Chrome
fixture
77% of bend defects relates to bender equipment

17. FMEA
Process: Machine Shop Process Responsibility: Alejandro Perez
Component: 13347 BACK FRAME LEGACY 600 Creation Date: 4/07/2010
Team: Rollator TEAM Revision Date: 9/10/2010
Requirements Failure Mode(s) Effect(s) of Failure Cause(s) of Process Control(s) Recommended Solution(s) Resp & Target Date
SEV
OCC
DET
RPN
SEV
OCC
DET
RPN
Failure
-Bring tubing cut to length from
M. Granados
4 First piece and last piece audit 4 64 supplier -Cut machine set-up 4 4 4 64
short or long Misalignment of side tubes on Bad cut Manufacturing
Tube cut length 4 check list
cut to length 13192 weldment fixture length
Make sampling plan to use Go no Manufacturing/Qu
2 -Use of fixture Go no Go 3 24 4 2 3 24
Go ality
Bender miss- -Monitoring pressure levels
4 3 60 TPM program 5 4 3 60 Maintenance
Back frame will not match adjusted on bender
with the front frame. The Incorrect preferably Use of Protractor Sampling program to verify Manufacturing/Eng
Angles within +/- Angles out of 3 3 45 5 3 3 45
Rollator will not have 5 bender set- Go no Go as a secondary correct bend on tubing. ineering
0.5 degree Spec Spec limits Go no Go
symmetrical structure. Check list to verify Go no Go uses. Manufacturing/Eng
Potential Three wheeling. fixture not 4 Training/Supervision 3 60 5 4 3 60
State in the work instructions. ineering
in use
Sampling plan or revalidation
holes location & Incorrect holes 4 3 60 Process re-validation 5 4 3 60 Engineering
Bad function of the folding Die miss- process.
orientation location & 5
mechanism. adjusted State Go no Go use on work Manufacturing/Eng
withing Spec. orientation 2 -Use of fixture Go no Go 2 20 5 2 2 20
instructions ineering
Wrong
-Identify bending dies per Put marks on bending dies & state
bending 4 3 48 4 4 3 48 Manufacturing
tubing to use on set-up instructions
tools
warehouse location for this tube 4 4 2 32 Warehouse
Flatten bends -Customer Dissatisfaction 4 Wrong
4 -Identify tubing on warehouse 2 32 Tube cut to length from supplier
tubing 4 4 2 32 M. Granados
Apearance to prevent mixed material
Bender non -Monitoring pressure levels
4 3 48 TPM program 4 4 3 48 Maintenance
adjusted on bender
Un- paint inspection before send to
-Scrap, Quality complaints, Manufacturing/Qu
Paint defects 3 appropriate 4 Quality inspection check list 3 36 final assembly & final assembly 3 4 3 36
Customer dissatisfaction ality
paint rack area inspection before assemble.

18. Measure Plan
●
Team will measure the part numbers as follow:
– Bend process: Angle on 1149178 y 1149181 left & right sides
– Punching: Distance between holes and angles on 1150607 &
1150608 left and right sides
– Welding: distance between sides and between holes on 1149177
●
Procedure:
– Production will send 5 pieces of each run to metrology for 2
weeks
• 1st piece, 3 more during the run and the last piece.
• Set up Tech will record all process changes during the run in order to
understand where is the variation.
– The pieces will be delivered to metrology technician one by one;
the measured pieces will be picked up and sent back to line.
– Metrology lab will maintain the record and at the end of each shift,
the record will be sent to the quality engineer.
– Quality engineer will process the data and obtain the graphics

19. 2010 Defects
12,000 M.S. Defects Brazing Defects F.A. Defects
10,000
04
4,3
8,000
29
3,4
18 28
Units
6,000 78 3,1 3,1 3, 059 9
2,9 2,8
7
9 1
0 7 46 9 7 2,2
2,2 2,2 3,9
4,000
84 39
5 9 5 0 4 41 3,1 2,5
2,7
6 2,8 2,9 2,8 73
2,6
4 9 8 6
2,1
27 385 4 1
2,000 2,0 2,0 6 556
16
1,0 264 329 6
60 29
2,4 02 82 87 748 59 45
61 84 1,7 1,7 1,7 09 1, 1,9 1,6 70
1,2 1,2 1,3 1,2
0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan-11
2010
Significative improvement achieved for production to control runs and
avoid mixing set-ups has helped reduce three wheeling.

