This document discusses optimizing inbound logistics costs for an automobile manufacturer through a case study at TAFE. It presents the existing decentralized warehouse system and associated high costs. The objectives are to introduce a centralized warehouse, optimize carrier selection using packaging heuristics, and implement barcode technology to minimize errors. The methodology involves selecting an optimal warehouse location and layout, estimating costs for the new system, and developing a transportation model from warehouse to plant. Introducing a centralized warehouse is expected to optimize total inbound logistics costs.
Smart logistics solutions are a great fit for the building materials industry
Tafe - New Centralized Warehouse
1. OPTIMIZATION OF CARRIER MODE INBOUND LOGISTICS IN AN
AUTOMOBILE INDUSTRY-A CASE STUDYAT TAFE
Guided By
Dr. PL.K Palaniappan
Associate Professor
Dept of Mech Engg
Thiagarajar College of Engg
Madurai
By
S.Anif Antony Amalan(13L02)
ME Industrial Engg
Dept of Mech Engg
Thiagarajar College of Engg
Madurai
8 February 2016
OPTIMIZATION OF CARRIER MODE INBOUND LOGISTICS IN AN AUTOMOBILE INDUSTRIES - A CASE
STUDY AT TAFE
1
L41 – PROJECT PHASE - II
Guided By
Mr. Rajagopal
Senior Engineer
Internal Logistics Dept
TAFE
Madurai
2. CONTENT
About TAFE
Logistics
Logistics Process
Literature Review
Problem Descriptions
Objective
Methodology flow chart
Model Formulation
Discussion for Proposed Work
Conclusion
Reference
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3. ABOUT -TAFE
Third Largest tractor manufacture in the world
Second Largest in India by volumes
Sale of approximately 1,50,000 tractors annually
Certified ISO 9001 and ISO 14001
Part of Amalgamation Group
CURRENT OPERATION CAPACITY AT
MADURAI PLANT
Current operations 200 Tractors per day (2 Shift)
Capacity available 230 Tractors per Day (2 Shift)
Assembly 2 Shift
Paint Shop 2 Shift
Machine Shop 3 Shift
Production 4 Mins / Tractors
Product Range 25 HP – 100 HP
National 17 models / 45 Variants
Export 55 Models / 275 Variants
Components 9932
Persons 1200
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4. 8 February 2016 4
The process of planning, implementing, and controlling the effective and
efficient flow of goods and services from the point of origin to the point of
consumption.
LOGISTICS
INTERNAL LOGISTICS
It manages, arranges, plans and delivers the materials to the assembly station.
OPTIMIZATION OF CARRIER MODE INBOUND LOGISTICS IN AN AUTOMOBILE INDUSTRIES - A CASE
STUDY AT TAFE
5. Literature Review
Journal Title Authors Content Tool Used
International
Journal of
Production
Economics,
Vol 103,
2006,
pp826–840.
Carrier-mode
logistics
optimization of
inbound supply
chains for
electronics
manufacturing
Jeffery K.
Cochran, Balaji
Ramanujam
• Using third party logistics (3PL) provider transportation,
storage facilities, and services is becoming standard practice.
• Choosing among 3PL providers and carrier mode options is a
complex task and the choice has significant impact on the
bottom line cost of the end product.
• Integer Programming
• LINGO
• BD Heuristic
Journal Of
Industrial
And
Management
Optimization
Volume 3,
Number 1,
Logistics
network design
with supplier
Consolidation
hubs and
multiple
shipment
options
Michelle F,
Cheong rohit
bhatnagar and
stephen . Graves
• Consolidate the transportation flow, so as to get the best
overall logistics performance.
• Network design problem to implement this tactic, namely
deciding the number, location and operation of consolidation
hubs so as to minimize the total logistics costs for the
network.
• Consolidated Hub
for Supplier to 3PL
• Linear
Programming
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6. PUBLICATION AUTHOR TITLE DESCRIPTION KEY TOOLS
European Journal
of Operational
Research
Hu Qin, Zizhen
Zhang , Zhuxuan
Qi , Andrew Lim
The freight
consolidation and
containerization
problem
An express company, such as UPS and FedEx,
unloads the shipments from the containers at the
destination
ports and distributes them to their corresponding
stores or retailers by parcel delivery.
The objective is to find an allocation that
minimizes the total container transportation and
parcel delivery
costs.
• Packing
• Freight consolidation
• Containerization
• Third-party logistics
CIRP Journal of
Manufacturing
Science and
Technology 4,
2011, pp 252–257
M. Florian a,b, J.
Kemper c, W.
Sihn a,b, B.
