7108IBA Supply Chain Modeling: SND Australia Supply Network Design

This report addresses the supply chain management challenges faced by SND Australia, which relies on an overseas supplier (OVS). The study examines the costs associated with sourcing from OVS and utilizing SND's subsidiary, DMS, for production. It analyzes transportation costs between cities, evaluates the optimal location for a DMS subsidiary (Melbourne), and assesses the management of international seaports. The report concludes that leveraging DMS services is preferable due to reasonable road transportation costs and the ability to adjust production based on demand. Sensitivity analyses are conducted to evaluate the impact of changes in parameters like lead time and demand levels. The report also explores the potential impact of shifting a portion of road transport to domestic or coastal transport, suggesting a possible shift towards sourcing from OVS under those conditions. This document is available on Desklib, a platform offering AI-based study tools and solved assignments for students.

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7108IBA SUPPLY CHAIN MODELING

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Table of contents
1.0 Overview..............................................................................................................................3
2.0 Lowest cost for SND............................................................................................................3
The cost related to DMS............................................................................................................4
The road transportation cost of SND.........................................................................................4
3.0 The location for the DMS and its location...........................................................................5
4.0 Management of the international seaports...........................................................................6
5.0 Management of the domestic transport................................................................................6
6.0 Conclusion of the model......................................................................................................7
7.0 Sensitivity of the solution to parameters..............................................................................7
8.0 Sensitivity of the solution to demands.................................................................................8
9.0 Transportation cost and its impact on the solution...............................................................8
10.0 Impacts of network optimisation in supply chain management.........................................8
Reference....................................................................................................................................9

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1.0 Overview
Due to the improvement in the connectivity and the communication, the business operations
are becoming more interconnected to each other. The different components of the production
process of business are taking place in different regions of the world. While this allows the
organisation to enjoy some of the conveniences, it also leads to complexity. This requires the
management of the company to continuously monitor the supply chain modelling. One of the
interesting point regarding the supply chain modelling and management is that it takes into
account the changes in the external environment of the business as well. As a result, it is
easier for the businesses to keep a track on the changing logistics costs related to the changes
in the demand for the products and the activity of the other players of the market
(Christopher, 2016). The supply chain modelling and management also provides the
organisation with flexibility and resilience in order to deal with any kind of adverse situation
regarding the operation. Hence, in the modern world with interconnected business operations
established in different parts of the world, it is important to analyse the supply chain models.
This study is related to supply chain management problem pertaining to a company based in
Australia. The SND Company is currently facing supply chain issues where it is supplied
from OVS, a foreign organisation. The cost of supplying the products to SND is till the ports
of each of the cities. However, the business of the SND faces a lot of volatility due to the
changes in the demand from the side of the customers of the market. This also leads the
organisation to exchange some of the supplied goods among the different cities of the
country. For the transpiration among the different cities of the country, the company uses
land transportation. DMS is the subsidiary of SND which has some of the productive capacity
and provides support to SND in case of peak demands.
2.0 Lowest cost for SND
Demand and unit production cost for SND (Table 1 in question)
Demand at Units Produce at Unit Cost
Adelaide 420 DMS Adelaide $450
Brisbane 870 DMS Brisbane $480
Melbourne 1250 DMS Melbourne $505
Perth 930 DMS Perth $490
Sydney 1310 DMS Sydney $515
OVS $440

