Team Rowland
Presenter 1: Elizabeth Rowland (E.R.)
Presenter 2: Juan Guerrero (J.G.)
Presenter 3: Tarun Aggarwal (T.A.)
Presenter 4: Norihiko Hosokawa (N.H.)
Six Sigma DMAIC Methodology (E.R)
Define
Control
Implement
Measure
Analyze
Eaton Corporation
•
•
•
•
•
(E.R)
Power management company
102,000 employees
$22 billion sales in 2013
Customers in 175+ countries
Four main business sectors
– Electrical, Aerospace, Vehicle, and Hydraulics
Define
Measure
Analyze
Implement
Control
Eaton Corporation: Sector of Focus(E.R)
•
•
•
•
•
Power management company
102,000 employees
$22 billion sales in 2013
Customers in 175+ countries
Four main business sectors
– Electrical, Aerospace, Vehicle, and Hydraulics
• Customer Manufacturing Solutions Centers (CMSCs)
Define
Measure
Analyze
Implement
Control
Problem Definition
(E.R)
• CMSCs must improve their supply chain
network by:
– Reducing premium freight frequency
– Managing overall inventory
• CMSCs must increase their future growth
sustainability
Define
Measure
Analyze
Implement
Control
0.2
10%
0%
Define
Measure
Analyze
Implement
Control
Dallas-SVC
Denver-SVC
New Jersey-SAT
Sea le-SAT
Cleveland-SAT
Bal more-SAT
St Louis-SAT
Phoenix-SAT
Har ord-SAT
Orlando-SAT
Chicago-SAT
Houston-SAT
Raleigh-SAT
San francisco-SAT
Denver-SAT
Atlanta-SVC
Atlanta-SAT
Portland-SVC
Chicago-SVC
Har ord-SVC
Los Angeles-SVC
Dallas-SAT
Houston-SVC
Los Angeles-SAT
Measurement
(E.R)
2013 Avg. Inventory (MUSD) - Pareto analysis
1.8
100%
1.6
90%
1.4
80%
1.2
70%
1.0
60%
0.8
50%
40%
0.6
30%
0.4
20%
0.2
10%
0%
Dallas-SVC
Denver-SVC
New Jersey-SAT
Sea le-SAT
Cleveland-SAT
Bal more-SAT
St Louis-SAT
Phoenix-SAT
Har ord-SAT
Orlando-SAT
Chicago-SAT
Houston-SAT
Raleigh-SAT
San francisco-SAT
Denver-SAT
Atlanta-SVC
Atlanta-SAT
Portland-SVC
Chicago-SVC
Har ord-SVC
Los Angeles-SVC
Dallas-SAT
Houston-SVC
Los Angeles-SAT
Measurement
1.8
100%
1.6
1.4
1.2
90%
0.6
0.4
Define
(E.R)
2013 Avg. Inventory (MUSD) - Pareto analysis
1.0
80%
0.8
70%
60%
50%
40%
30%
20%
Measure
Analyze
Implement
Control
160
6/9
140
120
20
10%
0%
Dallas-SVC
San francisco-SAT
Los Angeles-SAT
Chicago-SVC
Los Angeles-SVC
Denver-SAT
Houston-SVC
Raleigh-SAT
Chicago-SAT
Portland-SVC
Sea le-SAT
Houston-SAT
Orlando-SAT
New Jersey-SAT
Har ord-SVC
Atlanta-SAT
Cleveland-SAT
Phoenix-SAT
Dallas-SAT
Denver-SVC
Har ord-SAT
St Louis-SAT
Bal more-SAT
Atlanta-SVC
(000) Pounds
Measurement
(E.R)
2013 Orders shipped - Premium shipment by CMSC (pounds) Pareto analysis
9/13
100
40
WEST USA:
High inventory levels and high premium shipped
orders
100%
90%
80%
70%
80
60%
50%
60
40%
30%
20%
Analysis Part I: Transportation Cost (J.G)
Sources
CMSC
Define
Measure
Analyze
Implement
Control
CMSC
Analysis Part I: Transportation Cost
NC
SC
South East
35%
41%
North East
30%
Mid West
Sources
LA
Dallas
PA
TX
11%
10%
3%
48%
7%
11%
3%
37%
46%
6%
9%
3%
South
30%
51%
7%
9%
3%
South West
28%
32%
16%
6%
12%
6%
North West
47%
27%
12%
5%
7%
3%
West
35%
37%
11%
5%
10%
3%
CMSC:
• SE = Atl-Ral-Orl
• NE = Bal-NJ-Cle-Har
• MW = Chi-StL
• S = Dal-Hou
• SW = SF-LA-Pho
• NW = Sea-Por
• W = Den
Define
Short term
Sources:
• NC = Fayettville-ArdenRaleigh
• SC = Sumter-W34
• LA = W87
• Dallas = CDC&DBN
* P.Rico & Others not
included in analysis
Measure
Analyze
Implement
Control
(J.G)
Analysis Part I: Transportation Cost
!"
