A Study on the Storage Assignment of Distribution
Center -The case of Footwear and Apparel
Distribution Center
Advisor: Chi-Kong Huang, Ph.D.
Graduate: Siao-Rou Chiang
2013.Jun
Contents
Introduction
Literature Review
Research Method
Example Verification
Expect Conclusions
2
Introduction
Background and Motivation
Research Scope
Research Purposes
Research Process
3
Background And Motivation
• Distribution Center are the basic warehouse functions
–
–
–
–
Receiving
Storage
Order picking
Shipping
Warehouse Design
Overall
Structure
Sizing and
Dimensioning
Equipment
Selection
Operation
Strategy
Department
Layout
Performance
Evaluation
Warehouse Operation
Receiving
Storage
Order picking
Shipping
4
Background And Motivation
• Storage
 How Much Quantity ?
 How Frequently ?
 Improve efficiency
 Reduce the moving distance
 Where Should Stored ?
• Chan et al.(2010) indicates pickers have to travel long distance
and spend more time on picking
5%
10%
15%
20%
50%
Travel
Search
Pick
Setup
Other
5
Research Scope
 In this study, a case study is proposed
•
Case：LF Logistics of P brand supplier
•
SKUs Classify：Apparel、Footwear and Accessory
•
Characteristic：Multi-SKUs with low quantity, Periodicity, Fashion-like Products.
•
Historical Data：Inbound and Outbound Date during 2012 – Q3,Q4
Inbound,
Outbound
Data
SKUs
Characteristic
Existing
Warehouse
Environment
Research
6
Research Purposes
 A case study of an integrated Storage Assignment Plan
•
Assignment rule
 Make the suit classification and assignment of inventory
•
Storage policy
 Discuss the Inventory characteristics of the case study
•
Storage Layout
 Consider of a variety of different storage layouts to reduce the order picking
distance
7
Research Purposes
Assignment
rule
Research
Classbased
Storage
Storage
Layout
8
Research Process
Historical
Integrated
Data,
Storage
Find the
Analyze
Assignment
Question
SKUs
Plan
Literature
Construction
Reduce
Review
Methods
the
Order
Picking
Distance
9
Literature Review
Warehouse Operation
Storage Assignment Plan
A Case Study
10
Literature Review-Warehouse operation
Receiving
Storage
Order
Picking
Shipping
Storage
assignment
• Pan(2011) indicate the KEY to effective of a Storage Assignment
 Match the types of Warehouse Storage Assignment
 Different Stock Keeping Units (SKUs)
 Storage space
 Retrieval time
11
Literature Review-Storage Assignment Plan
Storage
Assignment
Assignment Rule
Storage Policy
Storage Layout
Closest open location
Dedicated Storage
Diagonal Layout
Turnover base location
Random Storage
Within-aisle Layout
Correlation
Class-based Storage
Across-aisle Layout
EIQ Analyze
Random within class
Perimeter Layout
Cube-Per-Order
Shared Storage
Complex-aisle Layout
12
Literature Review-Storage Assignment Plan
Type
Assignment
Rule
Assignment
Rule
Storage
Policy
Storage
Policy
Storage
Layout
Author Year
Yu-Shan
Chang
Chuang
et al.
Eldemir
et al.
Chan
et al.
Petersen
et al.
Result
Method
2002
Using EIQ analyze, design a storage
assignment with order picking for
distribution center a integration plan.
EIQ analysis indicators, apply a
way of picking and assign way.
2012
Construct item-associated model,
which can effectively improve order
picking efficiency.
Construct clustering and
assignment model, compare
with EIQ and Random storage
policy.
2004
To discuss operating cycle and
storage space, the simulation results,
class-based storage suitable for
short-cycle products
Compare dedicated storage,
random storage and classbased storage in the same
environment performance
2011
ABC class-based storage
assignment policy can improve the
performance of picking in total order
retrieval time.
Using EIQ analyze and COI,
AS/RS storage space.
1999
Route policy and Storage Strategies
order picking efficiency, storage
layout of the four categories
classified storage
Volume class-based storage
Proposed three layout of geometry
class-based storage, the computing
13
Literature Review- A Case Study
• P-Brand Supplier
• Operation：Inbound、Storage、Order Picking、Return
 By Carton- Pallet Rack (Two Pallets Type)
 By Piece - Light Duty Rack
Inbound
Pallet
Rack
Outbound
Light
Duty
Rack
Outbound
14
Research Method
Problem Definition
Research Method Structure
Storage Assignment Plan
15
Research Method-Problem Definition
• Storage management operation
→ Empirical rule
 New SKUs
 Return
Empirical rule
Empty storage spaces
Operator
Supervisor
Random Storage
16
Research Method-Problem Definition
Layout
I/O point
known,
lower left
corner
SKUs
Data
Distance
Total SKUs：
5,872
Total Quantity：
Inbound
During 2012
Single order
picking
Outbound
At 2012-Q4
Picking
from one
depot
377,223
Existing
storage
environment
6000 light
duty ranks
Apparel
3,246
Footwear
1,646
Nearest
Neighbor
Algorithm
Accessories
980
17
Research Method-Research Method Structure
•
Generalizing SKUs
 Hierarchies of SKUs be used for arranging SKUs
 Association rule mining is conducted among items at the lowest level
P brand
Apparel
Footwear
Women
Kinds
Men
Basic
Sports
Motor sport
Lifestyle
Accessories
Golf
18
Research Method-Research Method Structure
Start
Environmental
parameters
Historical
data of SKUs
The first phase
Correlation
Inventory ratio
EIQ Analyze
With ABC class-based Storage Policy
1
Assignment Rule
2
Class-based
storage/
Storage layout
The second phase
Diagonal
Within-aisle
Across-aisle
Complex-aisle
R
Storage Assignment
Program
Minim ize Dt
t 1
t ： location；Dt：the distance from location to I/O point
19
Research Method-Storage Assignment Plan
• Assignment Rule – Correlation
 The order-item association rule, item-index between items i and j as follows.
