BALANCING PRODUCT FLOW AND …ctl.mit.edu/sites/ctl.mit.edu/files/theses/Jeffrey...BALANCING PRODUCT...
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BALANCING PRODUCT FLOW AND SYNCHRONIZING TRANSPORTATION Jeff Bullock & Priya Andleigh Graduate Students, Supply Chain Management Massachusetts Institute of Technology
Transcript of BALANCING PRODUCT FLOW AND …ctl.mit.edu/sites/ctl.mit.edu/files/theses/Jeffrey...BALANCING PRODUCT...
BALANCING PRODUCT FLOW AND SYNCHRONIZING TRANSPORTATION
Jeff Bullock & Priya AndleighGraduate Students, Supply Chain Management Massachusetts Institute of Technology
AGENDA
Project Overview Methodology Model
Output Next Steps
PROJECT OBJECTIVE Plant Warehouse
PROJECT OBJECTIVE
How much?Which SKUs?
On-Demand
Fixed Volume $ per load
Plant Warehouse
STEADY FLOW TRADE-OFFS
5 6 7 8 9 10 11 12 13 14 15
Cos
ts/S
avin
gs ($
)
Steady Flow (# of pallets/week)
Transportation Savings
STEADY FLOW TRADE-OFFS
5 6 7 8 9 10 11 12 13 14 15
Cos
ts/S
avin
gs ($
)
Steady Flow (# of pallets/week)
Transportation Savings
Cross-Dock Savings
STEADY FLOW TRADE-OFFS
5 6 7 8 9 10 11 12 13 14 15
Cos
ts/S
avin
gs ($
)
Steady Flow (# of pallets/week)
Transportation Savings
Cross-Dock Savings
Excess Inventory Cost
5 6 7 8 9 10 11 12 13 14 15
Cos
ts/S
avin
gs ($
)
Steady Flow (# of pallets/week)
Transportation Savings
Cross-Dock Savings
Excess Inventory Cost
Total Savings
STEADY FLOW TRADE-OFFS
Maximum Savings
AGENDA
Project Overview Methodology Model
Output Next Steps
Yes
H weeks
METHODOLOGY
HistoricalData
ForecastData
ForecastCheck
DescriptiveStatistics
SteadyFlow
Eligible?
STOP
No
% Forecast>0 > X%%weeksshipped>Y%COV<Z%
ALL weeks
F weeks
1
2 3
4
5
6
CreateOptimizedSteadyFlow
LevelSKUs • List• Quantity
SteadyFlow
7 9
Maximize{Transportationsavings+Cross-docksavings–
ExcessInvcost}
FixedTruck/IMCapacity
8
STEADY FLOW OPTIMIZATION
OptimizedSteadyFlow
Level= #ofpalletsforwhichtheTotalSavingsaremaximized
Total Savings = Transportation Savings + Cross-dock
Savings - Excess Inventory Cost
For each SKU
Transportation Savings =
# of pallets of Steady
Flow
% of truck that a pallet represents *
Transportation Savings per truck
STEADY FLOW OPTIMIZATION
*𝛴All periods
Pallet TruckPallet
$Truck
𝑇𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡𝑎𝑡𝑖𝑜𝑛𝑆𝑎𝑣𝑖𝑛𝑔𝑠 = 0(s ∗ j ∗ p)7
89:
Cross-dock Savings TheorySTEADY FLOW OPTIMIZATION
Cross-dock Savings TheorySTEADY FLOW OPTIMIZATION
MIN (Steady Flow, Demand)
= # of pallets that can be cross-docked *
Cross-dock savings per pallet
Cross-dock Savings
MIN (Steady Flow, Demand)
Cross-dock eligibility
𝐶𝑟𝑜𝑠𝑠𝑑𝑜𝑐𝑘𝑆𝑎𝑣𝑖𝑛𝑔𝑠 = 0𝑀𝑖𝑛 𝑠, 𝑑8 7
89:
∗ 𝑐A ∗ 𝑐B
STEADY FLOW OPTIMIZATION
𝛴All periods
*
Pallet $Pallet
%
Excess Inventory TheorySTEADY FLOW OPTIMIZATION
And so forth
% of truck that a pallet represents
Excess Inventory
Cost=
Excess pallets from current
period
Excess pallets from previous
period+ *
Inventory holding cost per truck per week