#"
#"
!"
345
675
345
395 6: 5
395
3@5 6A5
3@5
395 475
395
( ) " 3B5
()"
6@5 ( %"
6@5
345 3@5
345
#"
675
675
6: 5
6: 5
6A5
6A5
475
475
3B5
3B5
( %"
( %"
3@5
3@5
#- . 8C?)
#- . 8C?)
8C?)
$% $%#-&'. (('
)&' ((' ) *%
$%
&' ((' )
! ! " ! ! " ! #"
!!"
%" %" ! ! "
%"
&" &" ' "
&"
%" %" ' "
%"
! &" ! &" &" &" ! ( "
! &"
&"
! ( " ! ( " *" *" %"
!("
*"
! ! " ! ! " *" *" ! #"
!!"
*"
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!*%
#" $"
! #"
! ! " $"
!!"
' " $"
'"
' " $"
'"
! ( " &"
!("
%" $"
%"
! #" $"
! #"
mated
savings
due
Es Esmated
savings
due
to to
Essourcing
mated re-alloca
savings due
to
sourcing re-alloca on:on:
sourcing
re-alloca
800
KUSD/y on:
800
KUSD/y
800 KUSD/y
Define
mizaonon
Model:
OpOpmiza
Model:
Op miza on Model:
Objecveve
Funcon:on:
Minimize
freight
cost
• • Objec
Func
Minimize
freight
cost
• Objec ve Func on: Minimize freight cost
Variables:
Pounds
CMSC
Source
• • Variables:
Pounds
toto
CMSC
Source
i from
i from
j j
• Variables: Pounds to CMSC
i from Sourcej
Restricons:
ons:
• • Restric
• Restric ons:
Demand
must
sfied
• • Demand
must
bebe
sasasfied
• Demand must be sa sfied
Source
capacity
limitaons
ons
• • Source
capacity
limita
• Source capacity limita ons
+,
+,
$"
$"
$"
$"
$"
$"
$"
$"
&"
&"
$"
$"
$"
$"
. 2'
/01
2' )/
#- .#-/01
)/
#- . /012' )/
! - 7/01
2' )/
! - 7/01
2' )/
! - 7/012' )/
: =;<1
= >)/
: ;<1
>)/
: ;<1= >)/
#- .#-/0. /0
#- . /0
. =/01
= >)/
#- .#-/01
>)/
#- . /01= >)/
! - 7/01
= >)/
! - 7/01
= >)/
! - 7/01= >)/
= >)/
= >)/
= >)/
": #"
": ":#"#"
#-2'. )/
/012' )/345
#- . /01
#- . /012' )/
! 2'
- 8/01
! - 8/01
)/ 2' )/395
! - 8/012' )/
;
<
=1
; <=1> ?)/> ?)/ 3@5
; <=1> ?)/
#- . /0#- . /0
395
#- . /0
#->. ?)/
/01> ?)/
#- . /01
()"
#- . /01> ?)/
! >- 8/01
! - 8/01
?)/> ?)/
6@5
! - 8/01> ?)/
> ?)/> ?)/
345
> ?)/
"; #"
"; #"
"; #"
!"
