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Forming an Inventory Control Policy in a Stochastic Environment: A Case Study at Sandvik Crushing and Screening

Mattisson, Anders and Alsmarker, David (2018) MIOM05
Production Management
Abstract
Background: For most companies that handle large material flows there are buffers between different
stages in the supply chain, often referred to as inventory. The main reasons for having these inventories are
to achieve economies of scale when handling material flows and to buffer against uncertainties when
matching demand and supply. Hence, the main objective in inventory control is to decide when and how
much to order and by doing so, balance conflicting goals. These goals could be to reduce operational costs
and to reduce stock on hand while achieving a certain service level to the customers.



Purpose: Forming an inventory control policy for a new warehouse which is based on the demand from
both the production of... (More)
Background: For most companies that handle large material flows there are buffers between different
stages in the supply chain, often referred to as inventory. The main reasons for having these inventories are
to achieve economies of scale when handling material flows and to buffer against uncertainties when
matching demand and supply. Hence, the main objective in inventory control is to decide when and how
much to order and by doing so, balance conflicting goals. These goals could be to reduce operational costs
and to reduce stock on hand while achieving a certain service level to the customers.



Purpose: Forming an inventory control policy for a new warehouse which is based on the demand from
both the production of new crushers and from the aftermarket.



Research questions: (1) How to form an inventory control policy for a new warehouse? a) How to optimize
the parameters in this policy to minimize the ordering costs and the inventory holding costs? (2) How does
the lead time variability affect these costs?



Methodology: In this study, a framework presented by Yin (2009) and Hillier & Liebermann (2010) has
been used to construct the research design. The initial step was to specify the problem at hand before the
gathering of data was initiated which also included a literature study. Based on the gathered information,
an initial analysis of the current system was performed before the mathematical model which represents the
new inventory control policy was created. A statistical analysis of the lead times was conducted to provide
input to the model. Finally, the constructed model was evaluated in a sensitivity analysis.



Conclusion: Based on the analysis of sales data, a compound Poisson process was chosen as an appropriate
demand model. From the theoretical foundation and current practices at the case company, an (R, Q) policy
with periodic review was chosen as the new inventory control policy. Since the case company currently
experience variability in the lead times, this uncertainty was incorporated in the new policy. The study
showed that in the future state, where the case company would operate with a shared warehouse with 95%
fill rate and take stochastic lead times into consideration, the holding costs would increase while the
ordering costs would be reduced. When analyzing the effect of lowering the lead time variability in the new
policy, it was shown that the holding costs were reduced while the ordering costs increased. Finally, it was
concluded that in the best-case scenario where lead times are assumed constant, the total costs in the future
state would be reduced compared to the current system. (Less)
Please use this url to cite or link to this publication:
author
Mattisson, Anders and Alsmarker, David
supervisor
organization
course
MIOM05
year
type
M1 - University Diploma
subject
keywords
Inventory Control, Stochastic Lead Time, Stochastic Demand, Input Analysis, Optimization
other publication id
18/5602
language
English
id
8953383
date added to LUP
2018-06-27 14:49:15
date last changed
2018-06-27 14:49:15
@misc{8953383,
  abstract     = {{Background: For most companies that handle large material flows there are buffers between different 
stages in the supply chain, often referred to as inventory. The main reasons for having these inventories are 
to achieve economies of scale when handling material flows and to buffer against uncertainties when 
matching demand and supply. Hence, the main objective in inventory control is to decide when and how 
much to order and by doing so, balance conflicting goals. These goals could be to reduce operational costs 
and to reduce stock on hand while achieving a certain service level to the customers. 

 

Purpose: Forming an inventory control policy for a new warehouse which is based on the demand from 
both the production of new crushers and from the aftermarket. 

 

Research questions: (1) How to form an inventory control policy for a new warehouse? a) How to optimize 
the parameters in this policy to minimize the ordering costs and the inventory holding costs? (2) How does 
the lead time variability affect these costs? 

 

Methodology: In this study, a framework presented by Yin (2009) and Hillier & Liebermann (2010) has 
been used to construct the research design. The initial step was to specify the problem at hand before the 
gathering of data was initiated which also included a literature study. Based on the gathered information, 
an initial analysis of the current system was performed before the mathematical model which represents the 
new inventory control policy was created. A statistical analysis of the lead times was conducted to provide 
input to the model. Finally, the constructed model was evaluated in a sensitivity analysis. 

 

Conclusion: Based on the analysis of sales data, a compound Poisson process was chosen as an appropriate 
demand model. From the theoretical foundation and current practices at the case company, an (R, Q) policy 
with periodic review was chosen as the new inventory control policy. Since the case company currently 
experience variability in the lead times, this uncertainty was incorporated in the new policy. The study 
showed that in the future state, where the case company would operate with a shared warehouse with 95% 
fill rate and take stochastic lead times into consideration, the holding costs would increase while the 
ordering costs would be reduced. When analyzing the effect of lowering the lead time variability in the new 
policy, it was shown that the holding costs were reduced while the ordering costs increased. Finally, it was 
concluded that in the best-case scenario where lead times are assumed constant, the total costs in the future 
state would be reduced compared to the current system.}},
  author       = {{Mattisson, Anders and Alsmarker, David}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Forming an Inventory Control Policy in a Stochastic Environment: A Case Study at Sandvik Crushing and Screening}},
  year         = {{2018}},
}