Pallets left at the end of the period
Risk factorEnd of period
penalty% of truck that a pallet represents
𝐸𝑥𝑐𝑒𝑠𝑠𝐼𝑛𝑣𝑒𝑛𝑡𝑜𝑟𝑦𝐶𝑜𝑠𝑡 = 0Max((𝑒8K: + 𝑠 − 𝑑8), 0) ∗ 𝑗 ∗ ℎ ∗ 𝑣7
89:
+ Max( 𝑒7K: + 𝑠 −𝑑7 , 0) ∗ 𝑗 ∗ 𝑣 ∗ 𝑟
STEADY FLOW OPTIMIZATION
*
***+
𝛴All periods
Inventory value per truck per
week*
Pallet TruckPallet
%
Pallet $Truck
Pallet TruckPallet
$Truck
%
𝑇𝑜𝑡𝑎𝑙𝑆𝑎𝑣𝑖𝑛𝑔𝑠 = 𝑇𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡𝑎𝑡𝑖𝑜𝑛𝑆𝑎𝑣𝑖𝑛𝑔𝑠 + 𝐶𝑟𝑜𝑠𝑠𝑑𝑜𝑐𝑘𝑆𝑎𝑣𝑖𝑛𝑔𝑠 − 𝐸𝑥𝑐𝑒𝑠𝑠𝐼𝑛𝑣𝑒𝑛𝑡𝑜𝑟𝑦𝐶𝑜𝑠𝑡
𝑶𝒃𝒋𝒆𝒄𝒕𝒊𝒗𝒆𝑭𝒖𝒏𝒄𝒕𝒊𝒐𝒏:𝑴𝑨𝑿𝑰𝑴𝑰𝒁𝑬𝑻𝒐𝒕𝒂𝒍𝑺𝒂𝒗𝒊𝒏𝒈𝒔
𝑫𝒆𝒄𝒊𝒔𝒊𝒐𝒏𝑽𝒂𝒓𝒊𝒂𝒃𝒍𝒆: #𝒐𝒇𝒑𝒂𝒍𝒍𝒆𝒕𝒔𝒐𝒏𝒔𝒕𝒆𝒂𝒅𝒚𝒇𝒍𝒐𝒘(𝒔)
𝑇𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡𝑎𝑡𝑖𝑜𝑛𝑆𝑎𝑣𝑖𝑛𝑔𝑠 = 0(s ∗ j ∗ p)7
89:
𝐶𝑟𝑜𝑠𝑠𝑑𝑜𝑐𝑘𝑆𝑎𝑣𝑖𝑛𝑔𝑠 = 0𝑀𝑖𝑛 𝑠, 𝑑8 7
89:
∗ 𝑐A ∗ 𝑐B
𝐸𝑥𝑐𝑒𝑠𝑠𝐼𝑛𝑣𝑒𝑛𝑡𝑜𝑟𝑦𝐶𝑜𝑠𝑡 = 0Max((𝑒8K: + 𝑠 − 𝑑8), 0) ∗ 𝑗 ∗ ℎ ∗ 𝑣7
89:
+ Max( 𝑒7K: + 𝑠 −𝑑7 , 0) ∗ 𝑗 ∗ 𝑣 ∗ 𝑟
STEADY FLOW OPTIMIZATION
5 6 7 8 9 10 11 12 13 14 15
Cos
ts/S
avin
gs ($
)
Steady Flow (# of pallets/week)
Transportation Savings
Cross-Dock Savings
Excess Inventory Cost
Total Savings
STEADY FLOW OPTIMIZATION
Maximum Savings
AGENDA
Project Overview Methodology Model
Output Next Steps
SKU EXAMPLE 1DemandCharacteristics
Minimum(pallets/week) 28 %weeksshipped 100%
Mean(pallets/week) 37.7 COV 0.13
StdDev(pallets/week) 4.80ModerateVolume,StableSKU
DemandCharacteristicsMinimum(pallets/week) 28 %weeksshipped 100%
Mean(pallets/week) 37.7 COV 0.13
StdDev(pallets/week) 4.80ModerateVolume,StableSKU
SKU EXAMPLE 1
SKU EXAMPLE 2DemandCharacteristics
Minimum(pallets/week) 9 %weeksshipped 100%Mean(pallets/week) 27.9 COV 0.60Std Dev(pallets/week) 16.7
HighCOVSKU
SKU EXAMPLE 2DemandCharacteristics
Minimum(pallets/week) 9 %weeksshipped 100%Mean(pallets/week) 27.9 COV 0.60Std Dev(pallets/week) 16.7
HighCOVSKU
DemandCharacteristicsMinimum(pallets/week) 1 %weeksshipped 87%Mean(pallets/week) 2.3 COV 0.52StdDev(pallets/week) 1.20
LowVolume,NotShippedEveryWeek
SKU EXAMPLE 3
DemandCharacteristicsMinimum(pallets/week) 1 %weeksshipped 87%Mean(pallets/week) 2.3 COV 0.52StdDev(pallets/week) 1.20
LowVolume,NotShippedEveryWeek
SKU EXAMPLE 3
Yes
H weeks
FINAL OUTPUT
HistoricalData
ForecastData
ForecastCheck
DescriptiveStatistics
SteadyFlow
Eligible?
STOP
No
% Forecast>0 > X%%weeksshipped>Y%COV<Z%
ALL weeks
F weeks
1
2 3
4
5
6
CreateOptimizedSteadyFlow
Level
SteadyFlow
7 9
Maximize{Transportationsavings+Cross-docksavings–
ExcessInvcost}
FixedTruck/IMCapacity
8
SKUs • List• Quantity
AGENDA
Project Overview Methodology Model
Output Next Steps
NEXT STEPS
q Data Aggregation
q Other Savings/Cost Considerations
q SKU Selection
q Parameter Tuning
q Multiple Lane Analysis
q Demand Segmentation
q Update Frequency
q Contract Innovation
q Distribution Resource Planning (DRP)
Model Enhancements
Analysis Processes
IMPLICATIONS
Steady
Flow
Transportation
Savings
Replenishment
Cycle Time
Reduction
Bullwhip
Dampening
Cross-dock
Productivity
Safety
Stock
Reduction
Contract
Innovation
THANK YOU!
