3. 3
Background
Current archiving accomplished
with large, expensive
equipment
endogo® combines
portability/simplicity with need
for endoscopic imagery
Provides a platform that
combines available imaging
technology with the endoscope
Result: Compact, digital
endoscopic imaging device,
ergonomically designed to
provide maximal comfort for
short and prolonged use
4. 4
Goal
Recommend design and assembly
process changes that will enable
production of the endogo® at reduced
cost, increased speed and higher quality
5. 5
Problem Definition
Design effort focused on functionality –
This project focuses on manufacturability
Metrics guide the project
Cycle Time
Metrics and Order-Winning Criteria (OWC)
assist in identification of figures of merit
Weighting matrix resulted in metrics
selected for this project
6. 6
Approach
Model/Analyze Baseline Design
Extend® Model
Part-count reduction
DFA Index Estimation
Insertion Time Estimation
Acquisition Time Estimation
Defect Estimation and Defect Table
Cycle Time, Distance, Quality, Inventory
Estimation
7. 7
Approach (continued)
Model/Analyze New Design
Extend® Model
Material Selection (Dimensionless Ranking)
DFA Index Estimation
Defect Estimation
Cycle Time, Distance, Quality, Inventory
Estimation
8. 8
Approach
Flowchart
Tasks
Interdependent
- DFA Index
- Inventory Turns
- Quality
- Distance
- Cycle Time
Baseline Design
Extend
Model
Part-Count
Reduction
Assembly /
Acquisition
Time
Estimation
Probability
of Defect
Calculation
Metrics
“Filter”
Process
Redesgin
Material
Selection
(Dimensionless
Ranking)
New Process
(Assembly)
New Product
(Manufacture)
New Design
- DFA Index
- Inventory Turns
- Quality
- Distance
- Cycle Time
Compare
10. 10
Extend Model (1 of 2)
Benefits of Starting with the Model
Clear understanding of the process
Provides Inventory Turns estimate
Inventory Turns calculated for the baseline
and new designs
$,
$,
InventoryAverageDaily
AnnuallySoldGoodsofCost
TurnsInventory
11. 11
Extend Model (2 of 2)
Average daily inventory taken from the
model by determining stock and work in
process
Cost of goods sold in a year taken from
the total number of cameras produced in a
single model run (simulates one year)
13. 13
Baseline Extend Model (2 of 5)
Order Size (Cameras per Order) is
calculated by dividing subassembly lead
time (Minutes per Order) by the endogo
lead time (Minutes per Camera)
TimeLeadendogo
TimeLeadySubassembl
SizeOrder
16. 16
Baseline Extend Model (5 of 5)
Cycle Time variation due to production approach
10 built in rapid succession followed by long period
until next 10
With 1 piece flow, Cycle Time between 285 and 276
minutes at the 99% confidence level
Average Cycle Time representative of system’s true
capability because demand exceeds capacity
Inventory Turns calculated across 30 model runs
Metric Average Upper Bound
(99% Confidence)
Lower Bound
(99% Confidence)
Inventory Turns 10.9 11.0 10.8
Cycle Time, min 278 387 169
18. 18
DFMA Considerations (1 of 12)
Part Count Reduction
During operation of the product, does the part
move relative to all other parts already
assembled?
Must the part be of a different material than or
be isolated from all other parts already
assembled?
Must the part be separate from all other parts
already assembled because otherwise
necessary assembly of other separate parts
would be impossible?