J.G
Short term
Measure
! "! "
!"
334334
334
584584
584
?@4?@4
?@4
Analyze
#" #"
#"
564564
564
?@4?@4
?@4
9@
9@@
4 @4
9@@4
BB4BB4
BB4
9@
9@@
4 @4
9@@4
B4 B4
B4
. 7C>)
#- .#-7C>)
#- . 7C>)
&' )((' )
$% $% &' (('
$%
&' ((' )
*%*%
*%
+, +,
+,
394394
394
A@4A@4
A@4
354354
354
Implement
964964
964
8B48B4
8B4
Control
Analysis Part I: Transportation Cost Long term
Op miza on Model:
Op miza on Model:
• Objec ve Func on: Minimize freight cost
• Objec ve Func on: Minimize freight cost
• Variables: Pounds to CMSCi from Sourcej
• Variables: Pounds to CMSCi from Sourcej
• Restric ons:
• Restric ons:
• Sa sfied demand
• Sa sfied demand
• Source capacity limita ons
• Source capacity limita ons
Capacity
Capacity
"$%
%&' ()"*+*, -(. )
"$%
%&'*1()"*+*, -(. )
/ +(-0
/ +(-0 *1
2 -33&%&' , &
2 -33&%&' , &
!"
! " &'
! "#! $"%
&'
)!"("#!
#)$"%
"( &%
) "( #) "( &%
' "' %%") $(
' "' %%") $(
#"
( "#' )#""*&$
) "*&$
!("'"#'
( *")
%(
! "' ( *") %(
LA
&' %LA
"%) $
&'
%
"%)*($
! ") ! $"(
! ") ! $"( *(
Dallas
Dallas
%*$")
$$
%
*$")
$$
*++"+++
*++"+++
' "( #( "&*& ,) "%) ' "%&& ,' +"%+'
' "( #( "&*& ,) "%) ' "%&& ,' +"%+'
PA
PA %
' "+$+"&%
"+$+"&%%
' '"+++"+++
' "+++"+++
$+"&%%
$+"&%%
TX
TX
! %+"+++
+"+++
!!%%
+"+++
! %+"+++
+
+
The op mal alloca on shows that a capacity enhancement 2.5 to 3.0
The op mal alloca on shows that a capacity enhancement 2.5 to 3.0
Million Pounds in LA (West Coast) will be op mal
Million Pounds in LA (West Coast) will be op mal
ESTIMATED SAVINGS =
ESTIMATED SAVINGS =
12.8 MUSD/y
12.8 MUSD/y
Define
Measure
Analyze
Implement
Control
J.G
Implementation & Control Part I (J.G)
Recommendations
• SHORT-TERM RECOMMENDATIONS:
– Revise sourcing allocation
• Implement optimization models
• Identify current & future bottle-necks
• Reduce logistic costs due to sourcing changes
• RISKS & CONSIDERATIONS:
– Verify Source capacities
– Verify distances between Sources and CMSCs
– Determine if production streamline can be achieved (1
source to 1 CMSC?)
