An Investigation into the Possibilities for Cost Saving in a Distribution Network with Demand Dependencies

Abstract

Inventory control is a subject that impacts more or less every section of most businesses, hence
companies today view it as a crucial problem of strategic importance (Axsäter, 2015). Managing
inventory is a complex task which can be made even more complex by considering multiple
items interacting with each other throughout the supply network. This master thesis attempts
to show, through a case study how the supply chain can be made more efficient by doing this in
a supply chain of large spare parts for heavy machinery.
In order to address the purpose, "investigate how companies can coordinate dependent demand
in their inventory management and distribution network and to determine the associated benefits
of doing this. A simulation tool has been developed in which a regular (S, s) policy has been
compared to a new model in which the inventory positions of the products that are likely to be
co-ordered are considered. Another attempt to make the supply chain more efficient was to stack
products on the pallets rather than sending them one product on each pallet.
The proposed model outperforms the (S, s) policy, mostly through savings in inventory costs and
fewer pallets in the warehouse. However, the behaviour of the model is hard to predict, it requires
a large amount of data and is also difficult to alter. The model performs very well when
implemented in supply chains which have a good flow of information and coordination amongst
supply chain partners,since it is reliant on the adequate availability of sales, production, warehousing
and products data. Therefore, it is the authors’ recommendation that companies that
do not have seamless information flows and high level of cooperation between supply chain players
do not adopt the model in its current state, since the benefits relative to the additional complexity
is small. It is also not recommended for companies that have short product life cycles
since they will likely not have the long term data needed to run the model well. Stacking the
products resulted in savings in labour and other costs and a reduction in the amounts of pallets
in the flow. However, while trying to keep the same service level, the tied up capital increased
significantly.

Popular Abstract

This master thesis was conducted as a single case study of a supply chain that produces and distributes spare parts for heavy machinery within Europe. Throughout the study it was noted that, whilst managing inventory is a complex task, this can be made even more complex by considering the demand dependencies of multiple items in the supply chain network. By running warehouses companies can better match the supply with their demand and this can be further enhanced by stacking products where possible to increase the stock per location. When products are stacked on top of each other for the inbound flow, the expected result of this is that the distribution cost per unit goes down.
This master thesis attempts to show, through this case study, how such complex supply chains can be made more efficient. In the results, we show that if the current (S, s) policy is maintained and the products are stacked, there is a potential for savings in the overall logistics cost. This is due to a decrease in the number of containers shipped and received, a decrease in the number of pallets handled as well as pallets in the logistics system.
To consider product affinity, a heuristic model that considers the stock of affiliated products when deciding on whether to order. The heuristic determines which product is associated with the largest saving, when ordering. The most beneficial pallet is added to a shipment, until the shipment is full. After which additional shipments are added until it is no longer beneficial to add additional shipments.
The proposed model outperforms the (S, s) policy, mostly through higher savings in inventory costs and fewer pallets in the warehouse. However, the behaviour of the model is hard to predict, it requires a large amount of data and is also difficult to alter to accommodate evolving markets.
The new model performs very well when implemented in supply chains which have a good flow of information and coordination amongst supply chain partners. Therefore, it is the authors’ recommendation that, companies that do not have seamless information flows and high level of cooperation between supply chain players do not adopt the model in its current state, since the benefits relative to the additional complexity is small. It is also not recommended for companies that have short product life cycles since they will not have the long-term data needed to run the heuristic accurately.

• author: Berggren, Erik and Nechavava, Rawlings
• supervisor: Peter Berling
• organization: Production Management
• course: MIOM01 20191
• year: 2019
• type: H2 - Master's Degree (Two Years)
• subject: Technology and Engineering
• keywords: Logistics, Inventory Control, Ordering, Dependencies, Demand Dependencies, coordinated Ordering
• language: English
• id: 8992531
• date added to LUP: 2019-10-15 14:34:04
• date last changed: 2019-10-15 14:34:04