19. 19
DFMA Considerations (2 of 12)
Part count reduced from
92 to 42
Example: Display
Mounting Ring and LCD
Ring Neck
Injection Mold the neck
and ring in once piece
The result, 42, is Nmin in
the DFA Index (next)
20. 20
DFMA Considerations (3 of 12)
DFA Index Calculation
assemblycompletetotimeestimatedt
partonefortimeassemblybasict
partsofnumberltheoreticalowestN
IndexDFAE
where
ttNE
ma
a
ma
maama
min
min
,
/
21. 21
DFMA Considerations (4 of 12)
ta calculation
Boothroyd assumes 3 seconds
Assumes no knowledge of actual process
Attempt to find a basic assembly time tailored
to this particular design
22. 22
DFMA Considerations (5 of 12)
ta calculation
First Attempt: DFA Index Greater than One
timecycletheofdevst
designbaselineinpartsofnumberactualN
cameraonebuildtorequiredtimeCT
where
N
CT
t
CT
actual
actual
CT
a
..
,
282.1
23. 23
DFMA Considerations (6 of 12)
ta calculation
Second Attempt: Data not Normal
steppertimeassemblyestimatedtheofdevst
steppertimeassemblyestimatedaveraget
where
tt
estimated
averageestimated
estimatedaverageestimateda
..
,
282.1
,
,
24. 24
DFMA Considerations (7 of 12)
ta calculation
Second Attempt: Data not Normal
Assembly Times, seconds
Percent
2520151050-5
99
95
90
80
70
60
50
40
30
20
10
5
1
Mean
<0.005
7.355
StDev 5.435
N 30
AD 1.967
P-Value
Normality Test of the Assembly Times
Normal
25. 25
DFMA Considerations (8 of 12)
ta calculation
Third Attempt: Log-normal Successful
Log of Assembly Times
Percent
1.61.41.21.00.80.60.40.20.0
99
95
90
80
70
60
50
40
30
20
10
5
1
0.411
10
Mean
0.542
0.7733
StDev 0.2824
N 30
AD 0.307
P-Value
Normality Test of the Log of Assembly Times
Normal
26. 26
DFMA Considerations (9 of 12)
ta calculation
Third Attempt: Log-normal Successful
Log of Assembly Times
Percent
1.61.41.21.00.80.60.40.20.0
99
95
90
80
70
60
50
40
30
20
10
5
1
0.411
10
Mean
0.542
0.7733
StDev 0.2824
N 30
AD 0.307
P-Value
Normality Test of the Log of Assembly Times
Normal
58.2411.0
411.0log
10
10
x
x
27. 27
DFMA Considerations (10 of 12)
EASY TO
ALIGN
NOT EASY
TO ALIGN
EASY TO
ALIGN
NOT EASY
TO ALIGN
EASY TO
ALIGN
NOT EASY
TO ALIGN
0 1 2 3 4 5
NO ACCESS OR
VISION
DIFFICULTIES
0 1.5 3 2.6 5.2 1.8 3.3
OBSTRUCTED
ACCESS OR
RESTRICED VISION
1 3.7 5.2 4.8 7.4 4 5.5
OBSTRUCTED
ACCESS AND
RESTRICTED VISION
2 5.9 7.4 7 9.6 7.7 7.7
COPYRIGHT 1999 BOOTHROYD DEWHURST, INC.
SECURED BY SEPARATE OPERATION OR PART
NO HOLDING DOWN HOLDING DOWN
SECURED ON INSERTION
BY SNAP FIT
tma Calculation: Insertion Time Estimate
28. 28
DFMA Considerations (11 of 12)
< 2mm < 2mm
SIZE > 15mm 6mm < SIZE < 15mm SIZE > 6mm SIZE > 15mm 6mm < SIZE < 15mm SIZE > 6mm
0 1 2 3 4 5
SYM < 360 0 1.13 1.43 1.69 1.84 2.17 2.45
360 ≤ SYM < 540 1 1.5 1.8 2.06 2.25 2.57 3
540 ≤ SYM < 720 2 1.8 2.1 2.36 2.57 2.9 3.18
SYM = 720 3 1.95 2.25 2.51 2.73 3.06 3.34
FOR PARTS THAT CAN BE GRASPED AND MANIPULATED WITH ONE HAND WITHOUT THE AID OF GRASPING TOOLS
COPYRIGHT 1999 BOOTHROYD DEWHURST, INC.