Sij 
p(i  j )
p(i)  p( j )
P(i∩j) is the number of orders containing items i and j
 Items are assigned into groups
N K
Maximize
 SabXab
High Correlation are in the same Group
a 1 b1
N
Subject to：
 xab  1
a, b  1,2,...,N
Item can be clustered in one group only
b1
N
Y
b 1
b
K
X ab 0,1 a, b  0, 1, ...,N
Yb 0,1 a, b  0, 1, ...,N
Limits that the number of clusters
Binary decision variables,
Xab, item a association to cluster b,
Yb point of cluster,
There was 1, and 0 otherwise
20
Research Method-Storage Assignment Plan
• Assignment Rule - Inventory Ratio
 Cycle of product ：one season
•
With ABC class
•
Differences between the seasons
 Seasonal
 Off-season
Select existing SKUs
Inbound of quantity,
history data
Existing SKUs,
Inventory data
The calculated SKUs Inventory Ratio,
(Existing inventory / Inbound of quantity)
Type：A
More than 50%
Type：B
50%-10%
Type：C
Less than 10%
constructed classification assign rule
21
Research Method-Storage Assignment Plan
• Assignment Rule - EIQ Analyze
•
•
Consider both the Quantity and Frequency
Historical order data
With ABC [Chan, 2011]
 A：60% of the total index of SKUs
 B：30% of the total index of SKUs
 C：10% of the total index of SKUs
Construct EIQ analyze
Item Quantity(IQ)
Analyze
Item Frequency
(IK) Analyze
IQ*IK Analyze
Class A SKUs
Class B SKUs
Class C SKUs
22
Research Method-Storage Assignment Plan
• With ABC Class-based storage / Storage layout
Diagonal
Within-aisle
Across-aisle
Complex-aisle
23
Example Verification
Example Description
Storage Assignment Plan Program 2
Storage Assignment Plan Program 6
Storage Assignment Plan Program 10
Analysis and Comparison
24
Example Verification-Description
•
Simplify Data and Layout in case
 Single order picking
 Nearest Neighbor Algorithm
•
Verify the feasibility
of the programs
Storage Assignment Plan program
 The First Phase： 3 of Assignment Rule
 The Second Phase： 4 of Storage layout
Assignment
Rule
Correlation
Inventory Ratio
EIQ Analyze
Diagonal Layout
Program1
Program5
Program9
Within-aisle Layout
Program2
Program6
Program10
Across-aisle Layout
Program3
Program7
Program11
Complex-aisle Layout
program4
Program8
Program12
Storage layout
25
Example Verification-Description
Y
12 orders in Oct.