Define
Measure
Analyze
Implement
Control
Analysis Part II: Inventory Control (T.A)
SATs
2,400,000.00
2,200,000.00
2,000,000.00
1,800,000.00
1,600,000.00
1,400,000.00
1,200,000.00
1,000,000.00
800,000.00
600,000.00
400,000.00
200,000.00
lb
s)
on
l(
in
ca
Le
ve
Lo
To
ta
l
In
ve
nt
or
y
28
31
-J a
n2
01
3
-F
eb
-2
01
31
3
-M
ar
-2
01
30
3
-A
pr
-2
01
31
3
-M
ay
-2
01
30
3
-J u
n20
13
31
- Ju
l-2
01
30
3
-A
ug
-2
01
3
9/
31
/2
01
31
3
-O
ct
-2
01
30
3
-N
ov
-2
01
31
3
-D
ec
-2
01
3
-
Atlanta-SAT
Bal more-SAT
Chicago-SAT
Cleveland-SAT
Dallas-SAT
Denver-SAT
Har ord-SAT
Houston-SAT
Los Angeles-SAT
Orlando-SAT
Phoenix-SAT
Raleigh-SAT
San francisco-SAT
Sea le-SAT
St Louis-SAT
Define
Measure
Analyze
Implement
Control
Analysis Part II: Inventory Control (T.A)
SVCs
1,800,000.00
1,600,000.00
1,400,000.00
1,200,000.00
1,000,000.00
800,000.00
600,000.00
400,000.00
200,000.00
lb
s)
(in
on
In
ve
n
to
r
yL
ev
el
Lo
ca
To
ta
l
13
20
3
31
-D
e
c-
01
3
30
-N
ov
-2
01
3
-O
31
31
9/
ct
-2
01
3
/2
01
3
ug
-2
01
30
-A
13
-J u
l -2
31
20
3
30
-Ju
n-
01
3
31
-M
ay
-2
01
3
30
-A
pr
-2
01
3
ar
-2
01
-2
-M
31
-F
eb
28
31
- Ja
n-
20
13
-
Atlanta-SVC
Chicago-SVC
Dallas-SVC
Denver-SVC
Har ord-SVC
Houston-SVC
Los Angeles-SVC
Portland-SVC
Define
Measure
Analyze
Implement
Control
Analysis Part II: Inventory Control (T.A)
Kanban System
Define
Measure
Analyze
Implement
Control
Analysis Part II: Challenge at Hand (T.A)
High Level of Varia on
Mean & Standard Devia on
200,000
60000
180,000
40000
120,000
100,000
30000
80,000
20000
60,000
40,000
Higher Safety Stocks at
loca ons
10000
20,000
St Louis-SAT
Sea le-SAT
San francisco-SAT
Raleigh-SAT
Portland-SVC
Phoenix-SAT
Orlando-SAT
New Jersey-SAT
Los Angeles-SAT
Los Angeles-SVC
Houston-SVC
Houston-SAT
Har ord-SVC
Har ord-SAT
Denver-SAT
Denver-SVC
Dallas-SVC
Dallas-SAT
Cleveland-SAT
Chicago-SVC
Chicago-SAT
Bal more-SAT
0
Atlanta-SVC
Atlanta-SAT
Mean
140,000
Standard Devia on
50000
160,000
Increased Inventory Levels
Loca on
Mean
Define
Standard Devia on
Measure
Analyze
Implement
Control
Analysis Part II: Challenge at Hand (T.A)
Causes
Effects
Improper Forecasting of demand
 Stock outs in CMSCs.