Hellingrath
Concept of transport-
oriented scheduling for
reduction of inbound
logistics traffic in the
automotive industries
high amount of transport traffic in inbound
logistics, small changes lead to substantial
savings in CO2 emissions
• Logistics
• Planning
• Scheduling
• Production
Proceedings of the
World Congress
on Engineering
2013 Vol I,
WCE 2013,
London.
Daniela L.
Antunes,
Sérgio D. Sousa
Using Project Six
Sigma and Lean
Concepts in Internal
Logistics
To reduce non added value activities and improve
intrinsic processes in the supply chain of an
organization
Six Sigma methodology in combination with Lean
concepts presents a high potential to be applied in
improving internal logistics (IL) processes.
• Continuous
Improvement
• Lean Logistics
• Quality Tools
• Six Sigma
• Supply Chain
Management.
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7. 8 February 2016
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o Integrated warehouse site selection and space determination minimizes the outbound
logistics cost.
o Automated layout design program (ALDEP) are widely used for facility layout problem.
o Choice of Packaging pallets for transport will lead to cost optimization.
o Centralized warehouse for inbound logistics is not in practice in Indian Automobile
Manufacturing Sector.
Literature Summary
8. Raw material
procurement
Process
Suppliers Packaging Labeling
Loading the material to
truck at supplier end
Truck moved to
warehouse
Materials unloaded from
the truck at W/H
Materials are stored by
Part Number wise
Order received by 3PL
and Suppliers
Invoice are prepared Materials are loaded to
truck for the order qty
Truck moved to factory
Unloading the materials
from the truck
Truck Moved to Unloading
Point
Verification of Part
Numbers and Quantity
Binning
Materials Moved to
Storage Point
3PL
Activities
Suppliers Logistics Activities
Factory
Logistics
Activities
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9. PROBLEMS IN INBOUND LOGISTICS
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10. 75%
25%
Inbound Logistic Cost
Transportation
Warehouse
operation
3PL's
Total Logistic Cost (Rs) Materials from
Warehouse
(in tons)
Total Cost Spent for
Warehouse Annually
(in lakhs)Transports Warehouse Total
1 1.31 0.43 1.75 10500 45.94
2 1.54 0.51 2.06 9600 49.44
3 1.42 0.47 1.9 8400 39.90
4 1.68 0.56 2.25 10800 60.75
5 1.53 0.51 2.05 9000 46.12
Total 7.50 2.50 10.01 48300 242.15
TOTAL INBOUND LOGISTIC COST
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45%
25%
10%
20%
Mode of Raw Material Receiving
Percentage
Milk Run
Line Haul
Delivery
Full Load Truck
Supliers
Transport
11. OBJECTIVE
To optimize inbound logistic cost by introducing
centralized warehouse.
To select optimum carrier for an order quantity using
packaging heuristics.
To develop Bar Code Technology in centralized
warehouse to minimize human errors.
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12. Existing Decentralized Warehouse of
inbound logistics
Proposed Centralized Warehouse of
inbound logistics
2
1
3
4
n
Suppliers Centralized
Warehouse
Manufacturing
Plant
P
n
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2
1
3
4
Suppliers 3PL
Warehouses
Manufacturing
Plant
1
P
n
m
2
13. METHODOLOGY
FLOW CHART
Literature Survey
Optimum Warehouse location
Rectilinear
Location Model
Gravity Location
Model
Minimax Location
Model
Optimum Warehouse layout Model
CORELAP
ALDEP
Cost Estimation for New
Centralized Warehouse
Transportation Model for
Warehouse to Plant
Develop Packing
Heuristics
Total Inbound logistic warehouse cost
be optimized
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14. WAREHOUSE LOCATION
1. Rectilinear location Method
2. Minimax Location Method
3. Center of Gravity Location Method
The optimum location warehouse is consider by rectilinear distance method
of (X*, Y*) = (10.13*, 77.92*) as a distance of 2 kilometer from the plant.