(0,5)
(1,5)
(2,5)
(0,4)
(1,4)
(2,4)
(0,3)
(1,3)
(2,3)
Entry
(0,2)
(1,2)
(2,2)
1
0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0
3
(0,1)
(1,1)
(2,1)
2
0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0
3
3
0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1
2
4
1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0
3
5
1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0
3
6
1 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0
4
7
1 1 1 1 0 0 0 1 0 1 1 1 0 0 0 0 0
8
8
1 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0
4
9
0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0
4
I/O
(1,0)
Item
(2,0)
X
Based on Rectilinear Distance
5
6
7
A B C D E F G H I J K L M N O P Q Total
4
5
6
3
4
5
10
0 0 0 0 0 1 1 1 0 0 0 0 1 0 1 1 0
6
2
3
4
11
1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0
3
1
2
3
12
0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0
2
I/O
1
2
Total
6 1 2 5 3 7 2 2 2 1 1 1 2 3 5 1 1
45
26
Example Verification-Program 2
• Program 2
 Correlation * Within-aisle Layout
Item A B C D E
F G H
A
-
B
0.08
C
0.08 0.08
D
0.33 0.08 0.08
E
0.17 0
0
0.17
F
0.25 0
0
0.33 0.17
0
0.08 0.08 0.17
G
0
0.08 0.08 0.33 0.17 0.25 0
-
0
0.08 0.08 0
-
J
K L M N O P Q
0.08 0.08 0.08 0.08 0.08 0
0.08 0.08 0.08 0
0
0
0
0.08
0.17 0.33 0.08 0.08 0
0.08 0.08 0.08 0
0
0.08 0
0
0
0.08 0
0
O
N
I
A
D
G
I/O
F
E
-
0.17 0.08 0
-
0
0
0
0.17 0.08 0.08 0
0
0
0.08 0.08 0.17 0.08 0
0
0
0.08 0
0.08 0.08 0
0.08 0.08 0.08 0.08 0
0.08 0.08 0
-
0
0.08 0
0
0
J
0.08 0.08 0.08 0.08 0
0
0
0.08 0
-
K
0.08 0.08 0.08 0.08 0
0
0
0.08 0
0.08
L
0.08 0.08 0.08 0.08 0
0
0
0.08 0 0.08 0.08
0
0
0
0
0
0.08 0.08 0.08 0
N
0.08 0
0
0
0
0.08 0
O
0.17 0
0
0
P
0.08 0
-
0
H
0
0
Q
M
0
0.08 0
0
L
0
0.08 0
0
B
0
I
0
C
0
0
P
Q
0
-
0
K
0.08 0.08 0.08 0
0.08 0.08
M
J
0.08 0
0.08 0.08 0.08 0.08 0
0
0
0
H
0
0.08 0.17 0
0
0.08 0
-
I
0
0
0.08 0
0
0
0
0
0.08 0.08 0
-
0.08 0
-
0
0.08 0
0
0
0
0
0
0
0
0
0
0
-
0.08 0
0
0
0.08
0
0
0
0.17 0.17
0
0
0
0.08 0
0
0
0
0
0
0
0
0
0
0
0
0.08 0.08 0.08 0
0
0
0
0.08 0.08 0.17 0.08 0.08 0
0
0
0
0.08 0.17 0.08 0
-
0
0.17 0
-
0
C
B
A
The second
phase
The
first
phase
Program 2
0.08 0
0.08
-
0
0
0
-
27
Example Verification- Program 6
• Program 6
 Inventory Ratio * Within-aisle Layout
Item
A
Inbound
Inventory
Ratio*
Sequence
480
478
B
C
242
11
D
65
E
935
15
1,515
146
99.6% 4.5% 2.3% 15.6%
2
12
16
F
G
390
645
79
388
5.2%
99.5%
11
3
7
H
611
42
604
L
C
I
B
K
Q
N
O
E
D
M
G
P
F
J
I/O
A
H
I
652
14
6.5% 98.8% 2.1%
10
4
17
C
B
A
Item
J
K
L
M
N
O
P
Q
Inbound
857
422
313
738
1498
720
373
449
Inventory
845
15
1
723
14
87
372
13
Ratio*
98.6%
3.5%
3.2%
98.0%
Sequence
5
13
14
6
6.9% 12. 8% 99.7%
9
8
1
2.9%
The second
phase
The
first
phase
Program 6
15
28
Example Verification- Program 10
• Program 10
 EIQ Analyze * Within-aisle Layout
IQ(%)
IK(%)
IQ*IK(%)
(2)
(1)*(2)*10
6
13.3%
3.67%
1
736
23.51%
D
535
E
Sequence
P
K
L
33.7%
1
I
Q
J
2.2%
0.8%
7
2
4.4%
10.5%
5
G
M
H
17.09%
5
11.1%
19.%
2
112
3.58%
3
6.7%
2.4%
6
E
B
N
F
215
6.87%
7
15.6%
10.7%
4
D
F
C
G
54
1.73%
2
4.4%
0.8%
8
H
31
0.99%
2
4.4%
0.4%
11
I/O
A
O
I
28
0.89%
2
4.4%
0.4%
12
J
24
0.77%
1
2.2%
0.2%
15
K
21
0.67%
1
2.2%
0.1%
16
L
10
0.32%
1
2.2%
0.1%
17
M
38
1.21%
2
4.4%
0.5%
10
N
28
0.89%
3
6.7%
0.6%
9
O
314
10.03%
5
11.1%
11.1%
3
P
35
1.12%
1
2.2%
0.2%
14
Q
42
1.34%
1
2.2%
0.3%
13
Total
3,130
100%
45
100%
100%
Item
IQ
A
792
25.30%
B
115
C
(1)
IK
C
B
A
The second
phase
The
first
phase
Program 10
29
Example Verification-Analysis and Comparison
•
Existing state as Random Storage
 Random vs. Program 2 vs. Program 6 vs. Program 10
 With 12 orders, 17 items
Random
Program 2
Program 6
Program 10
Distance
142
98
126
114
Improve
0
44
16
28
0%
31%
11%
20%
Diff(%)
With Random
Diff(%) ：(Program-Random)/(Random)
The program is feasible to reduce
picking distance
30
Expect Conclusions
•
•
•
Use of all of the existing warehouse SKUs
Data range of 2012-Q4 to 2013-Q2
Using simulation of method
Writing and integration
Data testing and analysis
Data collection, coding
1月
2月
3月
4月
5月
6月
31
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32