Risk‐ och exponeringsreducering i ett tillverkande företag

Abstract

The foundation of this thesis has been to investigate the possibilities of giving Stena Aluminium, a
company recycling aluminium, increased control to regulate and steer the risk they are taking when
exposing raw material and finished goods. Stena Aluminium wants to minimize the risk of losses on
raw material and finished goods when prices change. This is a large problem for instance when raw
material is stored a long time thus making it sensitive to volatile prices. Today, Stena Aluminium
bases their operations on the experience and tested methods that exists in the company and tried
methods without actual possibilities for controlled optimization and regulation. After an evaluation
of today’s conditions we arrived at the conclusion that we need to create a model to be able to
systematically approach the problem of risk and exposure.
To investigate this, we have put forward some questions at issue that initially control if Stena
Aluminium’s forecasting is sufficiently good enough to base subsequent investigations on. The basis
of a low level of exposure is that the forecasts have a forecasting error as small as possible. To
measure how good Stena Aluminium’s forecasts are we tried to forecast the actual result ourselves
using quantitative methods. To sharpen our forecasting we classified their articles according to the
demand pattern, making it possible to choose the best forecasting method for respective class. We
concluded that Stena Aluminium’s own qualitative way of forecasting is to be preferred, as they
actually have a very good take on the demand a month in advance, but that quantitative forecasting
could be used as a complement to level out the quality of the forecasts. When having an almost
deterministic demand, uncertainties in time are bigger than uncertainties in quantity.
The next step was so explore the possibility of affecting the exposure of raw material through
optimizing of purchasing. We reduced the problem to a minimization of the total cost by introducing
concepts like carrying cost, ordering cost and an easy way to vary the carrying cost on the basis of
volatility of the price. Optimal purchasing lots were then established by using a cost optimizing
algorithm on varying demand. We also tested a way of taking forward prices into accord by varying
the carrying cost, making it possible to take advantage of low price. A significant reduction of the
total cost was, however, not found.
We also evaluated different ways of calculating safety time. To systematically establish appropriate
safety times for finished goods we recommend Stena Aluminium to register their customers´
tendencies to change the delivery date of their orders and on the basis of this calculate the safety
times.
We compel Stena Aluminium to register more data to be able to have enough information to
evaluate all parts of the material management in a thorough way. This will help in future
performance improving projects.

• author: Almberg, Per and Ehlers, Jens
• supervisor: Peter Berling
• organization: Production Management
• course: MIO920
• year: 2008
• type: M1 - University Diploma
• subject: Technology and Engineering
• keywords: exposure, risk, stock, forward, contact, safety stock, safety time, carrying cost, inventory management, ordering cost, Stena Aluminum, aluminium
• other publication id: 08/5295
• language: Swedish
• id: 1979201
• date added to LUP: 2011-06-17 12:44:49
• date last changed: 2011-06-20 11:19:43