20. Three wheeling Defect Trend
9.00% 8% 9%
8.3 8.1 4%
8.00% 7.3
7.00%
6.00% 3%
4.8 8% 9%
5.00% 4.2 4.4
0% 0%
3.7 3.6
4.00% 2%
2.9 4%
3.00% 2.5
5%
1.9
2.00%
5% 0%
1.00% 0 .3 0.3
0.00%
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan-11
2010
Nov 2010 Production started to control production orders for
left and right sides of the frame.

21. DMAIC
IMPROVE

22. IPO Grid Bender
Output Variables
Distance
Tube bend operation Bend between
angle bends Length Total
Weigh Factor 9 5 1
Speed 9 5 1 107
Die penetration 9 1 1 87
Pressure 9 5 1 107
Stops position 1 9 9 63
Process input
Temperature 5 1 1 51
variables
Lubrication 5 1 1 51
Forming dies 5 5 1 71
Tube strength 9 1 1 87
Tube position 1 5 5 39
Per our pareto graphs we weighed bend angle as our output
variable to focus

23. Time Series Plot 610 angle
Run trial to establish our start point.
• 20 pieces in Bend & Punch operations
• Measured the 4 angles of the piece after each operation
• Graph each Angle to compare
Ti me Ser i es Pl ot of Angl e 1 , Max 1 , Mi n 1 , Punch 1 , Spec 1
62.0
Variable
Angle 1
Max 1
61.5 Min 1
Punch 1
Spec 1
61.0
D a
at
60.5
60.0
59.5
2 4 6 8 10 12 14 16 18 20
I ndex

24. Interval plot 600 Angle
6 0 degr ee Bend Bef or e and Af t er bei ng pi er ced
95% CI for the Mean
61.0
60.9
60.8
60.7
Dat a
60.6
60.5
60.4
60.3
60.2
60 after pierce 1
Delta of mean = 0.255 degrees

25. Hypothesis test for piercing process
●
The Angle deformation made during piercing operation is
statistically significant to deviate in +/-0.5 degrees
 H0-0.50<m0>+0.50
Box pl ot of Z-t est
 H1-0.50>m1<+0.50 (with Ho and 95% Z-confidence interval for the Mean, and StDev = 0.25)
One-Sample T: Z-test
Test of mu = 0.5 vs not = 0.5
Variable N Mean StDev SE Mean 95% CI T P
Z-test 59 -0.0458 0.3164 0.0412 (-0.1282, 0.0367) -13.25 0.009
_
One-Sample T: Z-test X
Ho
Test of mu = -0.5 vs not = -0.5
Variable N Mean StDev SE Mean 95% CI T P
Z-test 59 -0.0458 0.3164 0.0412 (-0.1282, 0.0367) 11.03 0.009 -0.75 -0.50 -0.25 0.00 0.25 0.50
Z- t est
P-values range from 0 to 1. The smaller the p-value, the smaller
the probability that rejecting the null hypothesis is a mistake
Conclusion:
The H0 is rejected as P value in both tests are 0.009

26. Cause and effect analysis
Cause-and-Ef f ect Di agr am
Measurements Material Personnel
Lenght
Go-no go out of spec
Lack of t raining
Mat erial hardness
lack of calibrat ion
Mat erial inconsistency
No experience
improper
measurement t ools walnut out of t olerance
Bend
Three
Angle
Wheeling
Three
process cont rols Wheeling
equipment check up
Welding process
Safety factors
t ooling lifecycle records prevent ive maint enance
Operat or dependant
set up parameters tooling condit ion
Temperature
t ube posit ion
unstable pressure
Set up t ools
Environment Methods Machines

27. Bend Data Sheet
●
Pieces from the bend operation were measured
and the results Ser i esshown 5in a ee
Ti me
are Pl ot of 5 degr control chart
56.5
56.0
55.5 USL
55 degree
55.0 Mean
54.5 LSL
54.0
1 13 26 39 52 65 78 91 104 117
I ndex