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Table 1: The demand and the unit production cost for SND
(Source: Stadtler, 2015)
The above figure shows the cost of SND per unit in different cities of the country. As per the
information of the table, DMS Adelaide has the lowest cost of production compared to the
other locations of the country (Schönsleben, 2016). However, if per unit production is taken
in to account, per unit cost of both Melbourne and Sydney is less due to the high demand that
it has for the products. The different components of the cost are presented below:
The cost related to DMS
Produce at DMS Unit Cost
DMS Adelaide $450
DMS Brisbane $480
DMS Melbourne $505
DMS Perth $490
DMS Sydney $515
Table 2: The cost of production in different locations of the country
(Source: Monczka et al.2015)
The above table shows the cost of operation at different DMS of the company. It is cheaper to
produce in DMS Adelaide as the overall cost is around $450 which is less compared to other
locations. It is important to note that, the DMS Sydney has the production cost of $515 which
is the highest among all the locations. DMS are the subsidiary production units if SND which
will be used to source the products in case of high demand in the market. However, one of the
pitfalls of producing in the DMS is that it can only produce 500 units maximum in each of the
location and hence the management of SND needs to use a combination of different locations
based on the cost of production and the demand for the products in the market. Hugos (2018)
stated that, the logistic modelling allows the management of the organisation to choose
different locations based on the different types of demand in the market.
The road transportation cost of SND
Road Transport
Cost
($)
Adelaid
e
Brisban
e
Melbourn
e
Pert
h Sydney Total
Adelaide $0 $0 $300 $0 $0 $300
Brisbane $0 $0 $500 $0 $150 $650

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Melbourne $0 $0 $0 $0 $0 $0
Perth $0 $0 $0 $0 $0 $0
Sydney $0 $0 $0 $0 $0 $0
Demand $0 $0 $800 $0 $150 $950
SND TOTAL
COST
$21,62,491.4
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Table 3: The road transportation cost of SND
(Source: Wang et al. 2016)
The above table depicts that total road transportation cost to the company is $2162491.47.
This is related to the total demand worth of $950. It is important to note that transportation to
Melbourne from Adelaide and Brisbane is high whereas other costs are low.
Sea transportation costs
Sea transport cost and lead time from overseas supplier to cities (table 2 in
question)
Port $/40' container $/20' container $/LCL unit Lead Time (days)
Adelaide $2,000 $1,200 $25 30
Brisbane $1,600 $1,000 $20 21
Melbourne $1,800 $1,100 $23 28
Perth $1,200 $700 $15 18
Sydney $1,650 $1,050 $22 25
Table: The sea transportation cost for different cities
(Source: )
The table above shows the cost of transporting the products in different cities of the country.
The cost is maximum for the case of Adelaide and minimum for Perth. However, it is
important to note that the lead time for each of these cities are also different from each other.
While the lead time in case of Adelaide is 30 days the lead time for the case of Perth is 18.
Perth also have the lowest $/LCL unit value as well.
3.0 The location for the DMS and its location
Road transport cost per unit between cities (table 3 in question)
($) Adelaide Brisbane Melbourne Perth Sydney
Adelaide $0 $35 $10 $35 $25
Brisbane $35 $0 $25 $70 $15
Melbourne $10 $25 $0 $45 $15
Perth $35 $70 $45 $0 $55
Sydney $25 $15 $15 $55 $0

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Table 4: The transport cost per unit between the different cities
(Source: Stevens & Johnson, 2016))
The table above points out different transpiration cost from one city to another which SND
may use in the wake of high demand. While there is no cost of product movement within the
city, there is a different cost associated with transportation among different cities. However,
in terms of the average cost, Melbourne is the right place for the subsidiary given its high
demand and average transportation cost to different other locations of DMS. This location
makes sense as it has high demand for the products (Ho et al. 2015).
4.0 Management of the international seaports
Demand
at
Lead Time in
days
Purchase
Cost
Pipeline Stock
Cost
Total Cost from
OVS
Unit Cost from
OVS
Adelaide 30 $0 $0.00 $0 $0.00
Brisbane 21 $4,03,400 $3,481.40 $4,06,881 $452.09
Melbour
ne 28 $5,38,800 $6,199.89 $5,45,000 $454.17
Perth 18 $4,15,150 $3,070.97 $4,18,221 $449.70
Sydney 25 $5,82,950 $5,989.21 $5,88,939 $453.03
$19,59,041
Table 5: demand and the cost at different seaports
(Source: Touboulic, & Walker, 2015)
The above table shows the lead time, purchase cost, pipeline stock cost and the total cost
from OVS. In terms of the lead time, Perth is the lowest however; its total cost is $418221. In
terms of the management, the shipments will be made direct to each of the seaports and
production capacity of each of the units needs to be increased so that, products can be
supplied to other parts of the country in order to extract the benefits from the shipment
(Grant, Wong & Trautrims, 2017). The total cost of shipment in different international ports
will be $1959041 which may vary depending on the demand for the products in the market.
5.0 Management of the domestic transport
Deman
d at
Units Received
from OVS
40'
container
20'
containe
r
LCL
container
20'
Container
Transport Cost
Purchase
Cost
Adelaid
e 0 0 0 0 $0 $0
Brisban 900 4 1 0 $7,400 $4,03,40