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15. Input Data of Automated Layout Planning Design Program (ALDEP)
S.NO NOTATIONS DEPARTMENTS AREA
(sq ft)
No of
UNITS
1 A Receiving end 4000 8
2 B Shipping end 3000 6
3 C Storage area 10000 20
4 D Office 1000 2
5 E Material Handling Equipment (MHE) Parking 500 1
6 F Truck waiting area 6000 12
7 B Common Place 500 1
TOTAL 25000 50
NOTATIONS RATING CLOSSNESS
VALUE
A Absolutely necessary 64
E Especially important 16
I Important 4
O Ordinary closeness OK 1
U Unimportant 0
X Not desirable -1024
FROM
1 -
2 U -
3 A A -
4 I I E -
5 O O O U -
6 E E U O U -
7 U O O I U O -
TO 1 2 3 4 5 6 7
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16. TRUCK
WAITING
AREA
RECEIVING END
STORAGE AREA
SHIPPING END
OFFICE
COMMON
MHE
PARKING
RESULTS OF ALDEP
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Iterations Closseness Values Score
Double Sweep
Score
1 A+A+U+E+U+O+O+I+O+I 155 310
2 A+A+O+E+U+O+U+O+I+O 152 304
3 A+E+E+E+U+O+I+I+U+O 122 244
4 E+A+U+E+U+E+O+O+O 115 230
5 U+O+E+A+U+E+E+O 114 228
6 E+U+A+A+E+O+I+O+U+O 167 334
7 I+O+E+A+U+E+E+O 118 236
18. Labour
unloading Point(400*8*12*25) 960000
Loading Point(400*8*12*25) 960000
Storage (350*6*12*25) 630000
MHE Driver(350*6*12*25) 630000
Security(400*4*365) 584000
Building 200000
Racks 50000
Wooden Pallets 10000
Steel Pallet 50000
MHE 144000
Computer & Softwares 20000
Xerox machine 20000
Bar code System 10000
Electricity(10000*6) 60000
Taxes & Insurance 1907344
Chief Manager/Executive
(2*25000) 50000
Manager/ Supervisary
Salary(5*20000) 125000
Total Warehouse Cost 6410344
Total Material Handled Annually 48300000
Costs involved in transportation
Driver salary(300*12*25*12) 1080000
wages(50*12*25*12) 180000
Cleaner(50*12*25*12) 180000
truck depreciation (10%)(12*1000000) 1200000
insurance & tax(10%)(12*1000000) 500000
Fuel(25*12*4*12*6.875*5) 495000
Oil(10*250*12*4) 120000
Tyre(12*2*10000) 240000
Repair(12*10000) 120000
Maintenance(12*10000) 120000
Total 4235000
Cost Model
Warehouse
( in Lakhs)
Transportation
( in Lakhs)
Total Cost
( in Lakhs)
Total Tons
Handled
Proposed New Centralized
Warehouse
64.1 42.35 106.45 48300
New Proposed Centralized warehouse Recurring Cost
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19. Cost Model
Warehouse
( in Lakhs)
Transportation
( in Lakhs)
Total Cost
( in Lakhs)
Profit
( in Lakhs)
Total Tons
Handled
Existing Decentralized
Warehouse
141.8 100.4 242.15
135.7 48300
Proposed New
Centralized Warehouse
64.1 42.35 106.45
COST COMPARISON
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20. Sq.ft Cent
Cost
( in Lakhs)
100 130
25000 57.392103 74.6
Length
(m)
Breath
(m)
Height
(m)
Volume
(meter cube)
Cost
Total Cost
( in Lakhs)
Pallets
Heavy Rack Area 2 0.6 1.8 2.16 10000
For Single Rack 23.261 0.8 3.6 66.99168 310146.6667
For 3 Rack 69.783 2.4 10.8 1808.77536 8373960 83.74 216
Light Rack Area 2 0.6 1.8 2.16 5000
For Single Rack 23.261 0.8 3.6 66.99168 155073.3333
For 5 Rack 116.305 4 18 8373.96 19384166.67 193.84 360
Total cost for Rack building 277.58 576
Initial Investment Requirement for Centralized warehouse Cost
Purchasing / Construction Cost in Rs
Land (130000per Cent*57.392103) 7460973
Building(1400per Sq.ft*19000) 26600000
Racks (Volume * Volume per Rate) 27758127
Water / Electricity 1000000
Wooden Pallets (500*1000) 500000
Steel Pallet (5000*200) 1000000
MHE (6*200000) 1200000
Transport (12*8L) 9600000
Computer & Softwares(50000*4) 200000
Bar code System
Printer (18500) 18500
Scanner in MHE (7000*6) 42000
Scanner in Storage Labour(2000*9) 18000
Total 75397600
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21. Return on Investment for Centralized warehouse Cost Model
Years
Existing
Warehouse Cost
( in Lakhs)
New centralized
warehouse
( in Lakhs)
Profit amount
( in Lakhs)
Total Investment
( in Lakhs)
Return on
Investment
1 242.15 106.45 135.7 753.19 5.6 years
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22. Order received for
centralized warehouse
Determine the order
quantity and volume for
the material
Mtrl vol
< cheap
box
Mtrl vol
< pallets
Mtrl vol
< truck
Determine the
Number of
Pallets needed
Determine the
Number of
cheap box
needed
Determine the
Optimum Truck
No
YesYesYes
No
Packaging Heuristics
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23. INPUTAND OUTPUT
OF THE C- PROGRAM
Length of ordered material in meter.
Breath of ordered material in meter.
Height of the ordered material in meter.
Quantity of the material needed in numbers.
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Choosing right cheap box, right pallets and right truck.
Number of Cheap Boxes needed for ordered quantity.
Number of Pallets needed for ordered quantity.