28. Gage R&R Measure
●
Gage R&R was performed to evaluate our
measure system on:
– Precision Gage Run Char t of Measur ement by Unit , Oper at or
Reported by : Mario Ruiz
Gage name: A ngle Tolerance:
– Repeatability
Date of study : 12/23/2010 Misc:
– Reproducibility 1 2 3 4 5 O perator
A
B
35.25
35.10
Measur em ent
Mean
34.95
34.80
34.65
34.50
Oper at or
Panel variable: Unit
Graph Shows measurement system is consistent between Operators
using the Faro measurement tool

29. ANOVA of Gage R&R
Gage R& R ( A NOVA ) f or Measur ement
Variation of the pieces, OK
Reported by : Mario Ruiz
Gage name: A ngle measurement Tolerance: 1
Major contributor of Date of study : 12/23/2010 Misc:
variation is the parts,
means, the measuring Com ponents of Variat ion Measurem ent by Unit
system is correct 100 % Cont ribut ion
% St udy Var
35.1
Percent
50
34.8
34.5
0
Gage R&R Repeat Reprod Par t-to-Part 1 2 3 4 5
Unit
system is on control, R Chart by Operat or
Measurem ent by Operator
A B
means operators are 0.10 UCL= 0.1004
Sam ple Range
measuring almost the _ 35.1
0.05 R= 0.044
same, 34.8
0.00 LCL= 0
1 2 3 4 5 1 2 3 4 5 34.5
Unit A B
Operat or
Xbar Chart by Operat or
A B Unit * Operat or I nteract ion
Pieces are out of control,
Sam ple Mean
_
_ Operat or
meaning measurement 35.1 UCL= 35.0761
X= 35.044
LCL= 35.0119 35.1
A
Aver age
B
system is valid 34.8
34.8
34.5
1 2 3 4 5 1 2 3 4 5 34.5
Unit 1 2 3 4 5
Unit
No interaction of operator
if lines are almost parallel
ANOVA to the measuring system shows our measurement system to be
reliable

30. Six pack Bender Analysis
Process sigma, CP and Cpk wasi tdetermined C5
Pr ocess Capabi l y Si xpack of
Xbar Char t Capabilit y Hist ogr am
Data shows a
LSL USL
56 UCL= 55.994
dispersion from Specif
Sam ple Mean
_
_ 53.83 to 55.99 LSL
55 X= 54.913 USL
54 1
LCL= 53.833
Pr 5ocess Capabi 15i t y Si xpack of C5
71 39 11
Tests performed with unequal sample sizes
13
l 17 19 21 23 53.4 54.0 54.6 55.2 55.8 56.4
Xbar Char t Capabilit y Hist ogr am
R Char t LSL USL
Nor mal Pr ob Plot
UCL= 55.994 A D: 0.421, P: 0.320
Specifications
Sa m ple Range
2 _
_ UCL= 1.877 LSL 54.5
Xbar shows data to X= 54.913 USL 55.5
1 be normal as well _
R= 0.574
0
as the histogram
1
LCL= 53.833
LCL= 0
7 11 139 15 17 19 21 23
1 3 5 7 9 11 13 15 17 19 21 23
equal sample sizes 53.4 54.0 54.6 55.2 55.8 56.4
Tests performed with unequal sample sizes 54.0 55.5
R Char t Last 2 4 Subgr oups Nor mal Pr ob Plot
Capabilit y Plot
A D: 0.421, P: 0.320
Within Within Over
56

31. Specifications
_
_ LSL 54.5
X= 54.913 USL 55.5
1
Six pack Bender Analysis
LCL= 53.833
3 5 7 9 11 13 15 17 19 21 23
d with unequal sample sizes 53.4 54.0 54.6 55.2 55.8 56.4
R Char t Nor mal Pr ob Plot
Defect opportunities 2 A D: 0.421, P: 0.320
Events observed 140
UCL= 1.877
Defects made (include defects fixed) _ 56
R= 0.574
DPO (defects per opportunity) LCL= 0
0.200
3 5 7 9 11 13 15 17 19 21 23
Yield
d with unequal sample sizes 80.00% 54.0 55.5 57.0
Process Sigma oups
Last 2 4 Subgr ~2.4 Capabilit y Plot
Within Within Over all
StDev 0.5092 StDev 0.5987
Cp 0.33 Pp 0.28
Cpk 0.27 O v erall Ppk 0.23
PPM 333124.40 Cpm *
PPM 408572.88
Specs
5 10 15 20
Sam ple
Our Bender D-11 is not capable to perform within +/-.5 degree specs