 Higher orders leading to increased lead times
Shifting of demand to different
facilities
 Reduced capability to fix inventory to facilities
Basic reliance on truck and air for
transportation
 Truck transport results in longer lead time
 Air transport results in higher transport cost
Product shipment normally of LTL
size
 Increases number of shipments and adds to
overall cost
Low Risk
Define
Moderate Risk
Measure
Analyze
High Risk
Implement
Control
Analysis Part II: Facing the Challenge
Process Optimization
Supply Chain
Production Plants
T.A
1. Maintain the 3-day shipment cycle.
2. Prioritize west-coast orders to counter higher lead time
Consolidation &
Transportation
1. Employ third party transportation to avoid LTL
shipments
2. Consider shipping via rail routes
W87 Distribution
Center
1. W87 to cater specifically to west coast CMSCs
2. Increase buffer stock levels in W87 to reduce inventory
buildup in CMSCs
New Distribution
Centre
1. Function in parallel with west coast facilities to meet
demand
2. Employ resource pooling to reduce safety stock build up
Define
Measure
Analyze
Implement
Control
Implementation: Options
1. Build a new warehouse in Western USA
• Decrease lead me and inventory levels
• Give flexibility on major warehouses
• Ensure capacity for future growth
2. Improve demand forecast models
• Consider trends and seasonality
3. Verify Kanban reorder point
• Adjust to new demands
• Adjust lead mes once new WH is built
Define
Measure
Analyze
Implement
Control
Option 1: Build New Warehouse (N.H)
• Decrease lead time in
Western area
• Decrease inventory
levels in Western area
• Decrease frequency of
premium freights
• Lower transportation
costs
• Give flexibility to major
warehouses
Define
Measure
• Not small amount of
capital expenditure
• Not easy to redesign
supply chain
• Not easy to find the place
Analyze
Implement
Control
Option 2: Review Demand Forecast
Define
Measure
Analyze
Implement
Control
N.H
Option 3: Verify Re-order Point (N.H)
• Decrease excess
inventory and shortage
• Easy to implement
Define
Measure
• Not necessarily eradicate
shortage
• Not necessarily decrease
lead time
Analyze
Implement
Control
Implementation Plan
(N.H)
Identify location
* Close to a major city
* Coverage of CMSCs
Legal formalities
* State Govt. regulations
* Compliance
Design capabilities
* Supply chain networks
* Capacity
Construction
* Shorter lead time
* Better inventory levels at CMSCs
Define
Measure
Analyze
Implement
Control
Control: Overcoming Potential Risk
N.H
Risk
Level of Impact
Mi ga on Plan
Amount of capital
expenditure
Medium
Conduct due diligence on cost
and benefit
Redesign of supply chain
networks
High
Collaborate with and involve
employees from warehouses
and CMSCs
Place of the warehouse
Medium
Consider mul ple candidates
Define
Measure
Analyze
Implement
Control
Road to Success
(N.H)
END
Additional Slides
Optimization Model
Demand (pounds)
Atlanta-SAT
Baltimore-SAT
Chicago-SAT
Cleveland-SAT
Dallas-SAT
Denver-SAT
Hartford-SAT
Houston-SAT
Los Angeles-SAT
New Jersey-SAT
Orlando-SAT
Phoenix-SAT
Portland-SVC
Raleigh-SAT
San francisco-SAT
Seattle-SAT
St Louis-SAT
Total
Cost/pound
Atlanta-SAT
Baltimore-SAT
Chicago-SAT
Cleveland-SAT
Dallas-SAT
Denver-SAT
Hartford-SAT
Houston-SAT
Los Angeles-SAT
New Jersey-SAT
Orlando-SAT
Phoenix-SAT
Portland-SVC
Raleigh-SAT
San francisco-SAT