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e 0
Melbou
rne 1200 6 0 0 $10,800
$5,38,80
0
Perth 930 4 1 0.3 $5,950
$4,15,15
0
Sydney 1300 6 1 0 $10,950
$5,82,95
0
Table 6: The cost for domestic transport
(Source: Ross, 2016)
The domestic transports are done through the containers of 20’ and 40’ which further can
hold 200 and 100 units of the products respectively. Given the DMS subsidiary in Adelaide,
the transportation cost is lowest for Perth and highest for Sydney. As per the demand and the
total purchase cost is also shown in the above table (Chin, Tat & Sulaiman, 2015). The
domestic transportation is done through the comparison of demand and the total purchase
cost for each of the locations .
6.0 Conclusion of the model
The model concludes that it is preferable to use the services of DMS rather than the services
of the OVS. This is due to the fact that, the DMS locations are different big cities of the
country and the road transportation cost is reasonable. Although, each of the units of
production is can produce only 500 units, the organisation needs to source supplies from
different locations based on the cost and the demand. Apart from that, other advantage of
using the service of DMS includes the operational cost which the organisation can remove
during the time of low demand as these DMS units will then operate autonomously to
manage their own cost of operation.
7.0 Sensitivity of the solution to parameters
The solution is sensitive to the changes in different parameters pertaining to the
transportations of the goods in the locations. For example, the lead time, changes of which
can alter the cost of operation of the company and the sourcing decision from different DMS
of the organisations (Alftan et al. 2015). The lead time changes creates problem for the
shipment timelines and hence the cost of transpiration and hence the production cost of the
organisation goes up. The use of solver in the model has ensured to deal with the changes
parameters such as the changes in the unit cost and the lead time for each of the shipments.

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8.0 Sensitivity of the solution to demands
The solution of the model is also sensitive to the changes in the demands in the market as
well. The different demand level in the market will require different levels of sourcing from
DMS of the organisation (Maloni et al. 2017). The changes in the demand will also impacts
on the cost of production and the transportation cost as well. The use of solver in the model
has allowed the cells to change depending on the values of the other cells (Hohenstein et al.
2015). The changes in demand can be put in the model and solver will adjust to provide the
accurate cost and production detail from each of the DMS as per the demand.
9.0 Transportation cost and its impact on the solution
If the domestic transport and coastal transport can be used in 10% of the road transport, then
the solution would change. The use of solver in the model has allowed the result to change
with the changes in the parameters. In that case, it will be preferable for the SND to get the
supplies from the OVS and distribute in different DMS locations as per the need and the
market demand for the product. In addition to that abrupt changes in the demand can also be
managed through this as well.
10.0 Impacts of network optimisation in supply chain management
The network optimisation is a concept through which the businesses optimise the supply
chain connections in order to minimise the operational cost of the business. In this solution,
the lead time and the demand variability have not been accounted and hence optimisation in
this case is static. Dynamic optimisation allows the organisation to include the changes in the
parameters which in turn allows the management to take action based the result. This type of
optimisation allows minimising the cost of operation given the output level guided by the
market demand. In order to trace the change in demand and its impacts on operation, dynamic
optimisation is important.

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