NO HANDLING DIFFICULTIES PART NESTS OR TANGLES
THICKNESS > 2mm THICKNESS > 2mm
tma Calculation: Acquisition Time Estimate
29. 29
DFMA Considerations (12 of 12)
tma calculation: Sum all estimates
ta, s tma, s Nmin Ema
Baseline Design 2.58 2273 33 0.04
34. 34
Workstation Changes
Contain all parts on the workbench rather
than in the storage rack
Do not “kit” each camera in the same bin
Organize each part bin in order of
assembly
Mark bins with part number and picture bin
36. 36
DFA Index Values
ta, s tma, s Nmin Ema
Baseline Design 2.58 2273 33 0.04
New Design 2.58 221 33 0.4
tma estimated primarily by way of
Boothroyd techniques
10-fold decrease in tma led to 10-fold
increase in DFA Index
The ideal would take 85 seconds to
assemble
38. 38
Quality Estimates
assemblyperoperationsofnumbern
soperationpertimeassemblyestimatedDFAaveraget
assemblyperdefectofyprobabilitD
where
tforD
tfortD
i
a
ia
i
n
ia
,
,
3,0
3,30001.011
n ti, seconds Da, ppm
Baseline Design 76 30 190,000
New Design 29 7.0 12,000
40. 40
Material and Process Selection
Dimensionless Ranking
rd parametethe derived to formhat is useExponent tm
determinedis beinghe N-valueor which tmaterial ftheofpropertynP
sg materialengineerinof commonrangeaforparameterderivedLowestD
sg materialengineerinof commonrangeaforparameterderivedHighestD
parameterDerivedD
PPPD
where
DDDDN
n
thn
m
n
mm n
min
max
21
minmax10min10
21
,
)/(log/)/(log100
Derived Parameter Description Exponents
m1 m2 m3 m4 m5
Best YT at Minimized Weight and $ -1 1 0 0 -2
Best YC and Minimized Weight and $ -1 0 0 1 -2
Best Beam/Plate Strength at Minimized Weight and $ -1 1/2 0 0 -2
Best Stiffness at Minimized Weight and $ -1 0 1/3 0 -2
42. 42
Stiffest at minimum
weight and cost
Strongest in Tension
at minimum weight
and cost
Stiffest Material at Minimum Weight
and Cost
Strongest Tension Member at
Minimum Weight and Cost
Particle Board 100 Pine 100
Cork 99 Particle Board 90
Pine 97 Glass 81
Concrete 90 Polyurethane Foam 78
Glass 85 Cork 78
Pottery 81
Polycarbonate (Glass-
reinforced) 77
Polyurethane Foam 79 Ductile Iron 74
Polyethylene (high-density) 77 Polyethylene (high-density) 73
Polycarbonate (Glass-
reinforced) 71 Gray Cast Iron 72
Gray Cast Iron 69 Malleable Iron 69
Ductile Iron 68 Pottery 65
Malleable Iron 65 Magnesium 64
Magnesium 61 Rubber 63
Al (High Strength) 58 Al (High Strength) 57
Mild Steel 57 Mild Steel 56
Epoxy 55 Alloy Steel 54
Rubber 51 Epoxy 54
Stainless Steel 47 Concrete 48
Copper, Hard 44 Titanium 46
Alloy Steel 41 Stainless Steel 44
Silicon Carbide (Sintered) 38 Copper, Hard 44
Titanium 35
Aluminum-Lithium Alloys
(2090) 34
Lead 33 Beryllium Copper 32
Aluminum-Lithium Alloys
(2090) 29 Silicon Carbide (Sintered) 19
Beryllium Copper 22 Lead 11
Diamond 17 Diamond 5
Tungsten Carbide 0 Tungsten Carbide 0
43. 43
Strongest in
compression at
minimum weight and
cost
Strongest beam at
minimum weight and
cost
Strongest Compression Member at
Minimum Weight and Cost
Strongest Beam or Plate at Minimum
Cost and Weight
Glass 100 Cork 100
Pottery 84 Pine 100
Pine 82 Particle Board 99
Particle Board 81 Polyurethane Foam 88
Polyurethane Foam 70 Glass 82