32. DMAIC
Measure
s
es s
oc
Pr alysi
2
an
Define
ari
lti-V
1
Mu
Cause
on
organizati
Analyze
3
Hipotesis
verification
Control
Reg
5
Improve re s ion
Do
E
4

33. Multi-vari analysis
Mai n Ef f ect s Pl ot f or Cur r ent
Data Means
Angle parameter date
55.50
55.25
55.00
Mean
54.75
54.50
.3 .5 .6 .7 .8 v v v v ec ec ec e c ec ec e c ec ec ec
11 11 11 11 11 No No No No D D D D D D D D D D
2 4- 25 - 26- 30- 1- 2- 3- 8 - 9- 1 0- 13 - 14- 15- 1 6-
The Encoder misread angle position, We use a cross reference table to set the angle

34. Time series Plot by angle
set
Ti me Ser i es Pl ot of Cur r ent
56.5 Angle
parameter
11.3
56.0
11.5
11.6
11.7
55.5
11.8
55.0
urrent
54.5
C
54.0
53.5
53.0
1 14 28 42 56 70 84 98 112 126 140
I ndex
We will likely look for extremes in order to see potential DOE variable

35. Facts about Bend precision
●
Angle Precision vs Speed
– Equipment states that Angle precision and speed are
inversely proportional; If we increase speed, the
result angle is less precise.
– the equipment is capable to decelerate the upper
piston speed almost at the end of the bend cycle.
– The set up is obtained by the constants of
deceleration and proportional of speed.
– More details can be found in the equipment’s display.
– Based on this, we determine the variables to use in
our DOE.

36. DOE Matrix and Results.
Std Center Run Prop. Result Result
Order Pt Order Blocks P1 P2 Speed deceleration 1 2
14 1 1 1 950 1600 0.8 10.00 89.3 89.3
3 1 2 1 700 1800 0.5 1.00 83.3 85.2
13 1 3 1 700 1600 0.8 10.00 89.1 88.4
4 1 4 1 950 1800 0.5 1.00 85.4 86.2
11 1 5 1 700 1800 0.5 10.00 89.6 88.9
15 1 6 1 700 1800 0.8 10.00 89.6 89.2
8 1 7 1 950 1800 0.8 1.00 84.3 87.1
16 1 8 1 950 1800 0.8 10.00 89 89.6
6 1 9 1 950 1600 0.8 1.00 86.4 87
10 1 10 1 950 1600 0.5 10.00 89.6 89.6
7 1 11 1 700 1800 0.8 1.00 84.6 86.1
12 1 12 1 950 1800 0.5 10.00 89.4 89.5
2 1 13 1 950 1600 0.5 1.00 86.4 88.1
1 1 14 1 700 1600 0.5 1.00 84.7 86.4
9 1 15 1 700 1600 0.5 10.00 88.8 89.7
5 1 16 1 700 1600 0.8 1.00 84.8 86.3

37. Results of DOE
Ti me Ser i es Pl ot of Resul t
90
89
88
87
Result
86
85
84
83
3 6 9 12 15 18 21 24 27 30
I ndex
Sample order
Results of DOE to be normal due variation as expected.

38. Marginal Plots
Mai n Ef f ect s Pl ot f or Resul t
Data Means
P1 P2
89
88
87
86
Mean
700 950 1600 1800
Speed Prop.
89
88
87
86
0.5 0.8 1.00 10.00
Proportional deceleration has the main effect for the desired result

39. Interaction Plot
I nt er act i on Pl ot f or Resul t Data Means
1600 1800 0.5 0.8 1.00 10.00
90.0
87.5
P1
P1
700
85.0
90.0
950
87.5 P2
P2
1600
1800
85.0
90.0
Speed
87.5 0.5
Speed
0.8
85.0
Prop.
Between Factors, Proportional of deceleration has the main effect for the
desired result

40. Conclusion of DOE
Dot Pl ot of Pr opor t i onal of decel er at i on
95% CI for the Mean
90
89
88
Dat a
87
86
85
1 10
Higher proportional of deceleration factor has the main effect for the desired
result

