Skip to main content

LUP Student Papers

LUND UNIVERSITY LIBRARIES

Lagerstyrning av reservdelar hos Mantena Sverige AB

Stefansson, Pontus and Ståhl, Oscar (2014) MIO920
Production Management
Abstract
Mantena Sverige AB is responsible for providing maintenance to Skånetrafiken’s
trains. The maintenance is done in their depot located outside of Helsingborg.
Previously all sourcing and inventory control of spare parts used for repairs has been
done by the company who built the trains and who has a warehouse located in the
same building as Mantena’s depot. However, Mantena is currently in the process of
establishing their own organization for sourcing and inventory control. The purpose of
this master’s thesis is to construct a tool that will help Mantena in the development
of an inventory control system.
The tool is built using Excel and Visual Basic and provides Mantena with forecasts of
future demand as well as an (R,Q)-policy... (More)
Mantena Sverige AB is responsible for providing maintenance to Skånetrafiken’s
trains. The maintenance is done in their depot located outside of Helsingborg.
Previously all sourcing and inventory control of spare parts used for repairs has been
done by the company who built the trains and who has a warehouse located in the
same building as Mantena’s depot. However, Mantena is currently in the process of
establishing their own organization for sourcing and inventory control. The purpose of
this master’s thesis is to construct a tool that will help Mantena in the development
of an inventory control system.
The tool is built using Excel and Visual Basic and provides Mantena with forecasts of
future demand as well as an (R,Q)-policy where the re-order points and order
quantities needed to meet a predefined service requirement are calculated. The
forecasts are done using Croston’s method and the modified version of it proposed by
Syntetos and Boylan. The order quantity is calculated by using the economic order
quantity. The re-order point is calculated by using a compound process where a
Bernoulli process represents time intervals between demands, and an empirical
distribution represents demand sizes.
When building the tool the authors strived towards making it reliable, functional and
user friendly. The aim was that any employee at Mantena should be able to use it,
despite any possible lack of knowledge about inventory control.
Analysis of the historical demand data revealed that many spare parts had only been
demanded a handful of times thus making the statistical calculations for these spare
parts less reliable. For these spare parts an alternative, qualitative, method to
determine re-order points and order quantities is presented in the report.
During the work process the authors identified several areas that should be
investigated further in order to improve both the tool in itself and Mantena’s work
with inventory in general. Among these are the defining of suitable service levels and
the defining of costs related to handling the inventory the most important. (Less)
Please use this url to cite or link to this publication:
author
Stefansson, Pontus and Ståhl, Oscar
supervisor
organization
course
MIO920
year
type
M1 - University Diploma
subject
keywords
Forecasting, Inventory Control, (R, Q)-policy, Spare Parts
other publication id
14/5486
language
Swedish
id
4516488
date added to LUP
2014-06-26 13:43:11
date last changed
2014-06-26 13:43:11
@misc{4516488,
  abstract     = {{Mantena Sverige AB is responsible for providing maintenance to Skånetrafiken’s
trains. The maintenance is done in their depot located outside of Helsingborg.
Previously all sourcing and inventory control of spare parts used for repairs has been
done by the company who built the trains and who has a warehouse located in the
same building as Mantena’s depot. However, Mantena is currently in the process of
establishing their own organization for sourcing and inventory control. The purpose of
this master’s thesis is to construct a tool that will help Mantena in the development
of an inventory control system.
The tool is built using Excel and Visual Basic and provides Mantena with forecasts of
future demand as well as an (R,Q)-policy where the re-order points and order
quantities needed to meet a predefined service requirement are calculated. The
forecasts are done using Croston’s method and the modified version of it proposed by
Syntetos and Boylan. The order quantity is calculated by using the economic order
quantity. The re-order point is calculated by using a compound process where a
Bernoulli process represents time intervals between demands, and an empirical
distribution represents demand sizes.
When building the tool the authors strived towards making it reliable, functional and
user friendly. The aim was that any employee at Mantena should be able to use it,
despite any possible lack of knowledge about inventory control.
Analysis of the historical demand data revealed that many spare parts had only been
demanded a handful of times thus making the statistical calculations for these spare
parts less reliable. For these spare parts an alternative, qualitative, method to
determine re-order points and order quantities is presented in the report.
During the work process the authors identified several areas that should be
investigated further in order to improve both the tool in itself and Mantena’s work
with inventory in general. Among these are the defining of suitable service levels and
the defining of costs related to handling the inventory the most important.}},
  author       = {{Stefansson, Pontus and Ståhl, Oscar}},
  language     = {{swe}},
  note         = {{Student Paper}},
  title        = {{Lagerstyrning av reservdelar hos Mantena Sverige AB}},
  year         = {{2014}},
}