Choosing right truck for ordered material.
INPUTS OF THE C- PROGRAM
OUTPUTS OF THE C- PROGRAM
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25. Linear barcodes (2D codes) are usually used in logistics and industry for serial
numbers, product IDs, etc.
130- Supplier code, 99- Transporter Code,
25-Material Code, 4567-Part number
Barcode Components
Barcode Scanners
Barcode-based Mobile Computers
Wireless Scanners
Pen/Key Based Terminals
Vehicle Mount Computers
Barcode Printers
Barcode Labels & Ribbons
Barcode Data Collection Software
Bar Code Technology
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26. 8 February 2016
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Sl No Report Dec Jan Feb Grand Total
1 Excess of materials 109 119 112 340
2 Shortage of materials 91 118 115 324
3 Wrong Supply of materials 92 114 78 284
4 Damaged materials 15 13 15 43
5 Materials in Wet Condition 1 28 6 35
6 Rusted materials 6 22 2 30
Grand Total 314 414 328 1056
Problems Due to Third Party Logistics Warehouses
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28. Automated Identification System (Two Dimensional Long Range Imager)
Application scenario: Long
range scanning in sunlight
Use case: Outdoor inventory
Application scenario: Long
range Omni-directional
scanning from a forklift
Use case: Inventory/forklift
application
Application scenario: Short
range 1D and 2D scanning,
long range 1D scanning
Use case:
Picking/serialization
Application scenario: Long
range scanning, limited space
for bar codes
Use case: Picking/forklift
application
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29. In this work, an attempt has been made to introduce centralized warehouse model in TAFE, to minimize inbound
logistics cost. The total inbound logistic cost is optimized by introducing centralized warehouse and choosing optimum
location and layout for the proposed centralized warehouse. Bar Code Technology is developed to minimize the human
error in the centralized warehouse. Transportation packing heuristics is developed for choosing right truck, right pallet
and right cheap box for the right quantity of material in order to optimize transportation cost from warehouse to
manufacturing plant. It is found that the recurring cost of the centralized warehouse model is less than the existing
decentralized warehouse model. The limitations of centralized warehouse is huge investment and the payback period
for the initial investment is found to be 5 years 6 months which is viable.
PROJECT CONCULSION
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30. • Afshin Mehrsai , Hamid-RezaKarimi , Klaus-DieterThoben , BerndScholz-Reiter “Application of learning pallets for real-
time scheduling by the use of radial basis function network”, Neurocomputing, 2013, Vol 101, pp 82–93.
• Aicha Aguezzoul., “The Third Party Logistics Selection: A Review of Literature”, International Logistics and Supply Chain
Congress., Nov 2007, pp8-9.
• Bhanuteja Sainathuni, Pratik J. Parikh, Xinhui Zhang, Nan Kong., “warehouse-inventory-transportation problem for supply
chains”., European Journal of Operational Research., vol 237., pp690–700., 2014.
• Cheong Lee Fong, Michelle, “New Models in Logistics Network Design and Implications for 3PL Companies”., Thesis,
Nanyang Technological University, 2005.
• Hu Qin , Zizhen Zhang , Zhuxuan Qi , Andrew Lim., “ freight consolidation and containerization problem”, European
Journal of Operational Research., 2013.
• Jeffery K. Cochran, Balaji Ramanujam “Carrier-mode logistics optimization of inbound supply chains for electronics
manufacturing”, International Journal of Production Economics, Vol 103, 2006, pp826–840.
REFERENCE
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31. • Khanittha Arayapan, Piyanut Warunyuwong.,“Logistics Optimization: Application of Optimization Modeling in Inbound
Logistics”, Thesis, Malardalen University Sweden.
• Nils Boysena,, Simon Emdea, Michael Hoeckb, Markus Kaudererc “ Part logistics in the automotive industry Decision
problems, literature review and research agenda” , European Journal of Operational Research 2014, PP 1–14.
• Ozsakalli G, Ozdemir D, Ozcan S, Sarioglu B and Dincer A, “Daily Logistics Planning With Multiple 3PLs: A Case Study in
a Chemical Company” Journal of Applied Research and Technology. Vol. 12, October 2014, pp985‐995.
• Paneerselvam, “Production and Operations Management”, ISBN-13, 2012.
• Scott R. Swensetha, Michael R. Godfrey “Incorporating transportation costs into inventory replenishment decisions”,
International Journal of Production Economics, 2002, vol 77 pp113–130.
• Seyed Davod Hosseini, Mohsen Akbarpour Shirazi, Behrooz KarimiDepartment., “Cross-docking and milk run logistics in a
consolidation network: A hybrid of harmony search and simulated annealing approach” Journal of Manufacturing Systems.,
2014, vol 33, pp567–577.
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32. Thank you
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