Plant Simulation for Order Planning : A Discrete Event Simulation Project at Volvo Trucks in Umeå

Detta är en Uppsats för yrkesexamina på avancerad nivå från Umeå universitet/Institutionen för matematik och matematisk statistik

Författare: Martin Carlestav; André Paulsson; [2015]

Nyckelord: ;

Sammanfattning: Abstract Volvo Trucks’ plant in Umeå produces the truck’s cab frame and the plant is divided into four production units, named ”driftsområden” (DO). Unlike the rest of the plant, who uses JIT manufacturing, DO2 uses traditional prediction based production. The management within Volvo Trucks suspects that the combination of prediction based production and JIT manufacturing entails unnecessary costs. At the same time they are uncertain if there is enough time for DO2 to produce the necessary components, in the given time frame, using JIT. It is important for Volvo Trucks to understand the consequences of making changes within DO2’s production parameters. This entails the need of a tool able to analyze how changes within DO2’s production will affect the total production of cabs. The problem is defined as: How can a macro simulation model be implemented and used in order to analyze how changes in production parameters for DO2 affect the total production for Volvo Trucks’ plant in Umeå?  The result is an implemented simulation model in Plant Simulation. The result highlights some components that are crucial when modelling the DO2 production unit:  The excel files, named “kapabilitetsfiler”, used to supervise and ensure that DO2 produces according to the production planning, contain lots of data which would be overwhelming retrieving elsewhere. The sales predictions, together with the dependency between the cab articles, are necessary. Without these components it is impossible to conduct a prediction based production planning, which fuels the production in DO2. The usage of a “black-box” to represent the production units proceeding DO2 is desirable, since it illustrates how the total production is affected due to changes in DO2. A simulation model that has an appropriate level of detail is a must. If the level of detail is too high the simulation model will run slowly and use too much computational power.

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