41. Time Series of DOE
Ti me Ser i es Pl ot
Proportional deceleration change
90
89
88
87
Degr ee
86
85
84
83
3 6 9 12 15 18 21 24 27 30
1 10

42. DMAIC
5 1
CONTROL DEFINE
Soluti
ons
4
IMPROVE 2
FMEA MEASURE
s
t test
Pilo 3
ANALYZE
an
pl
n
io
Act

43. Pilot test Results
Ti me Ser i es Pl ot of Cur r ent -pi l ot
56.5
56.0
UCL
55.5
urrent-pilot
55.0 Mean
LCL
54.5
C
54.0
53.5
53.0
1 17 34 51 68 85 102 119 136 153 170
I ndex
Pilot Test results show and improvement in bend accuracy.

44. Box Plot Pilot
Box pl ot of Cur r ent , Pi l ot
56.5
56.0
USL
55.5
Mean
55.0
Dat a
54.5 LSL
54.0
IQ Range = 0.8 IQ Range = 0.4
53.5
53.0
Current Pilot
Box Plot shows IQ range improvement of 0.4

45. Solution Grid
Solution Status Responsible Due date Comments
Run pilot test to validate constant of deceleration sets. 60
Closed Team 3/7
Pieces run thru all process
Jorge
Conduct a SMED event in D-11 Bender to improve set-up time Closed 5/18
Castellanos
Setup all part numbers parameters and save them in the Set-up technitians were
equipment to avoid missing information due set up technician Closed Jesus Fonseca 3/25 trained to load and save
change/absence. parts in equipment
Parameters reviewed and
Bender Equipment Parameters training to personnel Closed Mario Ruiz 3/15
saved in equipment
Perform TPM to assure proper bender operation and set
preventive maintenance schedule (oil leaks repair, change worn Closed Ramon Garcia
parts)
Trouble shooting
completed, will prepare
Develop a trouble shooting manual for Bender equipment Closed Ramon Garcia
info in binder to deliver
production
Welding fixtures maintenance and verification to assure Welding fixtures reviewed
Closed Ramon Garcia 3/25
dimensions and pass specs.
Review with Pines model
Reset Encoder to absolute 0 degrees Closed Hector Elizondo 4/05
& serial number.
Develop new inspection fixtures (go-no go). Closed Mario Ruiz QC certified the fixture

46. Summary
Description Before After Results Annual savings Improvement
%
Monthly Lost $292 $3 $288 $3,461 98.92%
hours
Scrap Report $3,102 $852 $2,250 $27,000 72.53%
Incorrect Bend $1,705 $14 $1,691 $20,292 99.16%
Rework cost $2,972 $32 $2,940 $35,279 98.91%
Lean Initiatives cost reduction
Annual Improvement
Model Before After Results
savings %
12050-37-85VA $62.09 $59.61 $2.48 $8,683 4.00%
12050-37-86VA $66.84 $65.31 $1.53 $52,044 2.29%
12120-37-746 $85.07 $83.34 $1.73 $23,793 2.03%
12122-37-746 $84.25 $82.53 $1.71 $2,142 2.03%
12122-37-23 $88.47 $86.67 $1.80 $2,249 2.03%
Annual cost Savings $171,482.00

47. DMAIC
1
DEFINE 2
MEASURE
Monit
or i ng
5 3
Evaluating CONTROL ANALYZE
results
ion
ntat
ume
Doc 4
IMPROVE
re
o su
Cl

48. Monitoring
●
As a method to constantly review bend
performance, Team has implemented to
check the bend at the beginning of the run,
every 10 pieces and the last piece, this has
helped understand variation and correct as
necessary.
●
Scrap and Rework has been dramatically
reduced.

49. Scrap monitoring
$6,000.00
$5,000.00
2010 2011
$4,000.00
$3,000.00
$2,000.00
$1,000.00
$0.00
Ja n Feb Ma r Apr Ma y Jun Jul Aug Sep Oct Nov Dec
Average 2010 scrap related to Bend defects was $ 1,979.44
2011 up-to-date scrap average $110. 37

50. Rework cost
Rework cos ts 2011
$60.00
$50.00
$40.00
$30.00
$20.00
$10.00
$-
Ja n Feb Ma r Apr Ma y Jun
Average 2010 rework cost related to Bend defects was $ 2,971.92
2011 up-to-date scrap average $35.39