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Creation of a Simulation Model based upon Process Mapping within Pipeline Management at Scania
Linköping University, Department of Management and Engineering, Logistics Management. Linköping University, The Institute of Technology.
Linköping University, Department of Management and Engineering, Logistics Management.
2013 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This is a Master’s Thesis that has been carried out at the Global Outbound Logistics department at Scania. Scania manufactures trucks, buses and engines. Some trucks and buses are delivered to markets where it, due to reduced customs duties and cheaper manpower, is more profitable to do the assembly locally at so called Regional Product Centres (RPCs). Since the components are produced far away from the RPC markets the lead times become long. In addition, the customers’ buying behaviour at the RPC markets is often not comparable to the European culture were a customer can accept to wait for weeks for a unit to be delivered. The long lead time in combination with the customer behaviour implies that the RPCs need to keep a certain selection of standard models of buses and trucks in stock. It has turned out to be difficult for the pipeline managers at the RPCs to place order volumes that correspond well to what will be delivered to the business units or distributors later on. The result of this is high stock levels at the RPCs, which leads to an important amount of tied up capital.

Due to what is explained above, the purpose of this study is “to create a simulation model, based upon a process mapping, that visualises future volume levels in the pipeline due to different demand and ordering scenarios”. The short term target, which is also the target of this study, is to increase the RPCs understanding for how different demand and ordering scenarios influence the future volume levels in the pipeline. The long term target is to reduce tied up capital by adjusting buffer levels and lead times, while still ensuring a certain service level. The model should contribute to more accurate decision making with respect to the previous mentioned aspects.

First, a high level process mapping was made in order to select which flows that were suitable for being subject for a detailed mapping. Second, a detailed mapping was made during which several RPC-, process- and function responsible were interviewed. After the detailed mapping, common denominators between the flows were identified and all activities were clustered into a solution that could be generalised and suitable for all flows. Factors such as lead times, deviation risks and capacity limitations were taken into account during the aggregation of activities.

When a common view of the different RPC flows had been created, the mathematical relationships for how the goods can move throughout the process could be established. Then, the development and validation of the simulation model, which was an iterative process, could start. A directive was to build the simulation model in Microsoft Excel. Interviews were made with experienced model creators in order to find out how to create a user-friendly and robust model. The creation of the simulation model started with the development of a structure and then the content of each part was defined. A final validation, which consisted of sensitivity analysis and user trials, was finally done in order to ensure the simulation models functioning and accuracy.

To conclude, a simulation model that will serve as a helpful tool for the RPCs when they are to decide which order volumes to place has been created. By clearly visualising the simulation results, the simulation model will hopefully increase the RPCs’ comprehension for how the pipeline works with respect to different ordering and demand scenarios.

On top of this, the method used, the process mapping and the mathematical relationships that have been defined are important input for a possible future development of a more permanent and robust non-Microsoft Excel solution. This solution could probably be even more precise, automatically updated and have an even higher granularity.

Place, publisher, year, edition, pages
2013. , 148 p.
Keyword [en]
Pipeline Management, Simulation Model, Process Mapping, Knock Down, Lead Time, Buffer Level, Supply Chain, Logistics Management
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-96797ISRN: LIU-IEI-TEK-A--13/01671--SEOAI: diva2:643886
External cooperation
Scania CV AB
Subject / course
Logistics Management
Available from: 2013-09-12 Created: 2013-08-27 Last updated: 2013-09-12Bibliographically approved

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