Optimization of aftermarket logistics with dual supply chains for Sandvik AB

Abstract

Background: Aftermarket logistics is important for a manufacturing company to maintain
customer satisfaction in the long run. However, the supply chain set for aftermarket parts is equally
crucial as the original equipment. Modification or optimization of the logistics systems for slow-moving aftermarket items is inevitable. Sandvik, an engineering company in the mining industry
is now interested in optimizing its aftermarket logistics. The analysis will be for the stone crusher
models for which original equipment is assembled in China, however the aftermarket items are
still supplied from the production site in Sweden. Sandvik is considering even sourcing the
aftermarket parts from the suppliers based in China. The company expects the optimization
decision will help reduce the complexity of the supply chain and the overall total costs. Before
making the decision, it is important to study the logistics and administrative related factors and its
impact on the optimized supply chain.
Purpose: The purpose will be to analyze the decision of phasing out selected aftermarket items
from the production unit (PU) Svedala alongside developing a generic decision model which will
support a similar decision-making process in the future.
Methodology: Case-based research to analyze the change in different costs, lead times and other
qualitative aspects if the aftermarket items are moved to the sister site in China and comparing it
with the current values. Design science is applied to develop a decision model which will be
generic to all crusher models. All related data were collected from the case company. The master
thesis follows an abductive research approach.
Conclusion: Sandvik should implement a single SC for stone crusher models AG120 & GA230
by sourcing the equipment and aftermarket items from the suppliers based in China. This will
ensure these slow-moving items have a linear supply chain with same efficiency at lower total
costs. A generic decision model is present which will help the company take similar optimization
decisions in the future. Major factors like annual demand, total costs, lead times, after-effects on
manufacturing as well as trade compliances are incorporated in the decision model. Sandvik should
search for alternate back-up suppliers to reduce the risk of high supplier dependency due to single
sourcing. Better information sharing between the DC and production sites can reduce the bullwhip
effect. Longer lead-times can be compensated by having higher safety stocks and efficient
inventory control
Keywords: Supply chain optimization, Aftermarket logistics, Single and Dual supply chains,
Decision Model

Popular Abstract

Optimization of aftermarket logistics with dual supply chains for Sandvik

In recent years an exponential trend has been observed in which manufacturing companies are
increasingly buying and manufacturing at a global level in order to improve cost efficiency,
multiple procurement options and geographically broaden their operational bases. As a result,
the challenges of supply chain management are becoming more complex. Companies are now
focusing on integrating their supply chain design, planning and management to gain the benefits
of operational efficiency, lower costs and increased customer efficiency.

A well-defined and efficient supply chain can give businesses a competitive advantage with
reduced costs, increased revenue and greater customer value leading to higher profit margins
and long-term relationships with customers. Sandvik, a global engineering company in the
mining industry has now recognized the importance of optimizing its aftermarket supply to
achieve similar benefits. This master thesis will focus on analyzing the decision of optimizing
the aftermarket supply for products in order to have a near-optimal logistics setup. The second
purpose is also to build a decision model that will act as a framework for the company to follow
while making similar optimization decisions in the future.

The analysis will be for the products for which original equipment is assembled in China,
however, the aftermarket items are supplied from the production site in Sweden. Sandvik is
considering even sourcing the aftermarket parts from the suppliers based in China. Before
making the decision, it is important to study the logistics and administrative related factors and
its impact on the optimized supply chain. Logistics aspects like annual demand, total costs, lead
times, manufacturing times were analyzed and compared for both the alternatives. Similarly,
administrative aspects like trade compliances and related costs like import duties were taken
into consideration. The company’s decision to optimize the aftermarket supply chain is
considered as a strategic decision which will have long term effects on the cost and
administration.

The total cost is observed to decrease considerably in the optimized supply chain. Apart from
the cost benefits, the optimization of the aftermarket contributes to simplifying the supply chain.
Since both original equipment and aftermarket parts will be sourced from China, it will generate
high-quality data in the company’s information systems. It was observed that the lead times
will be increased in the alternate supply chain. However higher lead times should not be the
only deciding factor about the optimization decision and this shortcoming does not overshadow
other advantages of having a single supply chain for slow-moving items.

The problem of higher lead time can be overcome by having in place efficient supply chain
planning strategies for better customer demand fulfillment. Effective inventory control measures
like opting for high order quantity values will help maintain the required service levels which
are the backbone of spare parts logistics. Sandvik can use economies of scale to negotiate for
better standard costs and induce healthy supplier competition.

Based on the steps followed in the analysis, a generic decision model was developed which acts
as a framework for the case company to follow while analyzing the decision on optimizing the
aftermarket supply chain. It provides a step-by-step procedure to analyze and compare the
supply chain before and after optimization. It also provides the user with the type of data that
will be required to execute the action mentioned at each step. It also mentions the people who
can be contacted to help with the analysis at each stage. We believe the decision model will
help the company in all future decision making about the optimization process.

• author: Srinivasan, Gopalakrishnan and Hingmire, Akshay
• supervisor: Jan Olhager
• organization: Department of Industrial Management and Logistics; Engineering Logistics
• course: MTTM02 20201
• year: 2020
• type: H2 - Master's Degree (Two Years)
• subject: Technology and Engineering
• report number: 5913
• language: English
• id: 9012345
• date added to LUP: 2020-06-03 13:38:51
• date last changed: 2020-06-03 13:38:51