Seattle-SAT
St Louis-SAT
Fayetteville, NC
522,843
25,051
389,866
42,768
51,429
257,979
369,556
485,814
418,895
44,237
49,270
45,462
287,345
42,197
32,223
27,709
62,902
3,155,546
Sumter, SC
107,241
67,843
110,559
87,583
138,862
138,416
104,196
93,768
192,349
93,031
126,443
102,557
0
77,838
91,335
67,311
104,482
1,703,816
Fayetteville, NC
0.16
0.15
0.19
0.19
0.22
0.40
0.17
0.22
0.45
0.16
0.14
0.41
0.48
0.07
0.50
0.48
0.21
Sumter, SC
0.11
0.20
0.20
0.20
0.20
0.39
0.20
0.20
0.43
0.20
0.11
0.39
0.48
0.20
0.48
0.48
0.20
W34
237,863
94,190
301,061
165,765
459,202
171,650
297,903
308,396
170,808
79,596
132,722
41,376
62,538
143,225
50,581
67,130
125,038
2,909,043
W34
0.11
0.20
0.20
0.20
0.20
0.39
0.20
0.20
0.43
0.20
0.11
0.39
0.48
0.20
0.48
0.48
0.20
W87
731
548
3,679
1,021
1,422
89,864
4,110
4,407
206,519
640
1,770
46,520
33,438
1,049
69,150
51,993
869
517,729
W87
0.92
1.10
0.47
0.75
0.28
0.24
0.74
0.30
0.00
0.92
0.66
0.07
0.19
2.67
0.07
0.19
0.46
CDC & DBN
112,343
48,290
40,704
35,482
83,527
45,417
39,192
51,912
60,072
27,734
52,507
25,946
187
59,869
34,052
33,476
38,588
789,299
Arden, NC
11,797
19,230
16,459
9,490
0
3,124
2,451
3,209
27,392
24,225
8,576
7,171
0
1,642
0
0
0
134,766
CDC & DBN
0.33
0.57
0.22
0.38
0.00
0.19
0.43
0.05
0.25
0.51
0.29
0.20
0.37
1.25
0.30
0.37
0.16
Beaver, PA
62,555
58,409
69,274
56,220
100,709
80,150
78,882
69,689
127,035
29,441
54,327
58,352
4,903
74,656
67,342
44,232
54,399
1,090,577
Arden, NC
0.16
0.15
0.19
0.19
0.22
0.40
0.17
0.22
0.45
0.16
0.14
0.41
0.48
0.07
0.50
0.48
0.21
El Paso, TX
12,874
10,212
20,547
22,101
34,485
23,799
21,845
17,734
53,985
14,952
20,623
32,459
1
17,126
27,651
23,237
16,367
370,000
Beaver, PA
0.30
0.16
0.08
0.00
0.23
0.32
0.14
0.25
0.41
0.16
0.27
0.37
0.40
0.60
0.43
0.40
0.14
Raleigh, NC
8,983
15,270
16,436
14,385
25,024
20,044
18,302
10,370
10,172
5,937
18,507
14,081
305
7,128
6,588
11,156
9,945
212,631
El Paso, TX
0.78
0.95
0.41
0.65
0.20
0.20
0.65
0.22
0.07
0.80
0.56
0.00
0.24
2.28
0.13
0.24
0.37
Raleigh, NC
0.16
0.15
0.19
0.19
0.22
0.40
0.17
0.22
0.45
0.16
0.14
0.41
0.48
0.07
0.50
0.48
0.21
NC
22,069
4,788
10,854
4,740
13,569
8,725
10,545
8,437
11,065
1,850
5,657
2,346
8,636
6,276
4,415
8,820
4,017
136,808
NC
0.16
0.15
0.19
0.19
0.22
0.40
0.17
0.22
0.45
0.16
0.14
0.41
0.48
0.07
0.50
0.48
0.21
Total
1,099,299
343,831
979,440
439,555
908,229
839,167
946,982
1,053,736
1,278,292
321,643
470,402
376,270
397,354
431,006
383,337
335,065
416,608
11,020,215
Optimization Model
Optimization Model
Subject to
Demand satisfaction
Atlanta-SAT
Baltimore-SAT
Chicago-SAT
Cleveland-SAT
Dallas-SAT
Denver-SAT
Hartford-SAT
Houston-SAT
Los Angeles-SAT
New Jersey-SAT
Orlando-SAT
Phoenix-SAT
Portland-SVC
Raleigh-SAT
San francisco-SAT
Seattle-SAT
St Louis-SAT
Total Shipped
1,099,299
343,831
979,440
439,555
908,229
839,167
946,982
1,053,736
1,278,292
321,643
470,402
376,270
397,354
431,006
383,337
335,065
416,608
Capacity
Real Pounds
Historic capacity
Fayetteville, NC
2,462,457
3,000,000
Total demand
1,099,299
343,831
979,440
439,555
908,229
839,167
946,982
1,053,736
1,278,292
321,643
470,402
376,270
397,354
431,006
383,337
335,065
416,608
Sumter, SC
2,048,975
1,700,000
W34
1,099,299
3,000,000
W87
CDC & DBN
3,239,484
800,000
550,000
800,000
Arden, NC
0
150,000
Beaver, PA
1,000,000
1,000,000
El Paso, TX
370,000
370,000
Raleigh, NC
0
200,000
NC
0
150,000