Cork 68 Polyethylene (high-density) 81
Concrete 67
Polycarbonate (Glass-
reinforced) 76
Polycarbonate (Glass-
reinforced) 67 Pottery 73
Polyethylene (high-density) 64 Rubber 72
Gray Cast Iron 62 Concrete 72
Ductile Iron 61 Ductile Iron 69
Malleable Iron 60 Gray Cast Iron 69
Epoxy 58 Malleable Iron 66
Magnesium 55 Magnesium 63
Rubber 53 Epoxy 60
Al (High Strength) 48 Al (High Strength) 58
Mild Steel 47 Mild Steel 56
Alloy Steel 45 Alloy Steel 46
Silicon Carbide (Sintered) 37 Stainless Steel 45
Titanium 36 Copper, Hard 44
Stainless Steel 34 Titanium 40
Copper, Hard 34
Aluminum-Lithium Alloys
(2090) 33
Aluminum-Lithium Alloys
(2090) 23 Silicon Carbide (Sintered) 28
Diamond 22 Beryllium Copper 27
Beryllium Copper 22 Lead 27
Tungsten Carbide 7 Diamond 10
Lead 0 Tungsten Carbide 0
44. 44
Full list of candidate
polymersCost
Tensile Yield
Strength
Elastic
modulus Density Autoclave?
$/kg MN/m2 MN/m2 kg/m3
Polyethylene
(high-density) 1.39 24.8 1080 971 No
Polycarbonate
(30% Glass-
reinforced) 2.45 118 11600 1433 Yes
Elastomer - Nitrile
Elastomer - SBR
Elastomer -
Thermoplastic
For design simplification, elastomers will not be used. Buttons will be of
the same material as the case.
Epoxy
Epoxy was lower rated than HDPE in initial screening. Typically used in
composites. This is also a thermoset.
Nylon 6,6 1.79 69 2515 1140 No
Phenolic Brittle thermoset
Polycarbonate
(PC) 2.45 63.8 7580 1200 Yes
Polyester
(thermoset) Thermoset
PEEK Not injection moldable and is very expensive
LDPE 1.79 11.75 225 924.5 No
UHMWPE 2.49 24.5 690 940 ?
PET 2.82 59.3 3450 1345 ?
PMMA Transparent
Polypropylene(PP) 1.81 32.6 1345 931 Yes
PS Relatively brittle and transparent
PTFE Poor cold flow properties
PVC 1.98 42.75 3250 1440 No
Silicone, flexible
cast Not injection moldable
Heat Resistant
ABS 2.19 43.5 2200 990 Yes
Acrylic Transparent
Acetal 3.09 66 3800 1465 No
45. 45
Final list of candidate
polymers
Compared relative to one
another
Some compared but not
listed:
High Density Polyethylene
Nylon 6,6
Low Density Polyethylene
Polyvinyl Chloride
Acetal
Tension
Beam or
Plate
Strength
Stiffest
Beam Average
Polycarbonate
(30% Glass-
reinforced)
73 29 65 56
Polycarbonate
(PC)
64 39 76 60
Ultra-high
Molecular Weight
Polyethylene
(UHMWPE)
62 69 81 71
Polyethylene
Terephthalate
(PET)
65 43 70 59
Polypropylene
(PP)
100 100 100 100
Heat Resistant
Acrylonitrile
butadiene styrene
(ABS)
98 89 95 94
47. 47
New Design Extend Model
Fundamental structure remains the same
Reduction of the number of steps due to
part count reduction
Elimination of “pre-work”
Reduction of re-work
53. 53
Deliverables
Product design changes
Process design changes
Material selection changes
Inventory Turns estimation for baseline and new design
Quality estimation for baseline and new design
Distance estimation for baseline and new design
Cycle Time estimation for baseline and new design
Extend® - based model of manufacturing processes for
baseline and new design
Final report
Final defense briefing
55. 55
OWC
BACK
Order-Winning Criterion Definition
Price The cost to the consumer of the product under
consideration.
Quality The perceived quality by the consumer of the product
under consideration.
Lead Time The duration of time from the moment the consumer
orders the product under consideration to the moment of
consumer receipt.
Delivery Reliability The repeatability of lead time.
Flexibility The number of parts that can be produced on the same
machine.
Innovation Ability An organization’s capacity for producing new marketable
products.
Size The volume of the product under consideration.
Design Leadership An organization’s capacity for transforming concepts into
finished products.
56. 56
Metrics Identified for Project
BACK
Metric Weighted
Score
Redesign
Target
Inventory 14 30 turns
Quality 11
Captured
and
Warranty: ≤
44000 ppm
Distance 11 ≤ 5000 feet
Cycle Time –
≤ 120
minutes
58. 58
Metric Units Definition
Inventory Inventory
Turns
Inventory Turns for a product is equal to the cost of
goods sold divided by the average inventory value
Flexibility number of
parts
The number different parts that can be produced on
the same machine.
Distance feet The measure of the total linear feet of a part’s travel
through the plant from raw material in receiving to
finished products in shipping. This includes the
sum of the individual routes of each subassembly.
For example, if a plant manufactures a paper cup,
the side of the cup travels 10 feet to get to the
location where it is mated to the bottom. The
bottom at that point has also traveled 10 feet. After
the two are mated, it travels another 10 feet to be
given a finish and then to shipping. The total
Distance is then 30 feet.
Uptime percent The percentage of time a machine is producing to
specifications compared to the total time that
production can be scheduled.
Metrics (continued)
BACK
60. 60
Dimensionless Ranking
rd parametethe derived to formhat is useExponent tm
valuethe lowestat it hasexcept thSame as PP
ialsring materon engineege of commfor a ranhest valueas the higial that hof a materpropertynP
determinedis beinghe N-valueor which tmaterial ftheofpropertynP
propertiesvaluedlowesttheofallofncombinatiothewithparameterDerivedD
propertiesvaluedhighesttheofallofncombinatiothewithparameterDerivedD
parameterDerivedD
PPPD
PPPD
PPPD
where
DDDDN
n
n,n
thn
thn
m
n
mm
m
n
mm
m
n
mm
n
n
n
maxmin,
max,
min
max
min,min,2min,1min
max,max,2max,1max
21
minmax10min10
21
21
21
,
)/(log/)/(log100
BACK
61. 61
Dimensionless Ranking Example
Five parameters form derived
parameters
1. Cost, $/kg
2. Tensile Yield Strength, MN/m2
3. Elastic Modulus, MN/m2
4. Compressive Yield Strength, MN/m2
5. Density, kg/m3
BACK
62. 62
Most likely derived parameter will be “best
tensile yield strength at minimized cost”
Using previous numbering convention and
dimensionless parameter equation: m2 = 1,
m1 = m5 = -1, and m3 = m4 = 0
This produces the derived parameter:
Yt /r Cm
Dimensionless Ranking Example
BACK
64. 64
Part-count Reduction
During operation of the product, does the part
move relative to all other parts already
assembled?
Must the part be of a different material than or
be isolated from all other parts already
assembled?
Must the part be separate from all other parts
already assembled because otherwise
necessary assembly of other separate parts
would be impossible?
BACK
67. 67
Probability of Defect (Entire
Assembly)
assemblyperoperationsofnumbern
soperationpertimeassemblyestimatedDFAaveraget
assemblyperdefectofyprobabilitD
where
tforD
tfortD
i
a
ia
i
n
ia
,
,
3,0
3,30001.011
BACK
